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QoS in Wireless Sensor Networks

A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Sensor Networks".

Deadline for manuscript submissions: closed (30 June 2018) | Viewed by 39253

Special Issue Editor


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Guest Editor
Inria Lille-Nord Europe, 59650 Villeneuve-d'Ascq, France
Interests: Internet of Things; wireless sensor networks; RFID; wireless robots networks; services (localization, neighbor discovery, etc)
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The last few decades have witnessed the advance of multiple wireless sensor networks, in both the academic and industrial worlds. A wireless sensor network is composed of a set of distributed hardware-constrained wireless devices in charge of monitoring a targeted area. Applications of WSN are multiple, and range from environment monitoring to urban health monitoring, as well as healthcare, logistic applications, and Smart Grids to name a few. The growing demand of usage of wireless sensor applications for different aspects makes quality-of-service (QoS) one of the paramount issues in wireless sensor applications.

Each application features its own requirement in terms of QoS. In each application, a great deal of information may request different QoS-processing (regular monitoring messages vs. alarm messages). However, due to the unreliable characteristics of the wireless medium and hardware limitations of devices, providing QoS in WSN-based applications remain a challenging task.

This Special Issue calls for high quality, up-to-date innovative original current advances in QoS management in wireless sensor networks.

The list of possible topics includes, but is not limited to:

  • QoS WSN classification
  • QoS-based routing protocols in WSN
  • QoS differentiation management in WSN
  • Smart Grid application
  • Modeling of QoS in WSN
  • Metrics for QoS in WSN
  • Implementation of QoS in WSN showcases
Dr. Nathalie Mitton
Guest Editor

Manuscript Submission Information

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Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Published Papers (11 papers)

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Editorial

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2 pages, 153 KiB  
Editorial
QoS in Wireless Sensor Networks
by Nathalie Mitton
Sensors 2018, 18(11), 3983; https://doi.org/10.3390/s18113983 - 16 Nov 2018
Cited by 5 | Viewed by 2068
Abstract
The last decades have witnessed advances in multiple wireless sensor networks in both the academic and industrial world. [...] Full article
(This article belongs to the Special Issue QoS in Wireless Sensor Networks)

Research

Jump to: Editorial

24 pages, 1271 KiB  
Article
Extensive Experimentations on Opportunistic Routing in Wireless Sensor Networks
by Ichrak Amdouni, Cedric Adjih, Nadjib AitSaadi and Paul Muhlethaler
Sensors 2018, 18(9), 3031; https://doi.org/10.3390/s18093031 - 10 Sep 2018
Cited by 6 | Viewed by 2786
Abstract
In this paper, we design and experiment ODYSSE (Opportunistic Duty cYcle based routing protocol for wirelesS Sensor nEtworks) protocol. It combines three main mechanisms: (i) duty cycle, where nodes alternate between active and sleep states, (ii) opportunistic routing where routing tables do not [...] Read more.
In this paper, we design and experiment ODYSSE (Opportunistic Duty cYcle based routing protocol for wirelesS Sensor nEtworks) protocol. It combines three main mechanisms: (i) duty cycle, where nodes alternate between active and sleep states, (ii) opportunistic routing where routing tables do not exist and the next hop is elected once the packet arrives, and (iii) source coding with LDPC (Low-Density Parity-Check) codes in order to face packet losses while minimizing energy consumption. We focus on two heterogeneous scenarios: bulk image transmission and infrequent events reporting. Modeling the average waiting delay of forwarders, we show that simple relay selection strategies are effective. We used 45 Arduino nodes communicating with IEEE 802.15.4 (XBee) within the large platform FIT IoT-LAB (IoT-LAB is part of the large platform FIT: Future Internet of Things). We implement and extensively study the behavior and performance of our proposal ODYSSE. We show that the three techniques fit perfectly, yielding a robust low complexity protocol for highly constrained nodes in typical IoT applications. Full article
(This article belongs to the Special Issue QoS in Wireless Sensor Networks)
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18 pages, 524 KiB  
Article
What Is the Fastest Way to Connect Stations to a Wi-Fi HaLow Network?
by Dmitry Bankov, Evgeny Khorov, Andrey Lyakhov, Ekaterina Stepanova, Le Tian and Jeroen Famaey
Sensors 2018, 18(9), 2744; https://doi.org/10.3390/s18092744 - 21 Aug 2018
Cited by 13 | Viewed by 3343
Abstract
Wi-Fi HaLow is an adaptation of the widespread Wi-Fi technology for the Internet of Things scenarios. Such scenarios often involve numerous wireless stations connected to a shared channel, and contention for the channel significantly affects the performance in such networks. Wi-Fi HaLow contains [...] Read more.
Wi-Fi HaLow is an adaptation of the widespread Wi-Fi technology for the Internet of Things scenarios. Such scenarios often involve numerous wireless stations connected to a shared channel, and contention for the channel significantly affects the performance in such networks. Wi-Fi HaLow contains numerous solutions aimed at handling the contention between stations, two of which, namely, the Centralized Authentication Control (CAC) and the Distributed Authentication Control (DAC), address the contention reduction during the link set-up process. The link set-up process is special because the access point knows nothing of the connecting stations and its means of control of these stations are very limited. While DAC is self-adaptive, CAC does require an algorithm to dynamically control its parameters. Being just a framework, the Wi-Fi HaLow standard neither specifies such an algorithm nor recommends which protocol, CAC or DAC, is more suitable in a given situation. In this paper, we solve both issues by developing a novel robust close-to-optimal algorithm for CAC and compare CAC and DAC in a vast set of experiments. Full article
(This article belongs to the Special Issue QoS in Wireless Sensor Networks)
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16 pages, 1380 KiB  
Article
Multiple Instances QoS Routing in RPL: Application to Smart Grids
by Jad Nassar, Matthieu Berthomé, Jérémy Dubrulle, Nicolas Gouvy, Nathalie Mitton and Bruno Quoitin
Sensors 2018, 18(8), 2472; https://doi.org/10.3390/s18082472 - 30 Jul 2018
Cited by 44 | Viewed by 4103
Abstract
The Smart Grid (SG) aims to transform the current electric grid into a “smarter” network where the integration of renewable energy resources, energy efficiency and fault tolerance are the main benefits. This is done by interconnecting every energy source, storage point or central [...] Read more.
The Smart Grid (SG) aims to transform the current electric grid into a “smarter” network where the integration of renewable energy resources, energy efficiency and fault tolerance are the main benefits. This is done by interconnecting every energy source, storage point or central control point with connected devices, where heterogeneous SG applications and signalling messages will have different requirements in terms of reliability, latency and priority. Hence, data routing and prioritization are the main challenges in such networks. So far, RPL (Routing Protocol for Low-Power and Lossy networks) protocol is widely used on Smart Grids for distributing commands over the grid. RPL assures traffic differentiation at the network layer in wireless sensor networks through the logical subdivision of the network in multiple instances, each one relying on a specific Objective Function. However, RPL is not optimized for Smart Grids, as its main objective functions and their associated metric does not allow Quality of Service differentiation. To overcome this, we propose OFQS an objective function with a multi-objective metric that considers the delay and the remaining energy in the battery nodes alongside with the dynamic quality of the communication links. Our function automatically adapts to the number of instances (traffic classes) providing a Quality of Service differentiation based on the different Smart Grid applications requirements. We tested our approach on a real sensor testbed. The experimental results show that our proposal provides a lower packet delivery latency and a higher packet delivery ratio while extending the lifetime of the network compared to solutions in the literature. Full article
(This article belongs to the Special Issue QoS in Wireless Sensor Networks)
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17 pages, 2980 KiB  
Article
Recharging Schedule for Mitigating Data Loss in Wireless Rechargeable Sensor Network
by Haolin Liu, Qingyong Deng, Shujuan Tian, Xin Peng and Tingrui Pei
Sensors 2018, 18(7), 2223; https://doi.org/10.3390/s18072223 - 10 Jul 2018
Cited by 15 | Viewed by 2971
Abstract
Wireless Power Transfer (WPT) technology is considered as a promising approach to make Wireless Rechargeable Sensor Network (WRSN) work perpetually. In WRSN, a vehicle exists, termed a mobile charger, which can move close to sensor nodes and charge them wirelessly. Due to the [...] Read more.
Wireless Power Transfer (WPT) technology is considered as a promising approach to make Wireless Rechargeable Sensor Network (WRSN) work perpetually. In WRSN, a vehicle exists, termed a mobile charger, which can move close to sensor nodes and charge them wirelessly. Due to the mobile charger’s limited traveling distance and speed, not every node that needs to be charged may be serviced in time. Thus, in such scenario, how to make a route plan for the mobile charger to determine which nodes should be charged first is a critical issue related to the network’s Quality of Service (QoS). In this paper, we propose a mobile charger’s scheduling algorithm to mitigate the data loss of network by considering the node’s criticality in connectivity and energy. First, we introduce a novel metric named criticality index to measure node’s connectivity contribution, which is computed as a summation of node’s neighbor dissimilarity. Furthermore, to reflect the node’s charging demand, an indicator called energy criticality is adopted to weight the criticality index, which is a normalized ratio of the node’s consumed energy to its total energy. Then, we formulate an optimization problem with the objective of maximizing total weighted criticality indexes of nodes to construct a charging tour, subject to the mobile charger’s traveling distance constraint. Due to the NP-hardness of the problem, a heuristic algorithm is proposed to solve it. The heuristic algorithm includes three steps, which is spanning tree growing, tour construction and tour improvement. Finally, we compare the proposed algorithm to the state-of-art scheduling algorithms. The obtained results demonstrate that the proposed algorithm is a promising one. Full article
(This article belongs to the Special Issue QoS in Wireless Sensor Networks)
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14 pages, 1120 KiB  
Article
Cooperative Feedback Bits Allocation and Transmit Power Control in Underlay Cognitive Radio Networks
by Deokhui Lee and Jaewoo So
Sensors 2018, 18(6), 1809; https://doi.org/10.3390/s18061809 - 04 Jun 2018
Cited by 6 | Viewed by 2471
Abstract
In this paper, we consider an underlay cognitive radio network where the spectrum is shared with the primary network. Due to the coexistence of primary and secondary networks, primary users (PUs) are interfered with by the inter-network interference, at the same time secondary [...] Read more.
In this paper, we consider an underlay cognitive radio network where the spectrum is shared with the primary network. Due to the coexistence of primary and secondary networks, primary users (PUs) are interfered with by the inter-network interference, at the same time secondary users (SUs) counteract the intra-network (inter-user) interference. Based on the cooperative feedback between the primary network and the secondary network, the secondary transmitter (ST) applies the cognitive beamforming to suppress the interference to PUs while improving the sum rate of SUs. We herein propose an adaptive feedback bits allocation among multiple PUs and SUs where the quantized channel direction information (CDI) for the interference channel is forwarded to the ST in order to utilize the beamforming. Moreover, based on the cognitive beamforming, we adjust the transmit power of the ST under the constraint of the average interference at PUs. To jointly solve the feedback bits allocation and the transmit power control problems, we formulate an optimization problem which requires a little iterations compared with the separated feedback bits allocation and the transmit power control problems. Numerical results show that the proposed scheme significantly improves the sum rate of SUs while satisfying the average interference constraint at PUs. Full article
(This article belongs to the Special Issue QoS in Wireless Sensor Networks)
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17 pages, 1158 KiB  
Article
Heterogeneous Wireless Networks for Smart Grid Distribution Systems: Advantages and Limitations
by Tarek Khalifa, Atef Abdrabou, Khaled Shaban and A. M. Gaouda
Sensors 2018, 18(5), 1517; https://doi.org/10.3390/s18051517 - 11 May 2018
Cited by 16 | Viewed by 3877
Abstract
Supporting a conventional power grid with advanced communication capabilities is a cornerstone to transferring it to a smart grid. A reliable communication infrastructure with a high throughput can lay the foundation towards the ultimate objective of a fully automated power grid with self-healing [...] Read more.
Supporting a conventional power grid with advanced communication capabilities is a cornerstone to transferring it to a smart grid. A reliable communication infrastructure with a high throughput can lay the foundation towards the ultimate objective of a fully automated power grid with self-healing capabilities. In order to realize this objective, the communication infrastructure of a power distribution network needs to be extended to cover all substations including medium/low voltage ones. This shall enable information exchange among substations for a variety of system automation purposes with a low latency that suits time critical applications. This paper proposes the integration of two heterogeneous wireless technologies (such as WiFi and cellular 3G/4G) to provide reliable and fast communication among primary and secondary distribution substations. This integration allows the transmission of different data packets (not packet replicas) over two radio interfaces, making these interfaces act like a one data pipe. Thus, the paper investigates the applicability and effectiveness of employing heterogeneous wireless networks (HWNs) in achieving the desired reliability and timeliness requirements of future smart grids. We study the performance of HWNs in a realistic scenario under different data transfer loads and packet loss ratios. Our findings reveal that HWNs can be a viable data transfer option for smart grids. Full article
(This article belongs to the Special Issue QoS in Wireless Sensor Networks)
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28 pages, 6179 KiB  
Article
Adaptive Aggregation Routing to Reduce Delay for Multi-Layer Wireless Sensor Networks
by Xujing Li, Anfeng Liu, Mande Xie, Neal N. Xiong, Zhiwen Zeng and Zhiping Cai
Sensors 2018, 18(4), 1216; https://doi.org/10.3390/s18041216 - 16 Apr 2018
Cited by 30 | Viewed by 4617
Abstract
The quality of service (QoS) regarding delay, lifetime and reliability is the key to the application of wireless sensor networks (WSNs). Data aggregation is a method to effectively reduce the data transmission volume and improve the lifetime of a network. In the previous [...] Read more.
The quality of service (QoS) regarding delay, lifetime and reliability is the key to the application of wireless sensor networks (WSNs). Data aggregation is a method to effectively reduce the data transmission volume and improve the lifetime of a network. In the previous study, a common strategy required that data wait in the queue. When the length of the queue is greater than or equal to the predetermined aggregation threshold ( N t ) or the waiting time is equal to the aggregation timer ( T t ), data are forwarded at the expense of an increase in the delay. The primary contributions of the proposed Adaptive Aggregation Routing (AAR) scheme are the following: (a) the senders select the forwarding node dynamically according to the length of the data queue, which effectively reduces the delay. In the AAR scheme, the senders send data to the nodes with a long data queue. The advantages are that first, the nodes with a long data queue need a small amount of data to perform aggregation; therefore, the transmitted data can be fully utilized to make these nodes aggregate. Second, this scheme balances the aggregating and data sending load; thus, the lifetime increases. (b) An improved AAR scheme is proposed to improve the QoS. The aggregation deadline ( T t ) and the aggregation threshold ( N t ) are dynamically changed in the network. In WSNs, nodes far from the sink have residual energy because these nodes transmit less data than the other nodes. In the improved AAR scheme, the nodes far from the sink have a small value of T t and N t to reduce delay, and the nodes near the sink are set to a large value of T t and N t to reduce energy consumption. Thus, the end to end delay is reduced, a longer lifetime is achieved, and the residual energy is fully used. Simulation results demonstrate that compared with the previous scheme, the performance of the AAR scheme is improved. This scheme reduces the delay by 14.91%, improves the lifetime by 30.91%, and increases energy efficiency by 76.40%. Full article
(This article belongs to the Special Issue QoS in Wireless Sensor Networks)
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17 pages, 7517 KiB  
Article
Energy-Efficient Data Collection Method for Sensor Networks by Integrating Asymmetric Communication and Wake-Up Radio
by Masanari Iwata, Suhua Tang and Sadao Obana
Sensors 2018, 18(4), 1121; https://doi.org/10.3390/s18041121 - 06 Apr 2018
Cited by 12 | Viewed by 3800
Abstract
In large-scale wireless sensor networks (WSNs), nodes close to sink nodes consume energy more quickly than other nodes due to packet forwarding. A mobile sink is a good solution to this issue, although it causes two new problems to nodes: (i) overhead of [...] Read more.
In large-scale wireless sensor networks (WSNs), nodes close to sink nodes consume energy more quickly than other nodes due to packet forwarding. A mobile sink is a good solution to this issue, although it causes two new problems to nodes: (i) overhead of updating routing information; and (ii) increased operating time due to aperiodic query. To solve these problems, this paper proposes an energy-efficient data collection method, Sink-based Centralized transmission Scheduling (SC-Sched), by integrating asymmetric communication and wake-up radio. Specifically, each node is equipped with a low-power wake-up receiver. The sink node determines transmission scheduling, and transmits a wake-up message using a large transmission power, directly activating a pair of nodes simultaneously which will communicate with a normal transmission power. This paper further investigates how to deal with frame loss caused by fading and how to mitigate the impact of the wake-up latency of communication modules. Simulation evaluations confirm that using multiple channels effectively reduces data collection time and SC-Sched works well with a mobile sink. Compared with the conventional duty-cycling method, SC-Sched greatly reduces total energy consumption and improves the network lifetime by 7.47 times in a WSN with 4 data collection points and 300 sensor nodes. Full article
(This article belongs to the Special Issue QoS in Wireless Sensor Networks)
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20 pages, 2485 KiB  
Article
An Autonomous Connectivity Restoration Algorithm Based on Finite State Machine for Wireless Sensor-Actor Networks
by Ying Zhang, Jun Wang and Guan Hao
Sensors 2018, 18(1), 153; https://doi.org/10.3390/s18010153 - 08 Jan 2018
Cited by 27 | Viewed by 4264
Abstract
With the development of autonomous unmanned intelligent systems, such as the unmanned boats, unmanned planes and autonomous underwater vehicles, studies on Wireless Sensor-Actor Networks (WSANs) have attracted more attention. Network connectivity algorithms play an important role in data exchange, collaborative detection and information [...] Read more.
With the development of autonomous unmanned intelligent systems, such as the unmanned boats, unmanned planes and autonomous underwater vehicles, studies on Wireless Sensor-Actor Networks (WSANs) have attracted more attention. Network connectivity algorithms play an important role in data exchange, collaborative detection and information fusion. Due to the harsh application environment, abnormal nodes often appear, and the network connectivity will be prone to be lost. Network self-healing mechanisms have become critical for these systems. In order to decrease the movement overhead of the sensor-actor nodes, an autonomous connectivity restoration algorithm based on finite state machine is proposed. The idea is to identify whether a node is a critical node by using a finite state machine, and update the connected dominating set in a timely way. If an abnormal node is a critical node, the nearest non-critical node will be relocated to replace the abnormal node. In the case of multiple node abnormality, a regional network restoration algorithm is introduced. It is designed to reduce the overhead of node movements while restoration happens. Simulation results indicate the proposed algorithm has better performance on the total moving distance and the number of total relocated nodes compared with some other representative restoration algorithms. Full article
(This article belongs to the Special Issue QoS in Wireless Sensor Networks)
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19 pages, 2675 KiB  
Article
Counter-Based Broadcast Scheme Considering Reachability, Network Density, and Energy Efficiency for Wireless Sensor Networks
by Ji-Young Jung, Dong-Yoon Seo and Jung-Ryun Lee
Sensors 2018, 18(1), 120; https://doi.org/10.3390/s18010120 - 04 Jan 2018
Cited by 19 | Viewed by 4033
Abstract
A wireless sensor network (WSN) is emerging as an innovative method for gathering information that will significantly improve the reliability and efficiency of infrastructure systems. Broadcast is a common method to disseminate information in WSNs. A variety of counter-based broadcast schemes have been [...] Read more.
A wireless sensor network (WSN) is emerging as an innovative method for gathering information that will significantly improve the reliability and efficiency of infrastructure systems. Broadcast is a common method to disseminate information in WSNs. A variety of counter-based broadcast schemes have been proposed to mitigate the broadcast-storm problems, using the count threshold value and a random access delay. However, because of the limited propagation of the broadcast-message, there exists a trade-off in a sense that redundant retransmissions of the broadcast-message become low and energy efficiency of a node is enhanced, but reachability become low. Therefore, it is necessary to study an efficient counter-based broadcast scheme that can dynamically adjust the random access delay and count threshold value to ensure high reachability, low redundant of broadcast-messages, and low energy consumption of nodes. Thus, in this paper, we first measure the additional coverage provided by a node that receives the same broadcast-message from two neighbor nodes, in order to achieve high reachability with low redundant retransmissions of broadcast-messages. Second, we propose a new counter-based broadcast scheme considering the size of the additional coverage area, distance between the node and the broadcasting node, remaining battery of the node, and variations of the node density. Finally, we evaluate performance of the proposed scheme compared with the existing counter-based broadcast schemes. Simulation results show that the proposed scheme outperforms the existing schemes in terms of saved rebroadcasts, reachability, and total energy consumption. Full article
(This article belongs to the Special Issue QoS in Wireless Sensor Networks)
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