Coverage problems in wireless sensor networks: designs and analysis

Thai, My T.; Wang, Feng; Du, David Hongwei; Jia, Xiaohua

doi:10.1504/ijsnet.2008.018482

Cited by 88 publications

(36 citation statements)

References 18 publications

(44 reference statements)

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“…The ACE clustering algorithm [18] partitions a network into uniformly dispersed clusters. Another clustering technique known as autonomous clustering and uses the coverage estimation parameter [19][20] [21].…”

Section: Memory Unitmentioning

confidence: 99%

Energy-Aware Fragmented Memory Architecture with a Switching Power Supply for Sensor Nodes

Kenchannavar¹,

Math²,

Kulkarni³

2013

IJACSA

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Abstract-The basic sensor node architecture in a wireless sensor network contains sensing, transceiver, processing and memory units along with the power supply module. Because the basic sensor network application nature is surveillance, these networks may be deployed in a remote environment without human intervention. The sensor nodes are also battery-powered tiny devices with limited memory capacity. Because of these sensor node limitations, the architecture can be modified to efficiently utilise energy during memory accesses by dividing the memory into multiple banks and including a memory switching controller unit and a power switching module. This modification conserves energy, so power can be supplied only to the bank or part of the memory being accessed instead of powering the entire memory module, thus leading to efficient energy consumption. Simulations have been performed on fragmented memory architecture by incorporating the M/M/1 queuing model. When the packets get queued up, energy utilisation and a packet drop at the sensor node is observed. The energy consumption is reduced by an average of 70%, and there is significantly less packet drop compared to the normal memory architecture. This leads to increase in node and network lifetime and prevents information loss.

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Section: Memory Unitmentioning

confidence: 99%

Energy-Aware Fragmented Memory Architecture with a Switching Power Supply for Sensor Nodes

Kenchannavar¹,

Math²,

Kulkarni³

2013

IJACSA

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“…We refer to the survey by Thai et al [16] for an overview. Berman et al [2,3] show that the region coverage problem can be reduced to the target coverage problem and present an algorithm with logarithmic approximation ratio.…”

Section: Related Workmentioning

confidence: 99%

Maximising lifetime for fault-tolerant target coverage in sensor networks

Erlebach

Grant

Kammer

2011

Proceedings of the Twenty-Third Annual ACM Symposium on Parallelism in Algorithms and Architectures

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We study the problem of maximising the lifetime of a sensor network for fault-tolerant target coverage in a setting with composite events. Here, a composite event is the simultaneous occurrence of a combination of atomic events, such as the detection of smoke and high temperature. We are given sensor nodes that have an initial battery level and can monitor certain event types, and a set of points at which composite events need to be detected. The points and sensor nodes are located in the Euclidean plane, and all nodes have the same sensing radius. The goal is to compute a longest activity schedule with the property that at any point in time, each event point is monitored by at least two active sensor nodes. We present a (6 + ε)-approximation algorithm for this problem by devising an approximation algorithm with the same ratio for the dual problem of minimising the weight of a fault-tolerant sensor cover and applying the Garg-Könemann algorithm. Our algorithm for the minimum-weight fault-tolerant sensor cover problem generalises previous approximation algorithms for geometric set cover with weighted unit disks and is obtained by enumerating properties of the optimal solution that guide a dynamic programming approach.

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“…Relation between area and target coverage colouring technique is used. As depicted in (Thai et al, 2008), despite the production of more sets than the ones achieved in the proposal of (Slijepcevic & Potkonjak, 2001), the dominating sets do not guarantee the coverage of the whole area. The complexity of the heuristic which computes the disjoint sets from the coloured graph is O(n 3 ).…”

Section: Disjoint Approachesmentioning

confidence: 99%