Special Issue "Algorithms for Wireless Sensor Networks"

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A special issue of Algorithms (ISSN 1999-4893).

Deadline for manuscript submissions: closed (30 October 2014)

Special Issue Editors

Guest Editor
Prof. Dr. Marc Sevaux

University of South Brittany, CNRS, UMR 6285, Lab-STICC, Research Center - BP 92116, F-56321 Lorient Cedex, France
Website | E-Mail
Interests: design of heuristics and metaheuristics; mathematical programming; matheuristics; routing problems; optimization in electronic design; wireless sensor networks; scheduling
Guest Editor
Dr. Massimo Vecchio

Senior Researcher, Smart Internet of Things Research Group @ CREATE-NET (Center for REsearch And Telecommunication Experimentation for NETworked communities), Italy
Website | E-Mail
Interests: wireless sensor networks design and applications; internet of things devices and services; bio-inspired modelling and optimization.
Guest Editor
Dr. Ahcène Bounceur

University of Brest (UBO), European University of Brittany (UEB), Department of Computer Science, Lab-STICC Laboratory (CNRS UMR 6285)
Website | E-Mail
Interests: cad tool development for the evaluation of analog and mixed-signal circuit bist techniques; modelling and optimization of analog, mixed-signal and rf circuit; statistical modelling of analog circuits; statistical methods for data-mining; tools for designing and simulating wireless sensors networks

Special Issue Information

Dear Colleagues,

With rapid advances in Future Internet technologies, such as the Internet of Things, the sensor cloud and the mobile Internet, the physical world is, on a daily basis, getting more connected and is moving faster towards the always-connected paradigm. Under this paradigm, cheap, wireless-connected and easily configurable sensors can sense and collect environmental data anytime and anywhere. Unfortunately, the high availability and cheapness of sensing technology can only soften the barriers for actually supporting the levels of scalability, reliability and resilience required for this paradigm to be global. Moreover, the dearth of accurate simulation models and efficient software methods specifically designed for Wireless Sensor Networks (WSNs) leads to a lack of reliable algorithms, whose availability is essential to set up the future deployments in the best conditions. This includes, for instance, systematic considerations on the impact of channel interferences, nodes mobility and network dynamicity in general, which are crucial points not adequately addressed yet, hence weakening or preventing the proper operation of the resulting networks. Thus, to smash such barriers we still need efficient, fast and accurate algorithms, especially to manage communications and judiciously handle the tiny computational, memory and battery resources of the sensor nodes comprising the networks.

This Special Issue will provide a forum advancing the state-of-the-art concerning such algorithms for WSNs; discussions will concern the theoretical concepts, practical designs, and implementations used for running experiments, services and/or applications. Potential topics include (but are not limited to) algorithms for:

  • wireless sensor nodes (re-)deployment
  • area coverage in WSNs
  • object detection/tracking in WSNs
  • data collection/aggregation/dissemination in WSNs
  • data compression and signal processing in WSNs
  • efficient routing/medium access control protocols in WSNs
  • real-world experiments/services/applications of WSNs
  • reliable and accurate simulation models for WSNs
  • accelerating simulations (distributed, parallelized, etc.)

Prof. Dr. Marc Sevaux
Dr. Massimo Vecchio
Dr. Ahcène Bounceur
Guest Editors

Submission

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. Papers will be published continuously (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are refereed through a peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Algorithms is an international peer-reviewed Open Access quarterly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 300 CHF (Swiss Francs). English correction and/or formatting fees of 250 CHF (Swiss Francs) will be charged in certain cases for those articles accepted for publication that require extensive additional formatting and/or English corrections.

Keywords

  • wireless sensor networks
  • algorithms
  • signal processing
  • network protocols
  • communication
  • mobility
  • simulation
  • real-world applications and services

Published Papers (3 papers)

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Research

Open AccessArticle Fusion of Multiple Pyroelectric Characteristics for Human Body Identification
Algorithms 2014, 7(4), 685-702; doi:10.3390/a7040685
Received: 13 October 2014 / Revised: 8 December 2014 / Accepted: 10 December 2014 / Published: 18 December 2014
Cited by 1 | PDF Full-text (762 KB) | HTML Full-text | XML Full-text
Abstract
Due to instability and poor identification ability of single pyroelectric infrared (PIR) detector for human target identification, this paper proposes a new approach to fuse the information collected from multiple PIR sensors for human identification. Firstly, Fast Fourier Transform (FFT), Short Time Fourier
[...] Read more.
Due to instability and poor identification ability of single pyroelectric infrared (PIR) detector for human target identification, this paper proposes a new approach to fuse the information collected from multiple PIR sensors for human identification. Firstly, Fast Fourier Transform (FFT), Short Time Fourier Transform (STFT), Wavelet Transform (WT) and Wavelet Packet Transform (WPT) are adopted to extract features of the human body, which can be achieved by single PIR sensor. Then, we apply Principal Component Analysis (PCA) and Support Vector Machine (SVM) to reduce the characteristic dimensions and to classify the human targets, respectively. Finally, Fuzzy Comprehensive Evaluation (FCE) is utilized to fuse recognition results from multiple PIR sensors to finalize human identification. The pyroelectric characteristics under scenarios with different people and/or different paths are analyzed by various experiments, and the recognition results with/without fusion procedure are also shown and compared. The experimental results demonstrate our scheme has improved efficiency for human identification. Full article
(This article belongs to the Special Issue Algorithms for Wireless Sensor Networks)
Open AccessArticle A CR Spectrum Allocation Algorithm in Smart Grid Wireless Sensor Network
Algorithms 2014, 7(4), 510-522; doi:10.3390/a7040510
Received: 7 May 2014 / Revised: 21 September 2014 / Accepted: 23 September 2014 / Published: 13 October 2014
Cited by 1 | PDF Full-text (1413 KB) | HTML Full-text | XML Full-text
Abstract
Cognitive radio (CR) method was introduced in smart grid communication systems to resolve potential maladies such as the coexistence of heterogeneous networks, overloaded data flow, diversity in data structures, and unstable quality of service (QOS). In this paper, a cognitive spectrum allocation algorithm
[...] Read more.
Cognitive radio (CR) method was introduced in smart grid communication systems to resolve potential maladies such as the coexistence of heterogeneous networks, overloaded data flow, diversity in data structures, and unstable quality of service (QOS). In this paper, a cognitive spectrum allocation algorithm based on non-cooperative game theory is proposed. The CR spectrum allocation model was developed by modifying the traditional game model via the insertion of a time variable and a critical function. The computing simulation result shows that the improved spectrum allocation algorithm can achieve stable spectrum allocation strategies and avoid the appearance of multi-Nash equilibrium at the expense of certain sacrifices in the system utility. It is suitable for application in distributed cognitive networks in power grids, thus contributing to the improvement of the isomerism and data capacity of power communication systems. Full article
(This article belongs to the Special Issue Algorithms for Wireless Sensor Networks)
Open AccessArticle Algorithm Based on Heuristic Strategy to Infer Lossy Links in Wireless Sensor Networks
Algorithms 2014, 7(3), 397-404; doi:10.3390/a7030397
Received: 7 May 2014 / Revised: 8 July 2014 / Accepted: 11 July 2014 / Published: 29 July 2014
Cited by 1 | PDF Full-text (271 KB) | HTML Full-text | XML Full-text
Abstract
With the maturing of the actual application of wireless sensor networks, network fault management is eagerly demanded. Severe link packet loss affects the performance of wireless sensor networks, so it must be found and repaired. Subject to the constraints on limited resources, lossy
[...] Read more.
With the maturing of the actual application of wireless sensor networks, network fault management is eagerly demanded. Severe link packet loss affects the performance of wireless sensor networks, so it must be found and repaired. Subject to the constraints on limited resources, lossy link is inferred using end to end measurement and network tomography. The algorithm based on heuristic strategy is proposed. This maps the problem of lossy links inferences to minimal set-cover problems. The performance of inference algorithms is evaluated by simulation, and the simulation results indicate feasibility and efficiency of the method. Full article
(This article belongs to the Special Issue Algorithms for Wireless Sensor Networks)

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