1,503 research outputs found
Coverage Protocols for Wireless Sensor Networks: Review and Future Directions
The coverage problem in wireless sensor networks (WSNs) can be generally
defined as a measure of how effectively a network field is monitored by its
sensor nodes. This problem has attracted a lot of interest over the years and
as a result, many coverage protocols were proposed. In this survey, we first
propose a taxonomy for classifying coverage protocols in WSNs. Then, we
classify the coverage protocols into three categories (i.e. coverage aware
deployment protocols, sleep scheduling protocols for flat networks, and
cluster-based sleep scheduling protocols) based on the network stage where the
coverage is optimized. For each category, relevant protocols are thoroughly
reviewed and classified based on the adopted coverage techniques. Finally, we
discuss open issues (and recommend future directions to resolve them)
associated with the design of realistic coverage protocols. Issues such as
realistic sensing models, realistic energy consumption models, realistic
connectivity models and sensor localization are covered
The Deployment in the Wireless Sensor Networks: Methodologies, Recent Works and Applications
International audienceThe wireless sensor networks (WSN) is a research area in continuous evolution with a variety of application contexts. Wireless sensor networks pose many optimization problems, particularly because sensors have limited capacity in terms of energy, processing and memory. The deployment of sensor nodes is a critical phase that significantly affects the functioning and performance of the network. Often, the sensors constituting the network cannot be accurately positioned, and are scattered erratically. To compensate the randomness character of their placement, a large number of sensors is typically deployed, which also helps to increase the fault tolerance of the network. In this paper, we are interested in studying the positioning and placement of sensor nodes in a WSN. First, we introduce the problem of deployment and then we present the latest research works about the different proposed methods to solve this problem. Finally, we mention some similar issues related to the deployment and some of its interesting applications
A Comprehensive Survey on Particle Swarm Optimization Algorithm and Its Applications
Particle swarm optimization (PSO) is a heuristic global optimization method, proposed originally by Kennedy and Eberhart in 1995. It is now one of the most commonly used optimization techniques. This survey presented a comprehensive investigation of PSO. On one hand, we provided advances with PSO, including its modifications (including quantum-behaved PSO, bare-bones PSO, chaotic PSO, and fuzzy PSO), population topology (as fully connected, von Neumann, ring, star, random, etc.), hybridization (with genetic algorithm, simulated annealing, Tabu search, artificial immune system, ant colony algorithm, artificial bee colony, differential evolution, harmonic search, and biogeography-based optimization), extensions (to multiobjective, constrained, discrete, and binary optimization), theoretical analysis (parameter selection and tuning, and convergence analysis), and parallel implementation (in multicore, multiprocessor, GPU, and cloud computing forms). On the other hand, we offered a survey on applications of PSO to the following eight fields: electrical and electronic engineering, automation control systems, communication theory, operations research, mechanical engineering, fuel and energy, medicine, chemistry, and biology. It is hoped that this survey would be beneficial for the researchers studying PSO algorithms
A Survey on the Application of Evolutionary Algorithms for Mobile Multihop Ad Hoc Network Optimization Problems
Evolutionary algorithms are metaheuristic algorithms that provide quasioptimal solutions in a reasonable time. They have been
applied to many optimization problems in a high number of scientific areas. In this survey paper, we focus on the application of
evolutionary algorithms to solve optimization problems related to a type of complex network likemobilemultihop ad hoc networks.
Since its origin, mobile multihop ad hoc network has evolved causing new types of multihop networks to appear such as vehicular
ad hoc networks and delay tolerant networks, leading to the solution of new issues and optimization problems. In this survey, we
review the main work presented for each type of mobile multihop ad hoc network and we also present some innovative ideas and
open challenges to guide further research in this topic
Contribution au déploiement optimisé des réseaux de capteurs sans fil
National audienceLes réseaux de capteurs sans fil (RCSF) sont un domaine de recherche en évolution continue avec une multitude de contextes d'application. Le déploiement des noeuds capteurs est une phase décisive qui influe considérablement sur le fonctionnement et la performance du réseau. Dans ce papier, nous nous intéressons à étudier le positionnement et le placement des noeuds capteurs dans un RCSF. Nous présentons tout d'abord la problématique de déploiement et nous détaillons ensuite les travaux de recherche les plus récents qui concernent les méthodologies de résolution de cette problématique
Joint optimization for wireless sensor networks in critical infrastructures
Energy optimization represents one of the main goals in wireless sensor network design
where a typical sensor node has usually operated by making use of the battery with
limited-capacity. In this thesis, the following main problems are addressed: first, the
joint optimization of the energy consumption and the delay for conventional wireless sensor networks is presented. Second, the joint optimization of the information quality and
energy consumption of the wireless sensor networks based structural health monitoring
is outlined. Finally, the multi-objectives optimization of the former problem under several constraints is shown. In the first main problem, the following points are presented:
we introduce a joint multi-objective optimization formulation for both energy and delay
for most sensor nodes in various applications. Then, we present the Karush-Kuhn-Tucker
analysis to demonstrate the optimal solution for each formulation. We introduce a method
of determining the knee on the Pareto front curve, which meets the network designer interest for focusing on more practical solutions. The sensor node placement optimization has
a significant role in wireless sensor networks, especially in structural health monitoring.
In the second main problem of this work, the existing work optimizes the node placement
and routing separately (by performing routing after carrying out the node placement).
However, this approach does not guarantee the optimality of the overall solution. A joint
optimization of sensor placement, routing, and flow assignment is introduced and is solved
using mixed-integer programming modelling. In the third main problem of this study, we
revisit the placement problem in wireless sensor networks of structural health monitoring by using multi-objective optimization. Furthermore, we take into consideration more
constraints that were not taken into account before. This includes the maximum capacity
per link and the node-disjoint routing. Since maximum capacity constraint is essential
to study the data delivery over limited-capacity wireless links, node-disjoint routing is
necessary to achieve load balancing and longer wireless sensor networks lifetime. We list
the results of the previous problems, and then we evaluate the corresponding results
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