Review of nature-inspired methods for wake-up scheduling in wireless sensor networks

Musilek, Petr; Krömer, Pavel; Bartoň, Tomáŝ

doi:10.1016/j.swevo.2015.07.007

Cited by 30 publications

(11 citation statements)

References 133 publications

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“…A review of evolutionary algorithm (EA)-based sleep scheduling protocols is given in [12]. The authors highlight the main reasons behind adopting EA in sleep scheduling protocols.…”

Section: A Related Reviewsmentioning

confidence: 99%

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Coverage protocols for wireless sensor networks: Review and future directions

2019

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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. coverageaware 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.

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“…A review of evolutionary algorithm (EA)-based sleep scheduling protocols is given in [12]. The authors highlight the main reasons behind adopting EA in sleep scheduling protocols.…”

Section: A Related Reviewsmentioning

confidence: 99%

“…Furthermore, most of the coverage problems were defined as NP-hard optimization problems [5] [15]. EAs have been used to solve such problems [12] [13] [16] [17].…”

Section: A3 Algorithm Characteristicsmentioning

confidence: 99%

Coverage protocols for wireless sensor networks: Review and future directions

2019

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“…Distinctive planning calculation for the WSN have been secured by the creator of [17] while the directing conduct has been portrayed here. Majumder et.al.…”

Section: Related Workmentioning

confidence: 99%

A survey on natural computing techniques

2017

IJLTET

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“…During the last decade many nature-inspired approaches addressing similar problems have been published [11]. Among them are genetic algorithms [12], multi-objective genetic algorithm [9], evolution strategies [7], memetic algorithm [14], Figure 1: An example of sensor network deployed over the target field particle-swarm optimization [1], differential evolution [16], etc.…”

Section: State Of the Artmentioning

confidence: 99%

Heuristic and Meta-Heuristic Approaches for Energy-Efficient Coverage-Preserving Protocols in Wireless Sensor Networks

Tretyakova

Seredyński

Guinand

2017

Proceedings of the 13th ACM Symposium on QoS and Security for Wireless and Mobile Networks

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Monitoring some sites using a wireless sensor network (WSN) may be hampered by the difficulty of recharging or renewing the batteries of the sensing devices. Mechanisms aiming at improving the energy usage at any moment while fulfilling the application requirements are thus key for maximizing the lifetime of such networks. Among the different methods for achieving such a goal, we focus on energy management methods based on duty-cycling allowing the sensors to switch between two modes: a high-energy mode (active) and a lowenergy mode (sleep). In this paper we propose two new scheduling heuristics for addressing the problem of maximizing the lifetime of a WSN under the constraint of coverage of a subset of fixed targets. The first one is a stochastic greedy algorithm and the second one is based on applying Simulated Annealing (SA). Both heuristics use a specific knowledge about the problem. Experimental results show that while both algorithms perform well, greedy algorithm is preferable for small and medium sizes networks, and SA algorithm has competitive advantages for larger networks.

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Review of nature-inspired methods for wake-up scheduling in wireless sensor networks

Cited by 30 publications

References 133 publications

Coverage protocols for wireless sensor networks: Review and future directions

Coverage protocols for wireless sensor networks: Review and future directions

A survey on natural computing techniques

Heuristic and Meta-Heuristic Approaches for Energy-Efficient Coverage-Preserving Protocols in Wireless Sensor Networks

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