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394 KiB

Open AccessArticle

An Ontology-Based Context Model for Wireless Sensor Network (WSN) Management in the Internet of Things

by Yang Liu, Boon-Chong Seet and Adnan Al-Anbuky

J. Sens. Actuator Netw. 2013, 2(4), 653-674; https://doi.org/10.3390/jsan2040653 - 30 Sep 2013

Cited by 18 | Viewed by 9477

Wireless sensor networks (WSNs) are an enabling technology of context-aware systems. The Internet of Things (IoT), which has attracted much attention in recent years, is an emerging paradigm where everyday objects and spaces are made context-aware and interconnected through heterogeneous networks on a [...] Read more.

Wireless sensor networks (WSNs) are an enabling technology of context-aware systems. The Internet of Things (IoT), which has attracted much attention in recent years, is an emerging paradigm where everyday objects and spaces are made context-aware and interconnected through heterogeneous networks on a global scale. However, the IoT system can suffer from poor performances when its underlying networks are not optimized. In this paper, an ontology model for representing and facilitating context sharing between network entities in WSNs is proposed for the first time. The context model aims to enable optimal context-aware management of WSNs in IoT, which will also harness the rich context knowledge of IoT systems. Full article

(This article belongs to the Special Issue Feature Papers)

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1177 KiB

Open AccessArticle

iMASKO: A Genetic Algorithm Based Optimization Framework for Wireless Sensor Networks

by Nanhao Zhu and Ian O'Connor

J. Sens. Actuator Netw. 2013, 2(4), 675-699; https://doi.org/10.3390/jsan2040675 - 09 Oct 2013

Cited by 19 | Viewed by 9521

Abstract

In this paper we present the design and implementation of a generic GA-based optimization framework iMASKO (iNL@MATLAB Genetic Algorithm-based Sensor NetworK Optimizer) to optimize the performance metrics of wireless sensor networks. Due to the global [...] Read more.

In this paper we present the design and implementation of a generic GA-based optimization framework iMASKO (iNL@MATLAB Genetic Algorithm-based Sensor NetworK Optimizer) to optimize the performance metrics of wireless sensor networks. Due to the global search property of genetic algorithms, the framework is able to automatically and quickly fine tune hundreds of possible solutions for the given task to find the best suitable tradeoff. We test and evaluate the framework by using it to explore a SystemC-based simulation process to tune the configuration of the unslotted CSMA/CA algorithm of IEEE 802.15.4, aiming to discover the most available tradeoff solutions for the required performance metrics. In particular, in the test cases different sensor node platforms are under investigation. A weighted sum based cost function is used to measure the optimization effectiveness and capability of the framework. In the meantime, another experiment is performed to test the framework’s optimization characteristic in multi-scenario and multi-objectives conditions. Full article

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905 KiB

Open AccessArticle

MIMO Underwater Acoustic Communications in Ports and Shallow Waters at Very High Frequency

by Gaultier Real, Pierre-Philippe Beaujean and Pierre-Jean Bouvet

J. Sens. Actuator Netw. 2013, 2(4), 700-716; https://doi.org/10.3390/jsan2040700 - 11 Oct 2013

Cited by 5 | Viewed by 7618

Abstract

Hermes is a Single-Input Single-Output (SISO) underwater acoustic modem that achieves very high-bit rate digital communications in ports and shallow waters. Here, the authors study the capability of Hermes to support Multiple-Input-Multiple-Output (MIMO) technology. A least-square channel estimation algorithm is used to evaluate [...] Read more.

Hermes is a Single-Input Single-Output (SISO) underwater acoustic modem that achieves very high-bit rate digital communications in ports and shallow waters. Here, the authors study the capability of Hermes to support Multiple-Input-Multiple-Output (MIMO) technology. A least-square channel estimation algorithm is used to evaluate multiple MIMO channel impulse responses at the receiver end. A deconvolution routine is used to separate the messages coming from different sources. This paper covers the performance of both the channel estimation and the MIMO deconvolution processes using either simulated data or field data. The MIMO equalization performance is measured by comparing three relative root mean-squared errors (RMSE), obtained by calculations between the source signal (a pseudo-noise sequence) and the corresponding received MIMO signal at various stages of the deconvolution process; prior to any interference removal, at the output of the Linear Equalization (LE) process and at the output of an interference cancellation process with complete a priori knowledge of the transmitted signal. Using the simulated data, the RMSE using LE is −20.5 dB (where 0 dB corresponds to 100% of relative error) while the lower bound value is −33.4 dB. Using experimental data, the LE performance is −3.3 dB and the lower bound RMSE value is −27 dB. Full article

(This article belongs to the Special Issue Underwater Sensor Networks)

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37771 KiB

Open AccessArticle

Sensor Enclosures: Example Application and Implications for Data Coherence

by Georgios Maniatis, Trevor Hoey and Joseph Sventek

J. Sens. Actuator Netw. 2013, 2(4), 761-779; https://doi.org/10.3390/jsan2040761 - 11 Dec 2013

Cited by 9 | Viewed by 8598

Abstract

Sensors deployed in natural environments, such as rivers, beaches and glaciers, experience large forces and damaging environmental conditions. Sensors need to be robust, securely operate for extended time periods and be readily relocated and serviced. The sensors must be housed in materials that [...] Read more.

Sensors deployed in natural environments, such as rivers, beaches and glaciers, experience large forces and damaging environmental conditions. Sensors need to be robust, securely operate for extended time periods and be readily relocated and serviced. The sensors must be housed in materials that mimic natural conditions of size, density, shape and roughness. We have developed an encasement system for sensors required to measure large forces experienced by mobile river sediment grains. Sensors are housed within two discrete cases that are rigidly conjoined. The inner case exactly fits the sensor, radio components and power source. This case can be mounted within outer cases of any larger size and can be precisely moulded to match the shapes of natural sediment. Total grain mass can be controlled by packing the outer case with dense material. Case design uses Solid-WorksTM software, and shape-matching involved 3D laser scanning of natural pebbles. The cases were printed using a HP DesignjetTM 3D printer that generates high precision parts that lock rigidly in place. The casings are watertight and robust. Laboratory testing produces accurate results over a wider range of accelerations than previously reported. Full article

(This article belongs to the Special Issue Underwater Sensor Networks)

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Review

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597 KiB

Open AccessReview

Software Updating in Wireless Sensor Networks: A Survey and Lacunae

by Stephen Brown and Cormac J. Sreenan

J. Sens. Actuator Netw. 2013, 2(4), 717-760; https://doi.org/10.3390/jsan2040717 - 14 Nov 2013

Cited by 32 | Viewed by 10331

Abstract

Wireless Sensor Networks are moving out of the laboratory and into the field. For a number of reasons there is often a need to update sensor node software, or node configuration, after deployment. The need for over-the-air updates is driven both by the [...] Read more.

Wireless Sensor Networks are moving out of the laboratory and into the field. For a number of reasons there is often a need to update sensor node software, or node configuration, after deployment. The need for over-the-air updates is driven both by the scale of deployments, and by the remoteness and inaccessibility of sensor nodes. This need has been recognized since the early days of sensor networks, and research results from the related areas of mobile networking and distributed systems have been applied to this area. In order to avoid any manual intervention, the update process needs to be autonomous. This paper presents a comprehensive survey of software updating in Wireless Sensor Networks, and analyses the features required to make these updates autonomous. A new taxonomy of software update features and a new model for fault detection and recovery are presented. The paper concludes by identifying the lacunae relating to autonomous software updates, providing direction for future research. Full article

(This article belongs to the Special Issue Feature Papers)

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J. Sens. Actuator Netw., Volume 2, Issue 4 (December 2013) – 5 articles , Pages 653-779

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