Metaheuristics for the Lifetime of WSN: A Review

Tsai, Chun-Wei; Hong, Tzung-Pei; Shiu, Guo-Neng

doi:10.1109/jsen.2016.2523061

Cited by 76 publications

(39 citation statements)

References 83 publications

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“…These are in the small dimensions and communicate with short distances and these low cost, smart sensor are networked through the wireless links. Then it is deployed in the huge quantities to provide the precedented opportunities for observing and controlling sensors along with the environment and the networked sensors are used in the broad spectrum for the applications with the defense area and generating a new capability for the surveillance of various applications [2][3][4]. Self-localization is the capability that can be a greatly desirable sign for the wireless sensor networks.…”

Section: Introductionmentioning

confidence: 99%

Intrusion Detection Algorithm for Packet Loss Minimization in Wireless Sensor Networks

Rizwana,

K M,

2019

IJEAT

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Wireless Sensor Network consists of a greater number of sensor nodes and recent advance is in wireless communications and it serves a backbone for controlling the real time applications. It consists of group of sensor nodes and that is sense the information from the event area and it is passes through the base station and which it reacts according to environment and to provide a large-scale monitoring and sensor measurement in a high temporal and the spatial resolution. The researcher uses a different algorithm in that they use a distributed energy fuzzy logic to reduce a packet loss. Wireless Sensor Networks are unprotected to many kinds of the security threats which can decrease the performance of network and cause the sensors to send wrong data to destination. The hostile node in the network is working as an attacker node and it takes all the information packets which is delivered through them. In this paper we propose an intrusion detection system algorithm against the packet dropping. Intrusion detection algorithm solves the problem by analyzing the network by detecting the abnormal node. Then the abnormal node is corrected into normal node with the help of intrusion detection algorithm.

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Section: Introductionmentioning

confidence: 99%

Intrusion Detection Algorithm for Packet Loss Minimization in Wireless Sensor Networks

Rizwana,

K M,

2019

IJEAT

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“…The lifetime of a WSN (the time during which it senses the region of interest under some coverage constraint) is a key performance indicator to determine its efficiency. Energy consumption must be restricted to achieve the maximum operating time of WSN because battery-powered sensors are difficult to recharge or replace [1][2][3][4][5].…”

Section: Introductionmentioning

confidence: 99%

A Novel Random Scheduling Algorithm based on Subregions Coverage for SET K-Cover Problem in Wireless Sensor Networks

Muhammad¹,

Roy²,

Ahn³

et al. 2018

KSII TIIS

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This paper proposes a novel Random Scheduling Algorithm based on Subregion Coverage (RSASC), to solve the SET K-cover problem (an NP-complete problem). SET K-cover problem distributes the set of sensors into the maximum number of mutually exclusive subsets (MESSs) in such a way that each of them can be scheduled for lifetime extension of WSN. Sensor coverage divides the target region into different subregions. RSASC first sorts the subregions in the ascending order concerning their sensor coverage. Then, it forms the subregion groups according to their similar sensor coverage. Lastly, RSASC ensures the K-coverage of each subregion from every group by randomly scheduling the sensors. We consider the target-coverage and area-coverage applications of WSN to analyze the usefulness of our proposed RSASC algorithm. The distinct quality of RSASC is that it utilizes less number of deployed sensors (33% less) to form the optimum number of MESSs with the higher computational speed (saves more than 93% of the time) as compared to the existing three algorithms.

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“…Solar and wind energies can be an alternative but they are unreliable. Energy-constrained IoT-based-WSNs are much more challenging on energy conservation than any other kind of networks [5][6][7][8][9][10]. To increase the networks lifetime while achieving the optimal coverage is a hot research topic in IoTbased-WSNs.…”

Section: Introductionmentioning

confidence: 99%

“…SDs in the sleeping state can be brought into active state for working in their scheduled durations. If a subset of SDs already gives full coverage of region of interest, other subsets can be sent into sleep state in order to save the energy [5,9,10].…”

Section: Introductionmentioning

confidence: 99%

Hybrid Artificial Bee Colony Algorithm for an Energy Efficient Internet of Things based on Wireless Sensor Network

Muhammad

Saxena

Qureshi

et al. 2017

IETE Technical Review

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Latest technologies, for example, the Internet of Things (IoT), smart applications, smart grids and machine-to-machine networks, inspired the organization for self-sufficient large-scale wireless sensor networks (IoT-based-WSNs). Many IoT devices are powered by batteries with limited lifetime and deployed in remote areas. Thus in some situation, limited battery restricts the network lifetime. Scheduling is an effective approach for an energy efficient IoT-based-WSNs by categorizing the smart devices into an optimal number of disjoint subsets which completely cover all objects in the monitored area. Scheduling is an effective approach for an energy efficient IoT-based-WSNs by categorizing the smart devices into an optimal number of disjoint subsets which completely cover all objects in the monitored area. Finding the maximum number of such disjoint subsets is nondeterministic polynomial-complete. This paper proposes a hybrid artificial bee colony algorithm with an efficient schedule transformation, termed as HABCA-EST, to solve above problem. The unique feature of HABCA-EST is the rapid growth in the fitness function due to complete utilization of excessive information among the scheduled devices. The swarm and EST operations in HABCA-EST work together to efficiently search an optimal solution in less running time. We consider an application of sensing different objects in the monitored area, termed as target-coverage, to analyse the effectiveness of HABCA-EST. Results show that HABCA-EST takes less number of fitness evaluations (up to 10%) and schedules less number of smart devices (up to 94%) which leads to a reduction (93%) in simulation time as compared to the existing techniques.

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Metaheuristics for the Lifetime of WSN: A Review

Cited by 76 publications

References 83 publications

Intrusion Detection Algorithm for Packet Loss Minimization in Wireless Sensor Networks

Intrusion Detection Algorithm for Packet Loss Minimization in Wireless Sensor Networks

A Novel Random Scheduling Algorithm based on Subregions Coverage for SET K-Cover Problem in Wireless Sensor Networks

Hybrid Artificial Bee Colony Algorithm for an Energy Efficient Internet of Things based on Wireless Sensor Network

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