Deploying Directional Sensor Networks with Guaranteed Connectivity and Coverage

Han, Xiaofeng; Cao, Xiang; Lloyd, Errol L.; Shen, Chien-Chung

doi:10.1109/sahcn.2008.28

Cited by 101 publications

(54 citation statements)

References 19 publications

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“…Although all of the above-mentioned researches have achieved the coverage requirement, some of them have not considered the network lifetime [12,20,22,27] and the network connectivity [16,[21][22][23]. Some works such as [14,15,[17][18][19][20]24] require that the transmission range is at least twice the size of the sensing range; otherwise, the connectivity may not be guaranteed.…”

Section: Related Workmentioning

confidence: 99%

Multiobjective Optimization for Topology and Coverage Control in Wireless Sensor Networks

Jameii

Faez

Dehghan

2015

International Journal of Distributed Sensor Networks

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Coverage, connectivity, and network lifetime are important issues in wireless sensor networks (WSNs). Balancing the energy consumption in the network, reducing the transmission range of nodes, and density control of active nodes are approaches to extend the network lifetime. However, transmission range reduction and smaller number of active nodes can affect the network topology and may cause the network to be disconnected. So, there exist conflicts among lifetime, coverage, and connectivity. In this paper, these conflicting issues are considered and an evolutionary multiobjective optimization approach based on nondominated sorting genetic algorithm-II (NSGA-II) is proposed to optimize them. Simulation results demonstrate that the proposed algorithm can improve the network lifetime and coverage while maintaining the network connectivity.

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Section: Related Workmentioning

confidence: 99%

Multiobjective Optimization for Topology and Coverage Control in Wireless Sensor Networks

Jameii

Faez

Dehghan

2015

International Journal of Distributed Sensor Networks

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“…In [2], the authors detect an algorithm based on learning automata to detect minimum number of nodes to detect the barrier.…”

Section: Target Coveragementioning

confidence: 99%

The Issues of Coverage in Directional Sensor Network

Mishra¹,

Sharma²,

Saxena³

2015

IJCA

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The wireless sensor networks (WSNs) come into prominence because they have the capability of changing our economy and life. A very vast range of applications supported by WSNs has served the human society very effectively; and, monitoring has been proven the most attention drawing application among these. As a tributary of sensor networks, Directional sensor networks (DSNs) consist of several camera sensors where nodes cover only a fraction of surrounding defined by a specific angle called vertex angle at a time. As sensors are randomly deployed, their sensing direction may overlap with one another and hence coverage optimization has become the most popular area for research over the years. In this paper , the problem of coverage is surveyed on the basis of the solutions proposed, and hence, classified into three categories as (1) Target coverage (2) Maximal coverage (subset of area coverage ) and (3) Maximum coverage with minimum sensors (subset of target coverage). The impact of various parameters of directional sensor networks as: sensor's location, its working direction, number of orientations, FoVs on the performance of the deployed sensor network is analyzed. Maximum coverage with minimum sensors (subset of target coverage)

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“…Han et al [25] investigate problems related to connected coverage in directional sensor networks where sensors only sense directionally and have a sector-like sensing range. Deployment patterns are proposed such that the location points/area is covered and forms a connected network.…”

Section: Related Workmentioning

confidence: 99%

M-Connected Coverage Problem in Wireless Sensor Networks

Mini

Udgata

Sabat

2012

ISRN Sensor Networks

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Solving coverage problem alone is not adequate in a wireless sensor network, since data has to be transmitted to the base station. This leads to the lookout for an energy efficient method to solve connected coverage problem. This paper addresses M-connected (each sensor node will have at least M other sensor nodes within its communication range) target coverage problem in wireless sensor networks, where the required level of connectivity and coverage may be high or low as required. We propose a heuristic for M-connected target coverage problem, where initially a cover is decided and later on it is checked for M-connectivity. M-connectivity for simple coverage, k-coverage, and Q-coverage is focussed on in this paper. We use a Low-Energy Adaptive Clustering Hierarchy (LEACH) inspired model, where a cluster is considered as a set of sensor nodes satisfying M-connectivity and required level of coverage. It is enough if one among these nodes transmits the monitored information to the base station. When the required level of coverage are high, chances of nodes being connected in the cover is high. Simulation results show that our proposed method can achieve better results than Communication Weighted Greedy Cover (CWGC).

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Deploying Directional Sensor Networks with Guaranteed Connectivity and Coverage

Cited by 101 publications

References 19 publications

Multiobjective Optimization for Topology and Coverage Control in Wireless Sensor Networks

Multiobjective Optimization for Topology and Coverage Control in Wireless Sensor Networks

The Issues of Coverage in Directional Sensor Network

M-Connected Coverage Problem in Wireless Sensor Networks

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