2022

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25 pages, 6310 KiB

Open AccessArticle

Energy Efficiency through the Implementation of an AI Model to Predict Room Occupancy Based on Thermal Comfort Parameters

by Shahira Assem Abdel-Razek, Hanaa Salem Marie, Ali Alshehri and Omar M. Elzeki

Sustainability 2022, 14(13), 7734; https://doi.org/10.3390/su14137734 - 24 Jun 2022

Cited by 19 | Viewed by 2966

Abstract

Room occupancy prediction based on indoor environmental quality may be the breakthrough to ensure energy efficiency and establish an interior ambience tailored to each user. Identifying whether temperature, humidity, lighting, and CO₂ levels may be used as efficient predictors of room occupancy [...] Read more.

Room occupancy prediction based on indoor environmental quality may be the breakthrough to ensure energy efficiency and establish an interior ambience tailored to each user. Identifying whether temperature, humidity, lighting, and CO₂ levels may be used as efficient predictors of room occupancy accuracy is needed to help designers better utilize the readings and data collected in order to improve interior design, in an effort to better suit users. It also aims to help in energy efficiency and saving in an ever-increasing energy crisis and dangerous levels of climate change. This paper evaluated the accuracy of room occupancy recognition using a dataset with diverse amounts of light, CO₂, and humidity. As classification algorithms, K-nearest neighbors (KNN), hybrid Adam optimizer–artificial neural network–back-propagation network (AO–ANN (BP)), and decision trees (DT) were used. Furthermore, this research is based on machine learning interpretability methodologies. Shapley additive explanations (SHAP) improve interpretability by estimating the significance values for each feature for classifiers applied. The results indicate that the KNN performs better than the DT and AO-ANN (BP) classification models have 99.5%. Though the two classifiers are designed to evaluate variations in interpretations, we must ensure that they have accurate detection. The results show that SHAP provides successful implementation following these metrics, with differences detected amongst classifier models that support the assumption that model complexity plays a significant role when predictability is taken into account. Full article

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15 pages, 859 KiB

Open AccessArticle

Energy-Saving Task Scheduling Based on Hard Reliability Requirements: A Novel Approach with Low Energy Consumption and High Reliability

by Qingfeng Chen, Yu Han, Jing Wu and Yu Gan

Sustainability 2022, 14(11), 6591; https://doi.org/10.3390/su14116591 - 27 May 2022

Cited by 3 | Viewed by 1440

Abstract

With the increasing complexity of application situations in multi-core processing systems, how to assure task execution reliability has become a focus of scheduling algorithm research in recent years. Most fault-tolerant algorithms achieve hard reliability requirements through task redundancy, which increases energy consumption and [...] Read more.

With the increasing complexity of application situations in multi-core processing systems, how to assure task execution reliability has become a focus of scheduling algorithm research in recent years. Most fault-tolerant algorithms achieve hard reliability requirements through task redundancy, which increases energy consumption and contradicts the concept of sustainable development. In this paper, we propose a new algorithm called HDFE (Heterogeneous-Dag-task-fault-tolerance-energy-efficiency algorithm) that combines DVFS technology and task replication technology to solve the scheduling problem of DAG applications concerning energy-saving and hard reliability requirements in heterogeneous multi-core processor systems. Our algorithm is divided into three phases: the priority calculation phase, the task replication phase, and the task assignment phase. The HDFE algorithm achieved energy savings while meeting hard reliability requirements for applications, which was based on the interrelationship between reliability and energy consumption in filtering task replicas. In the experimental part of this paper, we designed four comparison experiments between the EFSRG algorithm, the HRRM algorithm, and the HDFE algorithm. The experimental results showed that the energy consumption of task scheduling using the HDFE algorithm is lower than other algorithms under different scales, thus achieving energy savings and complying with the concept of sustainable development. Full article

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24 pages, 506 KiB

Open AccessArticle

Sustainable Adoption of E-Government from the UTAUT Perspective

by Mosleh Zeebaree, Mary Agoyi and Musbah Aqel

Sustainability 2022, 14(9), 5370; https://doi.org/10.3390/su14095370 - 29 Apr 2022

Cited by 19 | Viewed by 4039

Abstract

This paper attempts to study the sustainable adoption of e-government services in northern Iraq. The well-known unified theory of acceptance and use of technology (UTAUT) is applied and extended to study citizens’ behavior regarding e-government services. A quantitative technique was utilized to gauge [...] Read more.

This paper attempts to study the sustainable adoption of e-government services in northern Iraq. The well-known unified theory of acceptance and use of technology (UTAUT) is applied and extended to study citizens’ behavior regarding e-government services. A quantitative technique was utilized to gauge the efficiency of the model. Overall, 371 replies were received through distributing samples. SPSS software was used for the data evaluation. Two extra constructs were introduced in the study, i.e., “Trust of system (TOS)” and “Ethics of Internet (EOI)”, into the original UTAUT as the theoretical extension. The findings indicate that all constructs have a significant influence on the intention to use e-government services. Moreover, the EOI moderates the effects of TOS on social impacts (SI), performance expectancy (PE), and behavior intention (BI). The results also indicated that there were statistically significant differences in the demographic characteristics of age, educational level excluding gender, and behavioral intention to use e-government services. The study’s results support most of the hypotheses. The results contribute to a better knowledge of the factors affecting the sustainable adoption of e-government in northern Iraq. Full article

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2021

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13 pages, 34651 KiB

Open AccessArticle

Indoor Distance Measurement System COPS (COVID-19 Prevention System)

by Minchan Shin and Nammee Moon

Sustainability 2021, 13(9), 4738; https://doi.org/10.3390/su13094738 - 23 Apr 2021

Cited by 5 | Viewed by 2554

Abstract

With the rapid spread of coronavirus disease 2019 (COVID-19), measures are needed to detect social distancing and prevent further infection. In this paper, we propose a system that detects social distancing in indoor environments and identifies the movement path and contact objects according [...] Read more.

With the rapid spread of coronavirus disease 2019 (COVID-19), measures are needed to detect social distancing and prevent further infection. In this paper, we propose a system that detects social distancing in indoor environments and identifies the movement path and contact objects according to the presence or absence of an infected person. This system detects objects through frames of video data collected from a closed-circuit television using You Only Look Once (v. 4) and assigns and tracks object IDs using DeepSORT, a multiple object tracking algorithm. Next, the coordinates of the detected object are transformed by image warping the area designated by the top angle composition in the original frame. The converted coordinates are matched with the actual map to measure the distance between objects and detect the social distance. If an infected person is present, the object that violates the movement path and social distancing of the infected person is detected using the ID assigned to each object. The proposed system can be used to prevent the rapid spread of infection by detecting social distancing and detecting and tracking objects according to the presence of infected persons. Full article

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13 pages, 2012 KiB

Open AccessArticle

Prevention of Mountain Disasters and Maintenance of Residential Area through Real-Time Terrain Rendering

by Su-Kyung Sung, Eun-Seok Lee and Byeong-Seok Shin

Sustainability 2021, 13(5), 2950; https://doi.org/10.3390/su13052950 - 09 Mar 2021

Cited by 3 | Viewed by 1807

Abstract

Climate change increases the frequency of localized heavy rains and typhoons. As a result, mountain disasters, such as landslides and earthworks, continue to occur, causing damage to roads and residential areas downstream. Moreover, large-scale civil engineering works, including dam construction, cause rapid changes [...] Read more.

Climate change increases the frequency of localized heavy rains and typhoons. As a result, mountain disasters, such as landslides and earthworks, continue to occur, causing damage to roads and residential areas downstream. Moreover, large-scale civil engineering works, including dam construction, cause rapid changes in the terrain, which harm the stability of residential areas. Disasters, such as landslides and earthenware, occur extensively, and there are limitations in the field of investigation; thus, there are many studies being conducted to model terrain geometrically and to observe changes in terrain according to external factors. However, conventional topography methods are expressed in a way that can only be interpreted by people with specialized knowledge. Therefore, there is a lack of consideration for three-dimensional visualization that helps non-experts understand. We need a way to express changes in terrain in real time and to make it intuitive for non-experts to understand. In conventional height-based terrain modeling and simulation, there is a problem in which some of the sampled data are irregularly distorted and do not show the exact terrain shape. The proposed method utilizes a hierarchical vertex cohesion map to correct inaccurately modeled terrain caused by uniform height sampling, and to compensate for geometric errors using Hausdorff distances, while not considering only the elevation difference of the terrain. The mesh reconstruction, which triangulates the three-vertex placed at each location and makes it the smallest unit of 3D model data, can be done at high speed on graphics processing units (GPUs). Our experiments confirm that it is possible to express changes in terrain accurately and quickly compared with existing methods. These functions can improve the sustainability of residential spaces by predicting the damage caused by mountainous disasters or civil engineering works around the city and make it easy for non-experts to understand. Full article

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16 pages, 6042 KiB

Open AccessArticle

A Video Captioning Method Based on Multi-Representation Switching for Sustainable Computing

by Heechan Kim and Soowon Lee

Sustainability 2021, 13(4), 2250; https://doi.org/10.3390/su13042250 - 19 Feb 2021

Cited by 6 | Viewed by 2375

Abstract

Video captioning is a problem that generates a natural language sentence as a video’s description. A video description includes not only words that express the objects in the video but also words that express the relationships between the objects, or grammatically necessary words. [...] Read more.

Video captioning is a problem that generates a natural language sentence as a video’s description. A video description includes not only words that express the objects in the video but also words that express the relationships between the objects, or grammatically necessary words. To reflect this characteristic explicitly using a deep learning model, we propose a multi-representation switching method. The proposed method consists of three components: entity extraction, motion extraction, and textual feature extraction. The proposed multi-representation switching method makes it possible for the three components to extract important information for a given video and description pair efficiently. In experiments conducted on the Microsoft Research Video Description dataset, the proposed method recorded scores that exceeded the performance of most existing video captioning methods. This result was achieved without any preprocessing based on computer vision and natural language processing, nor any additional loss function. Consequently, the proposed method has a high generality that can be extended to various domains in terms of sustainable computing. Full article

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18 pages, 3811 KiB

Open AccessArticle

A Structure Landmark-Based Radio Signal Mapping Approach for Sustainable Indoor Localization

by Tao Liu, Xing Zhang, Huan Zhang, Nadeem Tahir and Zhixiang Fang

Sustainability 2021, 13(3), 1183; https://doi.org/10.3390/su13031183 - 23 Jan 2021

Cited by 5 | Viewed by 1829

Abstract

Low cost and high reproducible is a key issue for sustainable location-based services. Currently, Wi-Fi fingerprinting based indoor positioning technology has been widely used in various applications due to the advantage of existing wireless network infrastructures and high positioning accuracy. However, the collection [...] Read more.

Low cost and high reproducible is a key issue for sustainable location-based services. Currently, Wi-Fi fingerprinting based indoor positioning technology has been widely used in various applications due to the advantage of existing wireless network infrastructures and high positioning accuracy. However, the collection and construction of signal radio map (a basis for Wi-Fi fingerprinting-based localization) is a labor-intensive and time-cost work, which limit their practical and sustainable use. In this study, an indoor signal mapping approach is proposed, which extracts fingerprints from unknown signal mapping routes to construct the radio map. This approach employs special indoor spatial structures (termed as structure landmarks) to estimate the location of fingerprints extracted from mapping routes. A learning-based classification model is designed to recognize the structure landmarks along a mapping route based on visual and inertial data. A landmark-based map matching algorithm is also developed to attach the recognized landmarks to a map and to recover the location of the mapping route without knowing its initial location. Experiment results showed that the accuracy of landmark recognition model is higher than 90%. The average matching accuracy and location error of signal mapping routes is 96% and 1.2 m, respectively. By using the constructed signal radio map, the indoor localization error of two algorithms can reach an accuracy of 1.6 m. Full article

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2020

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20 pages, 5599 KiB

Open AccessArticle

A Meta-Analysis of Industrial Security Research for Sustainable Organizational Growth

by Harang Yu and Hangbae Chang

Sustainability 2020, 12(22), 9526; https://doi.org/10.3390/su12229526 - 16 Nov 2020

Cited by 3 | Viewed by 2515

Abstract

As the world enters a fourth Industrial Revolution, organizations worldwide face challenges in dealing with important assets such as industrial technology. Leaking these assets can not only damage organizations economically but also negatively affect customer relationships and brand image. This has led to [...] Read more.

As the world enters a fourth Industrial Revolution, organizations worldwide face challenges in dealing with important assets such as industrial technology. Leaking these assets can not only damage organizations economically but also negatively affect customer relationships and brand image. This has led to an increased awareness of industrial security in both the business and academic spheres and a focus on identifying and implementing countermeasures against security incidents, as future computing environments will continuously face security threats. This study first examines the literature on industrial security and its current status in South Korea, which is considered an active industrial security research environment. Subsequently, meta-analyses are conducted on South Korea and abroad to compare their status and research trends in the industrial security field. The results confirm that South Korea has more actively conducted relevant studies compared to international research. This study contributes to the current literature by not only increasing the awareness of industrial security but also encouraging future studies in the field to facilitate a safe and sustainable computing environment. Full article

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18 pages, 1534 KiB

Open AccessArticle

Web Service Instant Recommendation for Sustainable Service Mashup

by Feng Zhang, Benming Chen and Cong Liu

Sustainability 2020, 12(20), 8563; https://doi.org/10.3390/su12208563 - 16 Oct 2020

Viewed by 1696

Abstract

Service Mashups can help users to integrate data of multiple sources based on Web services composition. Considering a kind of sustainable service Mashup whose data requirement cannot be predetermined, so users need to choose and compose services in a tentative manner. Meanwhile, users [...] Read more.

Service Mashups can help users to integrate data of multiple sources based on Web services composition. Considering a kind of sustainable service Mashup whose data requirement cannot be predetermined, so users need to choose and compose services in a tentative manner. Meanwhile, users can choose and compose services continually to obtain more data based on existing composition results. In such Mashups, a Web service is chosen according to the data provided by the service. Because it is difficult for users to choose from large amounts of services manually, it is a challenge to recommend services instantly for users during the construction of a sustainable service Mashup. This paper proposes an approach to recommend Web services instantly for a sustainable service Mashup. According to the services used in the service Mashup under construction, candidate services are chosen based on the Mashups that are similar to the constructing Mashup, as well as the parameter correlations of services from the perspective of actual operations of Web service composition. Experimental results indicate that the proposed approach has better precision, recall, and coverage values compared to existing state-of-the-art approaches, and therefore, it is more suitable for instant service recommendation of sustainable service Mashups. Full article

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18 pages, 2314 KiB

Open AccessArticle

Blockchain-Based Cyber Threat Intelligence System Architecture for Sustainable Computing

by Jeonghun Cha, Sushil Kumar Singh, Yi Pan and Jong Hyuk Park

Sustainability 2020, 12(16), 6401; https://doi.org/10.3390/su12166401 - 09 Aug 2020

Cited by 26 | Viewed by 5622

Abstract

Nowadays, the designing of cyber-physical systems has a significant role and plays a substantial part in developing a sustainable computing ecosystem for secure and scalable network architecture. The introduction of Cyber Threat Intelligence (CTI) has emerged as a new security system to mitigate [...] Read more.

Nowadays, the designing of cyber-physical systems has a significant role and plays a substantial part in developing a sustainable computing ecosystem for secure and scalable network architecture. The introduction of Cyber Threat Intelligence (CTI) has emerged as a new security system to mitigate existing cyber terrorism for advanced applications. CTI demands a lot of requirements at every step. In particular, data collection is a critical source of information for analysis and sharing; it is highly dependent on the reliability of the data. Although many feeds provide information on threats recently, it is essential to collect reliable data, as the data may be of unknown origin and provide information on unverified threats. Additionally, effective resource management needs to be put in place due to the large volume and diversity of the data. In this paper, we propose a blockchain-based cyber threat intelligence system architecture for sustainable computing in order to address issues such as reliability, privacy, scalability, and sustainability. The proposed system model can cooperate with multiple feeds that collect CTI data, create a reliable dataset, reduce network load, and measure organizations’ contributions to motivate participation. To assess the proposed model’s effectiveness, we perform the experimental analysis, taking into account various measures, including reliability, privacy, scalability, and sustainability. Experimental results of evaluation using the IP of 10 open source intelligence (OSINT) CTI feeds show that the proposed model saves about 15% of storage space compared to total network resources in a limited test environment. Full article

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14 pages, 1017 KiB

Open AccessArticle

Research on Behavior-Based Data Leakage Incidents for the Sustainable Growth of an Organization

by Jawon Kim, Jaesoo Kim and Hangbae Chang

Sustainability 2020, 12(15), 6217; https://doi.org/10.3390/su12156217 - 02 Aug 2020

Cited by 5 | Viewed by 3053

Abstract

With the continuously increasing number of data leakage security incidents caused by organization insiders, current security activities cannot predict a data leakage. Because such security incidents are extremely harmful and difficult to detect, predicting security incidents would be the most effective preventative method. [...] Read more.

With the continuously increasing number of data leakage security incidents caused by organization insiders, current security activities cannot predict a data leakage. Because such security incidents are extremely harmful and difficult to detect, predicting security incidents would be the most effective preventative method. However, current insider security controls and systems detect and identify unusual behaviors to prevent security incidents but produce many false-positives. To solve these problems, the present study collects and analyzes data leaks by insiders in advance, analyzes information leaks that can predict security incidents, and evaluates risk based on behavior. To this end, data leakage behaviors by insiders are analyzed through an analysis of previous studies and the implementation of an in-depth interview method. Statistical verification of the analyzed data leakage behavior is performed to determine the validity and derive the levels of leakage risk for each behavior. In addition, by applying the N-gram analysis method to derive a data leakage scenario, the levels of risk are clarified to reduce false-positives and over detection (i.e., the limitations of existing data leakage prevention systems) and make preemptive security activities possible. Full article

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32 pages, 12010 KiB

Open AccessArticle

Hierarchical System Decomposition Using Genetic Algorithm for Future Sustainable Computing

by Jun-Ho Huh, Jimin Hwa and Yeong-Seok Seo

Sustainability 2020, 12(6), 2177; https://doi.org/10.3390/su12062177 - 11 Mar 2020

Cited by 2 | Viewed by 3041

Abstract

A Hierarchical Subsystem Decomposition (HSD) is of great help in understanding large-scale software systems from the software architecture level. However, due to the lack of software architecture management, HSD documentations are often outdated, or they disappear in the course of repeated changes of [...] Read more.

A Hierarchical Subsystem Decomposition (HSD) is of great help in understanding large-scale software systems from the software architecture level. However, due to the lack of software architecture management, HSD documentations are often outdated, or they disappear in the course of repeated changes of a software system. Thus, in this paper, we propose a new approach for recovering HSD according to the intended design criteria based on a genetic algorithm to find an optimal solution. Experiments are performed to evaluate the proposed approach using two open source software systems with the 14 fitness functions of the genetic algorithm (GA). The HSDs recovered by our approach have different structural characteristics according to objectives. In the analysis on our GA operators, crossover contributes to a relatively large improvement in the early phase of a search. Mutation renders small-scale improvement in the whole search. Our GA is compared with a Hill-Climbing algorithm (HC) implemented by our GA operators. Although it is still in the primitive stage, our GA leads to higher-quality HSDs than HC. The experimental results indicate that the proposed approach delivers better performance than the existing approach. Full article

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2019

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14 pages, 1909 KiB

Open AccessArticle

Vulnerability Evaluation Method through Correlation Analysis of Android Applications

by Cheolmin Yeom and Yoojae Won

Sustainability 2019, 11(23), 6637; https://doi.org/10.3390/su11236637 - 24 Nov 2019

Cited by 1 | Viewed by 2513

Abstract

Due to people in companies use mobile devices to access corporate data, attackers targeting corporate data use vulnerabilities in mobile devices. Most vulnerabilities in applications are caused by the carelessness of developers, and confused deputy attacks and data leak attacks using inter-application vulnerabilities [...] Read more.

Due to people in companies use mobile devices to access corporate data, attackers targeting corporate data use vulnerabilities in mobile devices. Most vulnerabilities in applications are caused by the carelessness of developers, and confused deputy attacks and data leak attacks using inter-application vulnerabilities are possible. These vulnerabilities are difficult to find through the single-application diagnostic tool that is currently being studied. This paper proposes a process to automate the decompilation of all the applications on a user’s mobile device and a mechanism to find inter-application vulnerabilities. The mechanism generates a list and matrix, detailing the vulnerabilities in the mobile device. The proposed mechanism is validated through an experiment on an actual mobile device with four installed applications, and the results show that the mechanism can accurately capture all application risks as well as inter-application risks. Through this mechanism, users can expect to find the risks in their mobile devices in advance and prevent damage. Full article

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16 pages, 2212 KiB

Open AccessArticle

A Novel Head Mounted Display Based Methodology for Balance Evaluation and Rehabilitation

by Eun-Young Lee, Van Thanh Tran and Dongho Kim

Sustainability 2019, 11(22), 6453; https://doi.org/10.3390/su11226453 - 16 Nov 2019

Cited by 7 | Viewed by 3227

Abstract

In this paper, we present a new augmented reality (AR) head mounted display (HMD)-based balance rehabilitation method. This method assesses the individual’s postural stability quantitatively by measuring head movement via the inertial measurement unit sensor integrated in the AR HMD. In addition, it [...] Read more.

In this paper, we present a new augmented reality (AR) head mounted display (HMD)-based balance rehabilitation method. This method assesses the individual’s postural stability quantitatively by measuring head movement via the inertial measurement unit sensor integrated in the AR HMD. In addition, it provides visual feedback to train through holographic objects, which interacts with the head position in real-time. We implemented applications for Microsoft HoloLens and conducted experiments with eight participants to verify the method we proposed. Participants performed each of three postural tasks three times depending on the presence or absence of augmented reality, the center of pressure (COP) displacement was measured through the Wii Balance Board, and the head displacement was measured through the HoloLens. There are significant correlations (p < 0.05) between COP and head displacement and significant differences (p < 0.05) between with/without AR feedback, although most of them were not statistically significant likely due to the small sample. Despite the results, we confirmed the applicability and potential of the AR HMD-based balance rehabilitation method we proposed. We expect the proposed method could be used as a convenient and effective rehabilitation tool for both patients and therapists in the future. Full article

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17 pages, 2643 KiB

Open AccessArticle

Priolog: Mining Important Logs via Temporal Analysis and Prioritization

by Byungchul Tak, Seorin Park and Prabhakar Kudva

Sustainability 2019, 11(22), 6306; https://doi.org/10.3390/su11226306 - 09 Nov 2019

Cited by 4 | Viewed by 2297

Abstract

Log analytics are a critical part of the operational management in today’s IT services. However, the growing software complexity and volume of logs make it increasingly challenging to mine useful insights from logs for problem diagnosis. In this paper, we propose a novel [...] Read more.

Log analytics are a critical part of the operational management in today’s IT services. However, the growing software complexity and volume of logs make it increasingly challenging to mine useful insights from logs for problem diagnosis. In this paper, we propose a novel technique, Priolog, that can narrow down the volume of logs into a small set of important and most relevant logs. Priolog uses a combination of log template temporal analysis, log template frequency analysis, and word frequency analysis, which complement each other to generate an accurately ranked list of important logs. We have implemented this technique and applied to the problem diagnosis task of the popular OpenStack platform. Our evaluation indicates that Priolog can effectively find the important logs that hold direct hints to the failure cause in several scenarios. We demonstrate the concepts, design, and evaluation results using actual logs. Full article

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15 pages, 6407 KiB

Open AccessArticle

An Improved Style Transfer Algorithm Using Feedforward Neural Network for Real-Time Image Conversion

by Chang Zhou, Zhenghong Gu, Yu Gao and Jin Wang

Sustainability 2019, 11(20), 5673; https://doi.org/10.3390/su11205673 - 14 Oct 2019

Cited by 8 | Viewed by 3751

Abstract

Creation of art is a complex process for its abstraction and novelty. In order to create those art with less cost, style transfer using advanced machine learning technology becomes a popular method in computer vision field. However, traditional transferred image still troubles with [...] Read more.

Creation of art is a complex process for its abstraction and novelty. In order to create those art with less cost, style transfer using advanced machine learning technology becomes a popular method in computer vision field. However, traditional transferred image still troubles with color anamorphosis, content losing, and time-consuming problems. In this paper, we propose an improved style transfer algorithm using the feedforward neural network. The whole network is composed of two parts, a style transfer network and a loss network. The style transfer network owns the ability of directly mapping the content image into the stylized image after training. Content loss, style loss, and Total Variation (TV) loss are calculated by the loss network to update the weight of the style transfer network. Additionally, a cross training strategy is proposed to better preserve the details of the content image. Plenty of experiments are conducted to show the superior performance of our presented algorithm compared to the classic neural style transfer algorithm. Full article

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15 pages, 2197 KiB

Open AccessArticle

BlockDeepNet: A Blockchain-Based Secure Deep Learning for IoT Network

by Shailendra Rathore, Yi Pan and Jong Hyuk Park

Sustainability 2019, 11(14), 3974; https://doi.org/10.3390/su11143974 - 22 Jul 2019

Cited by 70 | Viewed by 5823

Abstract

The recent development in IoT and 5G translates into a significant growth of Big data in 5G—envisioned industrial automation. To support big data analysis, Deep Learning (DL) has been considered the most promising approach in recent years. Note, however, that designing an effective [...] Read more.

The recent development in IoT and 5G translates into a significant growth of Big data in 5G—envisioned industrial automation. To support big data analysis, Deep Learning (DL) has been considered the most promising approach in recent years. Note, however, that designing an effective DL paradigm for IoT has certain challenges such as single point of failure, privacy leak of IoT devices, lack of valuable data for DL, and data poisoning attacks. To this end, we present BlockDeepNet, a Blockchain-based secure DL that combines DL and blockchain to support secure collaborative DL in IoT. In BlockDeepNet, collaborative DL is performed at the device level to overcome privacy leak and obtain enough data for DL, whereas blockchain is employed to ensure the confidentiality and integrity of collaborative DL in IoT. The experimental evaluation shows that BlockDeepNet can achieve higher accuracy for DL with acceptable latency and computational overhead of blockchain operation. Full article

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16 pages, 4401 KiB

Open AccessArticle

Early Fire Detection on Video Using LBP and Spread Ascending of Smoke

by Jesus Olivares-Mercado, Karina Toscano-Medina, Gabriel Sánchez-Perez, Aldo Hernandez-Suarez, Hector Perez-Meana, Ana Lucila Sandoval Orozco and Luis Javier García Villalba

Sustainability 2019, 11(12), 3261; https://doi.org/10.3390/su11123261 - 13 Jun 2019

Cited by 8 | Viewed by 3475

Abstract

This paper proposes a methodology for early fire detection based on visual smoke characteristics such as movement, color, gray tones and dynamic texture, i.e., diverse but representative and discriminant characteristics, as well as its ascending expansion, which is sequentially processed to find the [...] Read more.

This paper proposes a methodology for early fire detection based on visual smoke characteristics such as movement, color, gray tones and dynamic texture, i.e., diverse but representative and discriminant characteristics, as well as its ascending expansion, which is sequentially processed to find the candidate smoke regions. Thus, once a region with movement is detected, the pixels inside it that are smoke color are estimated to obtain a more detailed description of the smoke candidate region. Next, to increase the system efficiency and reduce false alarms, each region is characterized using the local binary pattern, which analyzes its texture and classifies it by means of a multi-layer perceptron. Finally, the ascending expansion of the candidate region is analyzed and those smoke regions that maintain or increase their ascending growth over a time span are considered as a smoke regions, and an alarm is triggered. Evaluations were performed using two different classifiers, namely multi-Layer perceptron and the support vector machine, with a standard database smoke video. Evaluation results show that the proposed system provides fire detection accuracy of between 97.85% and 99.83%. Full article

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6 pages, 192 KiB

Open AccessEditorial

Advanced IT-Based Future Sustainable Computing (2017–2018)

by Jong Hyuk Park

Sustainability 2019, 11(8), 2264; https://doi.org/10.3390/su11082264 - 15 Apr 2019

Cited by 3 | Viewed by 2462

Abstract

Future Sustainability Computing (FSC) is an emerging concept that holds various types of paradigms, rules, procedures, and policies to support breadth and length of the deployment of Information Technology (IT) for abundant life. However, advanced IT-based FCS is facing several sustainability problems in [...] Read more.

Future Sustainability Computing (FSC) is an emerging concept that holds various types of paradigms, rules, procedures, and policies to support breadth and length of the deployment of Information Technology (IT) for abundant life. However, advanced IT-based FCS is facing several sustainability problems in different information processing and computing environments. Solutions to these problems can call upon various computational and algorithmic frameworks that employ optimization, integration, generation, and utilization technique within cloud, mobile, and cluster computing, such as meta-heuristics, decision support systems, prediction and control, dynamical systems, machine learning, and so on. Therefore, this special issue deals with various software and hardware design, novel architectures and frameworks, specific mathematical models, and efficient modeling-simulation for advance IT-based FCS. We accepted eighteen articles in the six different IT dimensions: machine learning, blockchain, optimized resource provision, communication network, IT governance, and information security. All accepted articles contribute to the applications and research in the FCS, such as software and information processing, cloud storage organization, smart devices, efficient algorithmic information processing and distribution. Full article

18 pages, 3049 KiB

Open AccessArticle

Hardware-Based Adaptive Terrain Mesh Using Temporal Coherence for Real-Time Landscape Visualization

by Eun-Seok Lee and Byeong-Seok Shin

Sustainability 2019, 11(7), 2137; https://doi.org/10.3390/su11072137 - 10 Apr 2019

Cited by 2 | Viewed by 2931

Abstract

In general, changes in society or the environment are expected depending on changes in terrain. The faster and more accurately these terrain changes can be observed, the faster and more accurately predictions can be made. Recently, three-dimensional (3D) terrain visualization programs, such as [...] Read more.

In general, changes in society or the environment are expected depending on changes in terrain. The faster and more accurately these terrain changes can be observed, the faster and more accurately predictions can be made. Recently, three-dimensional (3D) terrain visualization programs, such as flight simulation, allow for interaction with various datasets to predict ecosystem influences in real time. Elaborate terrain data require a very large capacity. To render these large terrain data, the computing power of graphics devices cannot always satisfy the real-time conditions. Consequently, a large number of graphics devices in computing systems need to be replaced on a periodic basis. As the industry evolves, the replacement cycle of graphic devices shortens. To solve this problem, we present a novel acceleration approach for generating an adaptive terrain mesh using temporal coherence. By using our method, it is possible to prevent artifacts such as frame drop or screen flickering due to lack of computing power of the GPU in a specific viewing condition. Instead of generating the new terrain mesh on every frame, our method reuses the detail level of terrain mesh that was used in a previous frame. Therefore, it can maintain the frame coherency and improve the rendering speed. This allows the proposed method to more quickly provide more detailed information about the terrain to predict environmental changes more accurately on existing equipment. Thus, the proposed method can reduce the need to frequently replace GPUs. The proposed method can guarantee sufficient performance even with a resilient graphic device and can effectively slow down the replacement period of existing equipment. Full article

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3 pages, 191 KiB

Open AccessCorrection

Correction: An Efficient Grid-Based K-Prototypes Algorithm for Sustainable Decision Making Using Spatial Objects. Sustainability 2018, 10, 2614

by Hong-Jun Jang, Byoungwook Kim, Jongwan Kim and Soon-Young Jung

Sustainability 2019, 11(6), 1801; https://doi.org/10.3390/su11061801 - 25 Mar 2019

Cited by 1 | Viewed by 1949

Abstract

The authors would like to make the following corrections to this paper [...] Full article

2018

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25 pages, 979 KiB

Open AccessArticle

Environmental Sustainability in Information Technologies Governance

by Wilmer Rivas-Asanza, Jennifer Celleri-Pacheco, Javier Andrade-Garda, Rafael García-Vázquez, Virginia Mato-Abad, Santiago Rodríguez-Yáñez and Sonia Suárez-Garaboa

Sustainability 2018, 10(12), 4792; https://doi.org/10.3390/su10124792 - 15 Dec 2018

Cited by 4 | Viewed by 3560

Abstract

In the present day, many risk factors affect the continuity of a business. However, this situation produces a conducive atmosphere to approach alternatives that relieve this situation for organizations. Within these alternatives, environmental sustainability (ES) and information technologies governance (IT governance or ITG) [...] Read more.

In the present day, many risk factors affect the continuity of a business. However, this situation produces a conducive atmosphere to approach alternatives that relieve this situation for organizations. Within these alternatives, environmental sustainability (ES) and information technologies governance (IT governance or ITG) stand out. Both alternatives allow organizations to address intrinsically common issues such as strategic alignment, generation of value, mechanisms for performance improvement, risk management and resource management. This article focuses on the fusion of both alternatives, determining to what extent current ITG models consider ES issues. With this purpose, the strategy followed was firstly to identify the relevant factors of ES present in the main approaches of the domain (ISO14001, GRI G4, EMAS, SGE21 and ISO26000). As a result, we identified 27 activities and 103 sub-activities of ES. Next, as the second main objective, we determined which of those factors are present in the main current ITG approaches (COBIT5, ISO38500 and WEILL & ROSS). Finally, we concluded through a quantitative study that COBIT5 is the most sustainable (i.e., the one that incorporates more ES issues) ITG approach. Full article

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17 pages, 3655 KiB

Open AccessArticle

Consistent Registration and Discovery Scheme for Devices and Web Service Providers Based on RAML Using Embedded RD in OCF IoT Network

by Wenquan Jin and Dohyeun Kim

Sustainability 2018, 10(12), 4706; https://doi.org/10.3390/su10124706 - 10 Dec 2018

Cited by 12 | Viewed by 3720

Abstract

The Internet of Things (IoT) is comprised of connected devices which are equipped with sensors, actuators, and applications to provide services for enabling those objects to connect and exchange data. For these connected devices and the IoT network environment, heterogeneous protocols and frameworks [...] Read more.

The Internet of Things (IoT) is comprised of connected devices which are equipped with sensors, actuators, and applications to provide services for enabling those objects to connect and exchange data. For these connected devices and the IoT network environment, heterogeneous protocols and frameworks have been published and applied to provide novel IoT services in our daily life. On the Internet, most of the services are provided by existing web service providers which are based on the high-performance processor, storage, and stable power supply. However, devices of the IoT are developed for constrained environments using the small size of equipment to provide seamless services ubiquitously. For accessing the constrained devices and existing web service providers using the clients in the IoT networks such as smart homes, the services of servers from the devices and web service providers shall be discovered by the clients using a consistent discovery service. In this paper, a consistent registration and discovery scheme is proposed for the devices and web service providers in the Open Connectivity Foundation (OCF)-based IoT network. For supporting the proposed scheme, an embedded resource directory (RD) server is proposed to provide a consistent registration service that is used for publishing information of devices and web service providers. For the registration, a unified profile format is used that is based on the RESTful API Modeling Language to describes the information of devices and web service providers. Furthermore, the discovery service provides the consistent interface to discover the registered devices and web service providers by the client using the unified user interface. Accordingly, the client can access the resources of devices and web service providers based on the discovered information. Full article

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14 pages, 4630 KiB

Open AccessArticle

Blockchain-Based One-Off Address System to Guarantee Transparency and Privacy for a Sustainable Donation Environment

by Jaekyu Lee, Aria Seo, Yeichang Kim and Junho Jeong

Sustainability 2018, 10(12), 4422; https://doi.org/10.3390/su10124422 - 26 Nov 2018

Cited by 16 | Viewed by 4705

Abstract

The problem of transparency in donation systems has long been a topic for discussion. However, the emphasis on transparency raises privacy concerns for donors and recipients, with some people attempting to hide donations or the receipt of money. Therefore, a donation system that [...] Read more.

The problem of transparency in donation systems has long been a topic for discussion. However, the emphasis on transparency raises privacy concerns for donors and recipients, with some people attempting to hide donations or the receipt of money. Therefore, a donation system that guarantees transparency and privacy is required to avoid negative side effects. In this study, we developed a system that protects personal information by using a one-time account address system based on a blockchain while emphasizing transparency. The developed system could contribute to the creation of a sustainable and safe donation environment and culture. Full article

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15 pages, 5781 KiB

Open AccessArticle

A Study on the Transparent Price Tracing System in Supply Chain Management Based on Blockchain

by Minjae Yoo and Yoojae Won

Sustainability 2018, 10(11), 4037; https://doi.org/10.3390/su10114037 - 04 Nov 2018

Cited by 49 | Viewed by 7711

Abstract

Over the past few years, the importance of improving the product distribution structure has increased worldwide. Therefore, distribution prices are now disclosed and product information is shared with consumers. However, distribution channels are complex and supply chain management (SCM) is autonomously executed in [...] Read more.

Over the past few years, the importance of improving the product distribution structure has increased worldwide. Therefore, distribution prices are now disclosed and product information is shared with consumers. However, distribution channels are complex and supply chain management (SCM) is autonomously executed in each company. For this reason, it has been frequently pointed out that the distribution process is not transparent and the distribution margin is high. In this paper, we propose a system that guarantees the transparency of the product distribution structure by applying blockchain and smart contracts to the price-tracking portion of supply chain management systems. This approach allows companies to track their trades by enhancing transparency in the SCM, thereby discouraging companies from pursuing excessive profits. In addition, companies can cut management costs by automatically storing distribution details in a blockchain network and managing information more securely. Full article

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15 pages, 4165 KiB

Open AccessArticle

An Adaptive Offloading Method for an IoT-Cloud Converged Virtual Machine System Using a Hybrid Deep Neural Network

by Yunsik Son, Junho Jeong and YangSun Lee

Sustainability 2018, 10(11), 3955; https://doi.org/10.3390/su10113955 - 30 Oct 2018

Cited by 11 | Viewed by 3469

Abstract

A virtual machine with a conventional offloading scheme transmits and receives all context information to maintain program consistency during communication between local environments and the cloud server environment. Most overhead costs incurred during offloading are proportional to the size of the context information [...] Read more.

A virtual machine with a conventional offloading scheme transmits and receives all context information to maintain program consistency during communication between local environments and the cloud server environment. Most overhead costs incurred during offloading are proportional to the size of the context information transmitted over the network. Therefore, the existing context information synchronization structure transmits context information that is not required for job execution when offloading, which increases the overhead costs of transmitting context information in low-performance Internet-of-Things (IoT) devices. In addition, the optimal offloading point should be determined by checking the server’s CPU usage and network quality. In this study, we propose a context management method and estimation method for CPU load using a hybrid deep neural network on a cloud-based offloading service that extracts contexts that require synchronization through static profiling and estimation. The proposed adaptive offloading method reduces network communication overheads and determines the optimal offloading time for low-computing-powered IoT devices and variable server performance. Using experiments, we verify that the proposed learning-based prediction method effectively estimates the CPU load model for IoT devices and can adaptively apply offloading according to the load of the server. Full article

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20 pages, 4165 KiB

Open AccessArticle

An Efficient Grid-Based K-Prototypes Algorithm for Sustainable Decision-Making on Spatial Objects

by Hong-Jun Jang, Byoungwook Kim, Jongwan Kim and Soon-Young Jung

Sustainability 2018, 10(8), 2614; https://doi.org/10.3390/su10082614 - 25 Jul 2018

Cited by 8 | Viewed by 4313 | Correction

Abstract

Data mining plays a critical role in sustainable decision-making. Although the k-prototypes algorithm is one of the best-known algorithms for clustering both numeric and categorical data, clustering a large number of spatial objects with mixed numeric and categorical attributes is still inefficient due [...] Read more.

Data mining plays a critical role in sustainable decision-making. Although the k-prototypes algorithm is one of the best-known algorithms for clustering both numeric and categorical data, clustering a large number of spatial objects with mixed numeric and categorical attributes is still inefficient due to complexity. In this paper, we propose an efficient grid-based k-prototypes algorithm, GK-prototypes, which achieves high performance for clustering spatial objects. The first proposed algorithm utilizes both maximum and minimum distance between cluster centers and a cell, which can reduce unnecessary distance calculation. The second proposed algorithm as an extension of the first proposed algorithm, utilizes spatial dependence; spatial data tends to be similar to objects that are close. Each cell has a bitmap index which stores the categorical values of all objects within the same cell for each attribute. This bitmap index can improve performance if the categorical data is skewed. Experimental results show that the proposed algorithms can achieve better performance than the existing pruning techniques of the k-prototypes algorithm. Full article

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20 pages, 25336 KiB

Open AccessArticle

Server Operation and Virtualization to Save Energy and Cost in Future Sustainable Computing

by Jun-Ho Huh

Sustainability 2018, 10(6), 1919; https://doi.org/10.3390/su10061919 - 08 Jun 2018

Cited by 12 | Viewed by 4999

Abstract

Since the introduction of the LTE (Long Term Evolution) service, we have lived in a time of expanding amounts of data. The amount of data produced has increased every year with the increase of smart phone distribution in particular. Telecommunication service providers have [...] Read more.

Since the introduction of the LTE (Long Term Evolution) service, we have lived in a time of expanding amounts of data. The amount of data produced has increased every year with the increase of smart phone distribution in particular. Telecommunication service providers have to struggle to secure sufficient network capacity in order to maintain quick access to necessary data by consumers. Nonetheless, maintaining the maximum capacity and bandwidth at all times requires considerable cost and excessive equipment. Therefore, to solve such a problem, telecommunication service providers need to maintain an appropriate level of network capacity and to provide sustainable service to customers through a quick network development in case of shortage. So far, telecommunication service providers have bought and used the network equipment directly produced by network equipment manufacturers such as Ericsson, Nokia, Cisco, and Samsung. Since the equipment is specialized for networking, which satisfied consumers with their excellent performances, they are very costly because they are developed with advanced technologies. Moreover, it takes much time due to the purchase process wherein the telecommunication service providers place an order and the manufacturer produces and delivers. Accordingly, there are cases that require signaling and two-way data traffic as well as capacity because of the diversity of IoT devices. For these purposes, the need for NFV (Network Function Virtualization) is raised. Equipment virtualization is performed so that it is operated on an x86-based compatible server instead of working on the network equipment manufacturer’s dedicated hardware. By operating in some compatible servers, it can reduce the wastage of hardware and cope with the change thanks to quick hardware development. This study proposed an efficient system of reducing cost in network server operation using such NFV technology and found that the cost was reduced by 24% compared to existing network equipment. The technique proposed in this study is expected to be a foundation technology for future sustainability computing. Full article

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21 pages, 2567 KiB

Open AccessArticle

Context-Aware Multimodal FIDO Authenticator for Sustainable IT Services

by Seung-Hyun Kim, Daeseon Choi, Soo-Hyung Kim, Sangrae Cho and Kyung-Soo Lim

Sustainability 2018, 10(5), 1656; https://doi.org/10.3390/su10051656 - 21 May 2018

Cited by 4 | Viewed by 4211

Abstract

Existing sustainable IT services have several problems related to user authentication such as the inefficiency of managing the system security, low security, and low usability. In this paper, we propose a Fast IDentity Online (FIDO) authenticator that performs continuous authentication with implicit authentication [...] Read more.

Existing sustainable IT services have several problems related to user authentication such as the inefficiency of managing the system security, low security, and low usability. In this paper, we propose a Fast IDentity Online (FIDO) authenticator that performs continuous authentication with implicit authentication based on user context and multimodal authentication. The proposed FIDO authenticator, a context-aware multimodal FIDO authentication (CAMFA) method, combines information such as the user context, state of the mobile device, and user biometrics, then applies implicit and explicit authentication methods to meet the level of authentication required by the service provider. This reduces the user’s explicit authentication burden and continually authenticates users at risk during the session. Moreover, it is able to respond to attacks such as the theft of the authentication method or session hijacking. To study the effectiveness of CAMFA, we ran a user study by collecting data from 22 participants over 42 days of activity on a practical Android platform. The result of the user study demonstrates that the number of explicit authentication requests could be reduced by half. Based on the results of this study, an advanced user authentication that provides multimodal and continuous authentication could be applied to sustainable IT services. Full article

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12 pages, 894 KiB

Open AccessArticle

An Automated Vulnerability Detection and Remediation Method for Software Security

by Jeesoo Jurn, Taeeun Kim and Hwankuk Kim

Sustainability 2018, 10(5), 1652; https://doi.org/10.3390/su10051652 - 21 May 2018

Cited by 13 | Viewed by 5419

Abstract

As hacking techniques become more sophisticated, vulnerabilities have been gradually increasing. Between 2010 and 2015, around 80,000 vulnerabilities were newly registered in the CVE (Common Vulnerability Enumeration), and the number of vulnerabilities has continued to rise. While the number of vulnerabilities is increasing [...] Read more.

As hacking techniques become more sophisticated, vulnerabilities have been gradually increasing. Between 2010 and 2015, around 80,000 vulnerabilities were newly registered in the CVE (Common Vulnerability Enumeration), and the number of vulnerabilities has continued to rise. While the number of vulnerabilities is increasing rapidly, the response to them relies on manual analysis, resulting in a slow response speed. It is necessary to develop techniques that can detect and patch vulnerabilities automatically. This paper introduces a trend of techniques and tools related to automated vulnerability detection and remediation. We propose an automated vulnerability detection method based on binary complexity analysis to prevent a zero-day attack. We also introduce an automatic patch generation method through PLT/GOT table modification to respond to zero-day vulnerabilities. Full article

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22 pages, 773 KiB

Open AccessArticle

Signal Outages of CSMA/CA-Based Wireless Networks with Different AP Densities

by Soohyun Cho

Sustainability 2018, 10(5), 1483; https://doi.org/10.3390/su10051483 - 08 May 2018

Cited by 1 | Viewed by 2780

Abstract

In wireless networks, users may experience outages owing to low received signal strength. Divergent from other research, we investigate the outages for users of CSMA/CA-based wireless networks when multiple access points (APs) and multiple users are randomly positioned in a given area. We [...] Read more.

In wireless networks, users may experience outages owing to low received signal strength. Divergent from other research, we investigate the outages for users of CSMA/CA-based wireless networks when multiple access points (APs) and multiple users are randomly positioned in a given area. We model the locations of the APs and users using independent homogeneous Poisson point processes (PPPs), and analyze the signal outage probabilities of users when there are different numbers of access points, as well as when different modulation and coding schemes (MCSs) are used for communication. We also investigate heterogeneous CSMA/CA-based wireless networks, wherein the APs use different transmit powers. Then, we evaluate the results and compare the signal outage rates of users with the signal-to-interference-plus-noise ratio (SINR) outage rates of users in both homogeneous and heterogeneous IEEE 802.11a wireless networks using extensive event-driven simulations. The simulation results validate our analysis on the signal outages of users in multi-cell, multi-user wireless networking environments, and show that a significant portion of outages are caused by the signal outages when AP densities are low and high MCS levels are used for communication. Full article

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13 pages, 5755 KiB

Open AccessArticle

Advanced Camera Image Cropping Approach for CNN-Based End-to-End Controls on Sustainable Computing

by Yunsick Sung, Yong Jin, Jeonghoon Kwak, Sang-Geol Lee and Kyungeun Cho

Sustainability 2018, 10(3), 816; https://doi.org/10.3390/su10030816 - 15 Mar 2018

Cited by 12 | Viewed by 4470

Abstract

Recent research on deep learning has been applied to a diversity of fields. In particular, numerous studies have been conducted on self-driving vehicles using end-to-end approaches based on images captured by a single camera. End-to-end controls learn the output vectors of output devices [...] Read more.

Recent research on deep learning has been applied to a diversity of fields. In particular, numerous studies have been conducted on self-driving vehicles using end-to-end approaches based on images captured by a single camera. End-to-end controls learn the output vectors of output devices directly from the input vectors of available input devices. In other words, an end-to-end approach learns not by analyzing the meaning of input vectors, but by extracting optimal output vectors based on input vectors. Generally, when end-to-end control is applied to self-driving vehicles, the steering wheel and pedals are controlled autonomously by learning from the images captured by a camera. However, high-resolution images captured from a car cannot be directly used as inputs to Convolutional Neural Networks (CNNs) owing to memory limitations; the image size needs to be efficiently reduced. Therefore, it is necessary to extract features from captured images automatically and to generate input images by merging the parts of the images that contain the extracted features. This paper proposes a learning method for end-to-end control that generates input images for CNNs by extracting road parts from input images, identifying the edges of the extracted road parts, and merging the parts of the images that contain the detected edges. In addition, a CNN model for end-to-end control is introduced. Experiments involving the Open Racing Car Simulator (TORCS), a sustainable computing environment for cars, confirmed the effectiveness of the proposed method for self-driving by comparing the accumulated difference in the angle of the steering wheel in the images generated by it with those of resized images containing the entire captured area and cropped images containing only a part of the captured area. The results showed that the proposed method reduced the accumulated difference by 0.839% and 0.850% compared to those yielded by the resized images and cropped images, respectively. Full article

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2017

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6768 KiB

Open AccessArticle

Cloud-Centric and Logically Isolated Virtual Network Environment Based on Software-Defined Wide Area Network

by Dongkyun Kim, Yong-Hwan Kim, Ki-Hyun Kim and Joon-Min Gil

Sustainability 2017, 9(12), 2382; https://doi.org/10.3390/su9122382 - 20 Dec 2017

Cited by 11 | Viewed by 4698

Abstract

Recent development of distributed cloud environments requires advanced network infrastructure in order to facilitate network automation, virtualization, high performance data transfer, and secured access of end-to-end resources across regional boundaries. In order to meet these innovative cloud networking requirements, software-defined wide area network [...] Read more.

Recent development of distributed cloud environments requires advanced network infrastructure in order to facilitate network automation, virtualization, high performance data transfer, and secured access of end-to-end resources across regional boundaries. In order to meet these innovative cloud networking requirements, software-defined wide area network (SD-WAN) is primarily demanded to converge distributed cloud resources (e.g., virtual machines (VMs)) in a programmable and intelligent manner over distant networks. Therefore, this paper proposes a logically isolated networking scheme designed to integrate distributed cloud resources to dynamic and on-demand virtual networking over SD-WAN. The performance evaluation and experimental results of the proposed scheme indicate that virtual network convergence time is minimized in two different network models such as: (1) an operating OpenFlow-oriented SD-WAN infrastructure (KREONET-S) which is deployed on the advanced national research network in Korea, and (2) Mininet-based experimental and emulated networks. Full article

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1655 KiB

Open AccessArticle

A Governance and Management Framework for Green IT

by J. David Patón-Romero, Maria Teresa Baldassarre, Mario Piattini and Ignacio García Rodríguez de Guzmán

Sustainability 2017, 9(10), 1761; https://doi.org/10.3390/su9101761 - 29 Sep 2017

Cited by 27 | Viewed by 9143

Abstract

In recent years, Green Information Technology (IT) has grown enormously, and has become an increasingly important and essential area, providing multiple benefits to the organizations that focus on it. It is for this reason that there is an increasing number of organizations embracing [...] Read more.

In recent years, Green Information Technology (IT) has grown enormously, and has become an increasingly important and essential area, providing multiple benefits to the organizations that focus on it. It is for this reason that there is an increasing number of organizations embracing the idea of Green IT. However, Green IT is a very young field and each organization implements it according to its own criteria. That is why it is extremely important to develop the bases or best practices of governance and management that allow organizations to implement Green IT practices correctly and standardize them. In this article, we propose the “Governance and Management Framework for Green IT”, establishing the characteristics needed to carry out the governance and management of Green IT in an organization, and perform audits in this area. This framework is based on COBIT 5, which is a general framework for the control and audit of different areas related to IT. The results obtained through different validations demonstrate the validity and usefulness of the framework developed in the field of Green IT, providing a complete guide to the organizations in their efforts to implement, control and/or improve the practices of Green IT in their processes and day-to-day operations. Full article

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4047 KiB

Open AccessArticle

A Study on a JWT-Based User Authentication and API Assessment Scheme Using IMEI in a Smart Home Environment

by Namsu Hong, Mansik Kim, Moon-Seog Jun and Jungho Kang

Sustainability 2017, 9(7), 1099; https://doi.org/10.3390/su9071099 - 23 Jun 2017

Cited by 7 | Viewed by 7960

Abstract

The development of information and communication technology (ICT) has opened the era of the Internet of Things (IoT), in which many devices can connect to the Internet to communicate. Recently, various technologies, such as smart grids, connected cars, and smart farms, have emerged [...] Read more.

The development of information and communication technology (ICT) has opened the era of the Internet of Things (IoT), in which many devices can connect to the Internet to communicate. Recently, various technologies, such as smart grids, connected cars, and smart farms, have emerged based on IoT, and there is also the smart home, which is the fastest growing market. The smart home is where devices installed for various purposes connect to each other through the Internet so that users can use the service anytime and anywhere. However, while the smart home provides convenience to users, recently the smart home has been exposed to various security threats, such as vulnerability of session/cookies and the use of vulnerable OAuth. In addition, attacks on smart homes by hackers using these vulnerabilities are also increasing. Therefore, in this paper, we propose a user authentication method using the JSON Web Token (JWT) and International Mobile Equipment Identity (IMEI) in the smart home, and solved the problem of unauthorized smart home device registration of hackers by the application of IMEI and JWT technology. Full article

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6554 KiB

Open AccessArticle

Design and Analysis of Multiple OS Implementation on a Single ARM-Based Embedded Platform

by Byoungwook Kim and Min Choi

Sustainability 2017, 9(5), 684; https://doi.org/10.3390/su9050684 - 25 Apr 2017

Cited by 1 | Viewed by 5081

Abstract

Recently, with the development of embedded system hardware technology, there is a need to support various kinds of operating system (OS) operation in embedded systems. In mobile processors, ARM started to provide the virtualization extension support technology which was intended for processors in [...] Read more.

Recently, with the development of embedded system hardware technology, there is a need to support various kinds of operating system (OS) operation in embedded systems. In mobile processors, ARM started to provide the virtualization extension support technology which was intended for processors in PC processors. Virtualization technology has the advantage of using hardware resources effectively. If the real-time operating system (RTOS) is operated on a hypervisor, there is a problem that RTOS performance is degraded due to overhead. Thus, we need to compare the performance between a single execution of the RTOS and simultaneous execution of multiple OS (RTOS + Linux). Therefore, in this paper, we measure the performance when the RTOS operates independently on the NVidia Jetson TK-1 embedded board supporting virtualization technology. Then, we measure the performance when the RTOS and Linux are operating simultaneously on top of a hypervisor. For this purpose, we implemented and ported such a RTOS, especially FreeRTOS and uC/OS, onto two embedded boards, such as the Arndale board (SAMSUNG, Seoul, South Korea) and the NVidia TK1 board (NVIDIA, Santa Clara, CA, USA). Full article

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2438 KiB

Open AccessArticle

EH-GC: An Efficient and Secure Architecture of Energy Harvesting Green Cloud Infrastructure

by Saurabh Singh, Pradip Kumar Sharma, Seo Yeon Moon and Jong Hyuk Park

Sustainability 2017, 9(4), 673; https://doi.org/10.3390/su9040673 - 24 Apr 2017

Cited by 9 | Viewed by 5432

Abstract

Nowadays, the high power consumption of data centers is the biggest challenge to making cloud computing greener. Many researchers are still seeking effective solutions to reduce or harvest the energy produced at data centers. To address this challenge, we propose a green cloud [...] Read more.

Nowadays, the high power consumption of data centers is the biggest challenge to making cloud computing greener. Many researchers are still seeking effective solutions to reduce or harvest the energy produced at data centers. To address this challenge, we propose a green cloud infrastructure which provides security and efficiency based on energy harvesting (EH-GC). The EH-GC is basically focused on harvesting the heat energy produced by data centers in the Infrastructure-as-a-Service (IaaS) infrastructure. A pyroelectric material is used to generate the electric current from heat using the Olsen cycle. In order to achieve efficient green cloud computing, the architecture utilizes a genetic algorithm for proper virtual machine allocation, taking into consideration less Service Level Agreement (SLA) violations. The architecture utilizes Multivariate Correlation Analysis (MCA) correlation analysis based on a triangular map area generation to detect Denial of Service (DoS) attacks in the data center layer of the IaaS. Finally, the experimental analysis is explained based on the energy parameter, which proves that our model is efficient and secure, and that it efficiently reuses the energy emitted from the data center. Full article

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7145 KiB

Open AccessArticle

Exclusive Contexts Resolver: A Low-Power Sensing Management System for Sustainable Context-Awareness in Exclusive Contexts

by Dusan Baek and Jung-Won Lee

Sustainability 2017, 9(4), 647; https://doi.org/10.3390/su9040647 - 19 Apr 2017

Cited by 1 | Viewed by 4197

Abstract

Several studies focus on sustainable context-awareness of a mobile device to which power is supplied from a limited battery. However, the existing studies did not consider an unnecessary sensing operation in exclusive contexts wherein it is not possible for the exclusive contexts to [...] Read more.

Several studies focus on sustainable context-awareness of a mobile device to which power is supplied from a limited battery. However, the existing studies did not consider an unnecessary sensing operation in exclusive contexts wherein it is not possible for the exclusive contexts to logically exist at the same time and are instead occasionally inferred practically due to the inaccuracy of the context-awareness. Simultaneously inferring two or more exclusive contexts is semantically meaningless and leads to inefficient power consumption, and thus, it is necessary to handle this problem for sustainable context-awareness. To this end, in the present study, an exclusive contexts resolver (ExCore), which is a low-power sensing management system, is proposed for sustainable context-awareness in exclusive contexts. The ExCore takes the sensor behavior model to the developer and identifies the sensing operation inferring the exclusive contexts through unnecessary sensing operation search rules. It also generates low-power sensing operations. The application and middleware were evaluated with the low-power sensing operations generated by the ExCore. The results indicated an average power efficiency improvement of 12–62% depending on the test scenario. The ExCore helps application developers or middleware developers in providing sustainable context-aware service in exclusive contexts. Full article

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3022 KiB

Open AccessArticle

Cooperative Downlink Listening for Low-Power Long-Range Wide-Area Network

by Byoungwook Kim and Kwang-il Hwang

Sustainability 2017, 9(4), 627; https://doi.org/10.3390/su9040627 - 17 Apr 2017

Cited by 23 | Viewed by 6128

Abstract

Recently, the development of the Internet of Things (IoT) applications has become more active with the emergence of low-power wide-area network (LPWAN), which has the advantages of low-power and long communication distance. Among the various LPWAN technologies, long-range wide-area network (LoRaWAN, or LoRa) [...] Read more.

Recently, the development of the Internet of Things (IoT) applications has become more active with the emergence of low-power wide-area network (LPWAN), which has the advantages of low-power and long communication distance. Among the various LPWAN technologies, long-range wide-area network (LoRaWAN, or LoRa) is considered as the most mature technology. However, since LoRa performs uplink-oriented communication to increase energy efficiency, there is a restriction on the downlink function from the network server to the end devices. In this paper, we propose cooperative downlink listening to solve the fundamental problem of LoRa. In particular, the proposed scheme can be extended to various communication models such as groupcasting and geocasting by combining with the data-centric model. Experiments also show that the proposed technology not only significantly reduces network traffic compared to the LoRa standard, but also guarantees maximum energy efficiency of the LoRa. Full article

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