Integrated coverage and connectivity configuration in wireless sensor networks

Wang, Xiaorui; Xing, Guoliang; Zhang, Yuanfang; Lu, Chenyang; Pless, Robert; Gill, Christopher

doi:10.1145/958491.958496

Cited by 994 publications

(473 citation statements)

References 10 publications

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“…When R cmax ≥2R s , 1-coverage implies connectivity, as proved in Zhang and Hou (2005) and Wang et al (2003). However, R cmax ≥2R s may not hold.…”

Section: Connectivity Condition Of R Sgmentioning

confidence: 89%

“…Many location-based coverage configuration algorithms, such as in Tian and Georganas (2002) and Wang et al (2003), share a common coverage preserving principle in terms of sensing area (SA), i.e., if sensor A's sensing area (SA) is completely covered (1-covered or K s -covered) by other active sensors, sensor A can turn off. We call such principle SA Principle.…”

Section: Coveragementioning

confidence: 99%

“…Although no existing location-free algorithm can deal with coverage and connectivity simultaneously in a general way, Zhang and Hou (2005) and Wang et al (2003) have proved that when R cmax ≥2R s , coverage implies connectivity. Therefore, if R cmax ≥2R s , a node scheduling algorithm need only consider the coverage issue.…”

Section: Comparison With Existing Workmentioning

confidence: 99%

“…Yan et al (2003) proposed a reference time based node scheduling algorithm, which can deal with heterogeneous sensors with different sensing radii. Wang et al (2003) and Zhang and Hou (2005) consider the coverage as well as the connectivity of WSN. They have proved that if the communication range is at least twice the sensing range, a complete coverage of a convex area implies network connectivity.…”

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confidence: 99%

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A Location-free Algorithm of Energy-Efficient Connected Coverage for High Density Wireless Sensor Networks

Bai

Chen

et al. 2007

Discrete Event Dyn Syst

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One of the most serious concerns for wireless sensor networks (WSN) is energy. To obtain long lifetime, one potential method is deploying redundant sensors in the WSN and let each sensor switch its state between ACTIVE and OFF. At the same time, the WSN should meet various requirements of quality of service (QoS). This paper focuses on two important measurements of OoS: sensing coverage and network connectivity. Existing researches have provided many algorithms to schedule the nodes' states for coverage preserving, including location-free ones. Our work differs from existing location-free algorithms in several key ways: (1). We propose a novel principle on coverage preserving that is suitable for location-free schemes; (2). Following the principle, a distributed, localized and location-free node scheduling algorithm, Stand Guard Algorithm (StanGA), is proposed for treating coverage and connectivity in a unified scheme. Under certain conditions, StanGA can guarantee network connectivity and any degree of sensing coverage. Simulation results show that StanGA is scalable and robust, and also show that StanGA outperforms existing location-free algorithms even when only coverage issue is considered.

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“…When R cmax ≥2R s , 1-coverage implies connectivity, as proved in Zhang and Hou (2005) and Wang et al (2003). However, R cmax ≥2R s may not hold.…”

Section: Connectivity Condition Of R Sgmentioning

confidence: 89%

Section: Coveragementioning

confidence: 99%

Section: Comparison With Existing Workmentioning

confidence: 99%

mentioning

confidence: 99%

See 2 more Smart Citations

A Location-free Algorithm of Energy-Efficient Connected Coverage for High Density Wireless Sensor Networks

Bai

Chen

et al. 2007

Discrete Event Dyn Syst

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“…They proved that as long as the perimeter of the sensors are sufficiently covered, the whole area is sufficiently covered. In [15], Wang et al studied the relationship between coverage and connectivity. They proved that if a region is k-covered then the sensor network is k-connected as long as the communication range is at least twice of the sensing range.…”

Section: Related Workmentioning

confidence: 99%

Radar placement along banks of river

Zhang

2011

J Glob Optim

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In this paper, we consider the Radar Placement and Power Assignment problem (RPPA) along a river. In this problem, a set of crucial points in the river are required to be monitored by a set of radars which are placed along the two banks. The goal is to choose the locations for the radars and assign powers to them such that all the crucial points are monitored and the total power is minimized. If each crucial point is required to be monitored by at least k radars, the problem is a k-Coverage RPPA problem (k-CRPPA). Under the assumption that the river is sufficiently smooth, one may focus on the RPPA problem along a strip (RPPAS). In this paper, we present an O(n 9 ) dynamic programming algorithm for the RPPAS, where n is the number of crucial points to be monitored. In the special case where radars are placed only along the upper bank, we present an O(kn 5 ) dynamic programming algorithm for the k-CRPPAS. For the special case that the power is linearly dependent on the radius, we present an O(n log n)-time 2 √ 2-approximation algorithm for the RPPAS.

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Energy‐Efficient Backbone Construction, Broadcasting, and Area Coverage in Sensor Networks

Simplot‐Ryl

Stojmenović

2005

Handbook of Sensor Networks

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A backbone is a subset of sensors that is sufficient for performing assigned tasks. The exact definition depends on the task or the particular desirable properties of a backbone. We discuss two specific kinds of backbones, neighbor and area dominating sets, that we believe are the essential and perhaps only backbones required for sensor networks. A sensor is covered by a backbone if it is in the backbone or is a neighbor to a sensor in the backbone. This type of backbone is referred to here as neighbor-dominating sets, or simply dominating sets. A point within a monitoring area is covered by a sensor backbone if it is within sensing range of at least one sensor from the backbone. This type of backbone is called area-dominating set. In a broadcasting (also known as data-dissemination) task, a message is sent from one node, which could be a monitoring center, to all nodes in the network. Sensors, which are randomly placed in an area, decide which of them should be active and monitor an area, and which of them may sleep and become active at a later time. The communication connectivity is important so that the measured data can be reported to a monitoring center. This problem is known as the sensor-area coverage problem, and needs to be solved efficiently to enable sensor functioning for a prolonged time. Sensors may also be placed deterministically in an area to optimize coverage and reduce power consumption. Most solutions considered in this chapter are based Handbook of Sensor Networks: Algorithms and Architectures, Edited by I. Stojmenovic ÍSBN 0-471-68472-4

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Integrated coverage and connectivity configuration in wireless sensor networks

Cited by 994 publications

References 10 publications

A Location-free Algorithm of Energy-Efficient Connected Coverage for High Density Wireless Sensor Networks

A Location-free Algorithm of Energy-Efficient Connected Coverage for High Density Wireless Sensor Networks

Radar placement along banks of river

Energy‐Efficient Backbone Construction, Broadcasting, and Area Coverage in Sensor Networks

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