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Deployment and Control of Wireless Sensor Networks

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

Deadline for manuscript submissions: closed (30 October 2020) | Viewed by 10740

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Prof. Dr. Abdelhamid Mellouk

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Guest Editor

IT4H.EPISEN - NT.IUTCV Departments, TincNET Research Team, University of Paris-Est Creteil (UPEC), F-94400 Vitry-sur-Seine, France
Interests: communication protocols and algorithms; switching and routing; dynamic wireless and mobile networks (sensors, VANET, and so on); quality of service; quality of experience; adaptive network real-time control; video streaming; Internet of Things; cloud computing
Special Issues, Collections and Topics in MDPI journals

Dr. Mustapha Reda Senouci

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Guest Editor

Distributed and Complex Systems Laboratory, Ecole Militaire Polytechnique, Algiers, Algeria
Interests: sensors and ad-hoc networks; Internet of things (IoT); next generation networks

Prof. Dr. Nidal Nasser

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Guest Editor

Alfaisal University—KSA
Interests: wireless and mobile ad hoc and sensor networks; mobile and wireless computing; ubiquitous and pervasive computing; radio resource management; provisioning quality of service; scalable distributed systems and algorithms; performance evaluation of communication networks and communication protocols and algorithms; Internet of things; cloud computing

Dr. Hai Anh Tran

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Guest Editor

School of Information and Communication Technology, Hanoi University of Science and Technology, Hanoi 10000, Vietnam
Interests: computer networks; next-generation networks; software-defined networks; knowledge-defined networks; machine learning; optimization; quality of service (QoS); quality of experience (QoE); Internet of Things; cloud computing
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

In the past two decades, wireless sensor networks (WSNs) have emerged, opening new research directions that are still evolving because of the new challenges and technological advances in the field. A WSN consists of many sensor nodes that can sense, measure, and gather information about their surrounding environment, and transmit the sensed data to the final user via wireless links. As a bridge between cyberspace and the physical world, WSNs have enabled new applications and opened new perspectives. Moreover, WSNs are key central building blocks in the Internet of things (IoT) and smart systems.

The successful completion of the mission (control, monitoring, etc.) assigned to a WSN requires that the network should be deployed and managed in a rigorous manner, which guarantees the QoS performance of the services provided by the WSN throughout the assigned mission. This QoS could encompass different metrics, such as coverage, connectivity, and energy consumption. In practice, WSNs could be deployed in distinct areas, using different architectures and typologies, while employing several types of nodes (sensor nodes, relay nodes, data collectors, etc.).

WSNs have gained plenty of popularity in a wide range of applications, and have attained a high level of maturity. In this Special Issue, we will investigate WSNs, with a focus on the deployment and control topics, with a specific emphasis on the practical aspects. Deployment encompasses all of the tasks performed during the network setup (e.g., sensor placement), whereas control includes the techniques employed to maintain the QoS performance of the services provided by the WSN (e.g., connectivity restoration) and the end-to-end QoE driven application.

Research topics including, but not limited to, the following, will be considered:

WSNs deployment (sensor and relay node placement) under realistic scenarios
QoS and QoE in a WSN context
Coverage and connectivity optimization
Long-life sensor node deployment and topology control
Network health monitoring and management
Scheduling algorithms for WSNs
Energy harvesting and energy management
Measurements and models for coverage, connectivity, and energy consumption of WSNs
Applications and deployment experiences (health, atmospheric pollution, smart cities, vehicular, domotics, submarine, etc.)

Prof. Dr. Abdelhamid Mellouk
Dr. Mustapha Reda Senouci
Prof. Dr. Nidal Nasser
Dr. Hai Anh Tran
Guest Editors

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.

Keywords

wireless sensor networks
practical experimentation
deployment
sensor placement
coverage
connectivity
3D terrains
scalability
real-life WSN application

Published Papers (4 papers)

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Research

18 pages, 3725 KiB

Open AccessArticle

Disjoint Spanning Tree Based Reliability Evaluation of Wireless Sensor Network

by Sonam Lata, Shabana Mehfuz, Shabana Urooj, Asmaa Ali and Nidal Nasser

Sensors 2020, 20(11), 3071; https://doi.org/10.3390/s20113071 - 29 May 2020

Cited by 5 | Viewed by 2713

Abstract

Wireless sensor networks (WSNs) are becoming very common in numerous manufacturing industries; especially where it is difficult to connect a sensor to a sink. This is an evolving issue for researchers attempting to contribute to the proliferation of WSNs. Monitoring a WSN depends on the type of collective data the sensor nodes have acquired. It is necessary to quantify the performance of these networks with the help of network reliability measures to ensure the stable operation of WSNs. Reliability plays a key role in the efficacy of any large-scale application of WSNs. The communication reliability in a wireless sensor network is an influential parameter for enhancing network performance for secure, desirable, and successful communication. The reliability of WSNs must incorporate the design variables, coverage, lifetime, and connectivity into consideration; however, connectivity is the most important factor, especially in a harsh environment on a large scale. The proposed algorithm is a one-step approach, which starts with the recognition of a specific spanning tree only. It utilizes all other disjoint spanning trees, which are generated directly in a simple manner and consume less computation time and memory. A binary decision illustration is presented for the enumeration of K-coverage communication reliability. In this paper, the issue of computing minimum spanning trees was addressed and it is a pertinent method for further evaluating reliability for WSNs. This paper inspects the reliability of WSNs and proposes a method for evaluating the flow-oriented reliability of WSNs. Further, a modified approach for the sum-of-disjoint products to determine the reliability of WSN from the enumerated minimal spanning trees is proposed. The proposed algorithm when implemented for different sizes of WSNs demonstrates its applicability to WSNs of various scales. The proposed methodology is less complex and more efficient in terms of reliability. Full article

(This article belongs to the Special Issue Deployment and Control of Wireless Sensor Networks)

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25 pages, 483 KiB

Open AccessArticle

An Elite Hybrid Particle Swarm Optimization for Solving Minimal Exposure Path Problem in Mobile Wireless Sensor Networks

by Nguyen Thi My Binh, Abdelhamid Mellouk, Huynh Thi Thanh Binh, Le Vu Loi, Dang Lam San and Tran Hai Anh

Sensors 2020, 20(9), 2586; https://doi.org/10.3390/s20092586 - 1 May 2020

Cited by 13 | Viewed by 2575

Abstract

Mobile wireless sensor networks (MWSNs), a sub-class of wireless sensor networks (WSNs), have recently been a growing concern among the academic community. MWSNs can improve network coverage quality which reflects how well a region of interest is monitored or tracked by sensors. To evaluate the coverage quality of WSNs, we frequently use the minimal exposure path (MEP) in the sensing field as an effective measurement. MEP refers to the worst covered path along which an intruder can go through the sensor network with the lowest possibility of being detected. It is greatly valuable for network designers to recognize the vulnerabilities of WSNs and to make necessary improvements. Most prior studies focused on this problem under a static sensor network, which may suffer from several drawbacks; i.e., failure in sensor position causes coverage holes in the network. This paper investigates the problem of finding the minimal exposure paths in MWSNs (hereinafter MMEP). First, we formulate the MMEP problem. Then the MMEP problem is converted into a numerical functional extreme problem with high dimensionality, non-differentiation and non-linearity. To efficiently cope with these characteristics, we propose HPSO-MMEP algorithm, which is an integration of genetic algorithm into particle swarm optimization. Besides, we also create a variety of custom-made topologies of MWSNs for experimental simulations. The experimental results indicate that HPSO-MMEP is suitable for the converted MMEP problem and performs much better than existing algorithms. Full article

(This article belongs to the Special Issue Deployment and Control of Wireless Sensor Networks)

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32 pages, 5881 KiB

Open AccessArticle

A Path-Length Efficient, Low-Overhead, Load-Balanced Routing Protocol for Maximum Network Lifetime in Wireless Sensor Networks with Holes

by Phi Le Nguyen, Thanh Hung Nguyen and Kien Nguyen

Sensors 2020, 20(9), 2506; https://doi.org/10.3390/s20092506 - 28 Apr 2020

Cited by 10 | Viewed by 2474

Abstract

In wireless sensor networks (WSNs) with holes, designing efficient routing protocols, which prolong the network lifetime, is one of the most critical issues. To this end, this paper proposes a new geographic routing protocol for WSNs named the load Balanced and constant Stretch protocol for bypassing Multiple Holes (i.e., BSMH). In contrast to the existing works in the literature, the design of BSMH simultaneously takes into account the three factors that impacted the network lifetime, including routing path length, control packet overhead, and load balance among the nodes. Moreover, BSMH aims at minimizing the routing path length and the control overhead, while maximizing the load balance. We theoretically prove the efficiency of BSMH and extensively evaluate BSMH against the state-of-the-art protocols. The evaluation results show that the proposed protocol outperforms the others in various investigated metrics, not only network lifetime, but also routing path stretch, load balance, and control overhead. Specifically, BSMH prolongs the network lifetime by

30 %

compared to the existing protocols while guaranteeing that the routing path stretch is under

1.3

. Full article

(This article belongs to the Special Issue Deployment and Control of Wireless Sensor Networks)

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17 pages, 447 KiB

Open AccessArticle

An Effective Sensor Deployment Scheme that Ensures Multilevel Coverage of Wireless Sensor Networks with Uncertain Properties

by Yu-Ning Chen, Wu-Hsiung Lin and Chiuyuan Chen

Sensors 2020, 20(7), 1831; https://doi.org/10.3390/s20071831 - 25 Mar 2020

Cited by 9 | Viewed by 2304

Abstract

The coverage problem is a fundamental problem for almost all applications in wireless sensor networks (WSNs). Many applications even impose the requirement of multilevel (k) coverage of the region of interest (ROI). In this paper, we consider WSNs with uncertain properties. More precisely, we consider WSNs under the probabilistic sensing model, in which the detection probability of a sensor node decays as the distance between the target and the sensor node increases. The difficulty we encountered is that there is no unified definition of k-coverage under the probabilistic sensing model. We overcome this difficulty by proposing a “reasonable” definition of k-coverage under such a model. We propose a sensor deployment scheme that uses less number of deployed sensor nodes while ensuring good coverage qualities so that (i) the resultant WSN is connected and (ii) the detection probability satisfies a predefined threshold

p_{th}

, where

0 < p_{th} < 1

. Our scheme uses a novel “zone 1 and zone 1–2” strategy, where zone 1 and zone 2 are a sensor node’s sensing regions that have the highest and the second highest detection probability, respectively, and zone 1–2 is the union of zones 1 and 2. The experimental results demonstrate the effectiveness of our scheme. Full article

(This article belongs to the Special Issue Deployment and Control of Wireless Sensor Networks)

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