Energy-efficient Area Coverage by Sensors with Adjustable Ranges

In wireless sensor networks, density control is an important technique for prolonging a network’s lifetime. To reduce the overall energy consumption, it is desirable to minimize the overlapping sensing area of the sensor nodes. In this paper, we study the problem of energy-efficient area coverage by the regular placement of sensors with adjustable sensing and communication ranges. We suggest a more accurate method to estimate efficiency than those currently used for coverage by sensors with adjustable ranges, and propose new density control models that considerably improve coverage using sensors with two sensing ranges. Calculations and extensive simulation show that the new models outperform existing ones in terms of various performance metrics

Movement-efficient Sensor Deployment in Wireless Sensor Networks

We study a mobile wireless sensor network (MWSN) consisting of multiple mobile sensors or robots. Two key issues in MWSNs - energy consumption, which is dominated by sensor movement, and sensing coverage - have attracted plenty of attention, but the interaction of these issues is not well studied. To take both sensing coverage and movement energy consumption into consideration, we model the sensor deployment problem as a constrained source coding problem. %, which can be applied to different coverage tasks, such as area coverage, target coverage, and barrier coverage. Our goal is to find an optimal sensor deployment to maximize the sensing coverage with specific energy constraints. We derive necessary conditions to the optimal sensor deployment with (i) total energy constraint and (ii) network lifetime constraint. Using these necessary conditions, we design Lloyd-like algorithms to provide a trade-off between sensing coverage and energy consumption. Simulation results show that our algorithms outperform the existing relocation algorithms.Comment: 18 pages, 10 figure

Set It and Forget It: Approximating the Set Once Strip Cover Problem

We consider the Set Once Strip Cover problem, in which n wireless sensors are deployed over a one-dimensional region. Each sensor has a fixed battery that drains in inverse proportion to a radius that can be set just once, but activated at any time. The problem is to find an assignment of radii and activation times that maximizes the length of time during which the entire region is covered. We show that this problem is NP-hard. Second, we show that RoundRobin, the algorithm in which the sensors simply take turns covering the entire region, has a tight approximation guarantee of 3/2 in both Set Once Strip Cover and the more general Strip Cover problem, in which each radius may be set finitely-many times. Moreover, we show that the more general class of duty cycle algorithms, in which groups of sensors take turns covering the entire region, can do no better. Finally, we give an optimal O(n^2 log n)-time algorithm for the related Set Radius Strip Cover problem, in which all sensors must be activated immediately.Comment: briefly announced at SPAA 201

Distributed Algorithms for Improving Wireless Sensor Network Lifetime with Adjustable Sensing Range

Wireless sensor networks are made up of a large number of sensors deployed randomly in an ad-hoc manner in the area/target to be monitored. Due to their weight and size limitations, the energy conservation is the most critical issue. Energy saving in a wireless sensor network can be achieved by scheduling a subset of sensor nodes to activate and allowing others to go into low power sleep mode, or adjusting the transmission or sensing range of wireless sensor nodes. In this thesis, we focus on improving the lifetime of wireless sensor networks using both smart scheduling and adjusting sensing ranges. Firstly, we conduct a survey on existing works in literature and then we define the sensor network lifetime problem with range assignment. We then propose two completely localized and distributed scheduling algorithms with adjustable sensing range. These algorithms are the enhancement of distributed algorithms for fixed sensing range proposed in the literature. The simulation results show that there is almost 20 percent improvement of network lifetime when compare with the previous approaches

Distributed Algorithms for Maximizing the Lifetime of Wireless Sensor Networks

Wireless sensor networks (WSNs) are emerging as a key enabling technology for applications domains such as military, homeland security, and environment. However, a major constraint of these sensors is their limited battery. In this dissertation we examine the problem of maximizing the duration of time for which the network meets its coverage objective. Since these networks are very dense, only a subset of sensors need to be in sense or on mode at any given time to meet the coverage objective, while others can go into a power conserving sleep mode. This active set of sensors is known as a cover. The lifetime of the network can be extended by shuffling the cover set over time. In this dissertation, we introduce the concept of a local lifetime dependency graph consisting of the cover sets as nodes with any two nodes connected if the corresponding covers intersect, to capture the interdependencies among the covers. We present heuristics based on some simple properties of this graph and show how they improve over existing algorithms. We also present heuristics based on other properties of this graph, new models for dealing with the solution space and a generalization of our approach to other graph problems

On perimeter coverage in wireless sensor networks with minimum cost

One of the major applications of sensor networks is tracking and surveillance. Very often, a single sensor is sufficient to monitor a single target. However, when the object is very large, several sensors have to work together to monitor the object continuously. In this paper, we study how to identify a set of sensors that can cover the perimeter of a large target with the minimum cost. We develop a novel distributed algorithm that requires fewer messages than existing mechanisms. Our algorithm can be extended to solve the problem when the sensor range is adjustable. We provide a formal proof of correctness and convergence time analysis of our algorithm. We further demonstrate the performance through extensive simulations. © 2011 Inderscience Enterprises Ltd.postprin

Average Case Network Lifetime on an Interval with Adjustable Sensing Ranges

Given n sensors on an interval, each of which is equipped with an adjustable sensing radius and a unit battery charge that drains in inverse linear proportion to its radius, what schedule will maximize the lifetime of a network that covers the entire interval? Trivially, any reasonable algorithm is at least a 2-approximation for this Sensor Strip Cover problem, so we focus on developing an efficient algorithm that maximizes the expected network lifetime under a random uniform model of sensor distribution. We demonstrate one such algorithm that achieves an expected network lifetime within 12 % of the theoretical maximum. Most of the algorithms that we consider come from a particular family of RoundRobin coverage, in which sensors take turns covering predefined areas until their battery runs out