Wireless Sensor Network Configuration—Part II: Adaptive Coverage for Decentralized Algorithms

Derr, Kurt; Manic, Milos

doi:10.1109/tii.2013.2245907

Cited by 28 publications

(18 citation statements)

References 22 publications

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“…As discussed in Section III-A, the position of a γ-agent is calculated based on the information map using Eqs. (9) and (10). One can identify that there are three parameters, σ 2 , σ 1 , and ρ, which govern the position of the γ-agent.…”

Section: A Parameter Estimationmentioning

confidence: 99%

“…Their first algorithm is based on a centralized approach which is capable of generating mesh network configurations to achieve 100% area coverage [8]. In their second algorithm, a decentralized approached was proposed to achieve adaptive coverage in mesh networks by dynamically adjusting the sensing range of the sensor nodes [9]. Mahboubi et al proposed several algorithms based on Voronoi diagrams for improving sensor network coverage [10], [11].…”

Section: Introductionmentioning

confidence: 99%

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Distributed Antiflocking Algorithms for Dynamic Coverage of Mobile Sensor Networks

Ganganath

Cheng

Tse

2016

IEEE Trans. Ind. Inf.

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Abstract-Mobile sensor networks (MSNs) are often used for monitoring large areas of interest (AoI) in remote and hostile environments which can be highly dynamic in nature. Due to the infrastructure cost, MSNs usually consist of limited number of sensor nodes. In order to cover large AoI, the mobile nodes have to move in an environment while monitoring the area dynamically. MSNs that are controlled by most of the previously proposed dynamic coverage algorithms either lack adaptability to dynamic environments or display poor coverage performances due to considerable overlapping of sensing coverage. As a new class of emergent motion control algorithms for MSNs, anti-flocking control algorithms enable MSNs to self-organize in an environment and provide impressive dynamic coverage performances. The anti-flocking algorithms are inspired by the solitary behavior of some animals who try to separate from their species in most of daily activities in order to maximize their own gains. In this paper, we propose two distributed anti-flocking algorithms for dynamic coverage of MSNs, one for obstacle free environments and the other one for obstacle dense environments. Both are based on the sensing history and local interactions among sensor nodes.

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Section: A Parameter Estimationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Distributed Antiflocking Algorithms for Dynamic Coverage of Mobile Sensor Networks

Ganganath

Cheng

Tse

2016

IEEE Trans. Ind. Inf.

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“…Besides, it arouses the research warmness for WSN technology. WSN works in poor environment in which sensor nodes are usually deployed in the monitoring region through random spreading [4,5]. Distribution of sensor nodes is very uneven.…”

Section: Introductionmentioning

confidence: 99%

“…Therefore, the overhead of node energy can be decreased and dynamic allocation can be achieved. (4) As to network energy, the targets in concern are always located in the sensing range of the working nodes by employing the dynamic allocation mechanism. The state transition of nodes can be finished through scheduling mechanism; thus the dynamic adjustment of nodes can be realized.…”

Section: Introductionmentioning

confidence: 99%

A novel coverage algorithm based on event-probability-driven mechanism in wireless sensor network

Sun

Wang

et al. 2014

J Wireless Com Network

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Coverage problem is an important research topic in the field of wireless sensor network (WSN). The coverage algorithm based on event probability driven mechanism (EPDM) is put forward in this paper. First of all, the network probability model is established and the subordinate relation between sensor nodes and the target nodes is presented. Secondly, a series of probability is computed and the related theorems and reasoning are also proven. Thirdly, effective coverage for the monitoring region is achieved through scheduling mechanism of nodes themselves, thus the purpose of increasing network lifetime can be realized. Finally, experimental results show that the proposed algorithm could achieve complete coverage for networks of different scale and increase the network lifetime. It possesses the good quality of effectiveness and stability.

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“…It is a system having the capabilities of calculating, perceiving, and communicating which can be widely applied in national defense monitoring, environment detecting, mine wrecking, medicine, traffic realms, and so forth. The coverage problem, the connectivity problem among nodes or between nodes and station, and the energy consuming problem of nodes are all hotspot issues of WSN [1][2][3][4]. The coverage and connectivity problem not only directly affects the working of network, but also determines network energy consuming, network life cycle length, and network quality of service.…”

Section: Introductionmentioning

confidence: 99%

An Optimized Strategy Coverage Control Algorithm for WSN

Sun

Wang

et al. 2014

International Journal of Distributed Sensor Networks

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The problem of using lesser wireless sensor network nodes to achieve coverage and connection of certain areas under given coverage conditions is a priority and hotspot issue of WSN. For this reason, in this paper, an optimized strategy coverage control (OSCC) algorithm is proposed. First of all, a relation mapping model of sensor nodes and target nodes is established by OSCC which is based on geometric figure and related theories, probability theory, converge property, and so forth to complete effective reasoning and calculate certain network models. Secondly, OSCC makes efficient analysis of the calculating results figure out the least number of sensor nodes to cover specific monitoring area. Thirdly, OSCC picks out the optimal routing solution while conducting combinatorial optimization of routing path using ant colony optimization (ACO) algorithm, thus reducing the energy spending of whole network. In the end, this paper verifies OSCC algorithm by simulation experiment and proves it can use least sensor nodes to effectively cover target area. Also, OSCC helps greatly reduce network energy consuming, minimize network resources layout costs, and enhance network life cycle, simultaneously.

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Wireless Sensor Network Configuration—Part II: Adaptive Coverage for Decentralized Algorithms

Cited by 28 publications

References 22 publications

Distributed Antiflocking Algorithms for Dynamic Coverage of Mobile Sensor Networks

Distributed Antiflocking Algorithms for Dynamic Coverage of Mobile Sensor Networks

A novel coverage algorithm based on event-probability-driven mechanism in wireless sensor network

An Optimized Strategy Coverage Control Algorithm for WSN

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