Energy-Efficient \u3cem\u3ek\u3c/em\u3e-Coverage for Wireless Sensor Networks with Variable Sensing Radii

Wireless Sensor Networks (WSNs) consist of spatially-distributed autonomous sensors that can cooperatively monitor physical and environmental conditions. Because of sensors’ resource-constraints in terms of size, power, and bandwidth, one of the fundamental objectives in WSNs is improving energy-efficiency. In this paper, utilizing sensors with variable sensing radii, we propose a group-based technique to obtain energy-efficient k-coverage based on our previous work with the Delaunay-Triangulation-based 1-coverage algorithm. Our sensing-radii optimization technique ensures full coverage and attains nearly-optimal energy consumption in sensing. Furthermore, our ns-2 simulations confirm that the group-based k-coverage reduces sensing energy consumption and maintains a sound coverage ratio for reliable surveillance

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

An Energy-Efficient Distributed Algorithm for k-Coverage Problem in Wireless Sensor Networks

Wireless sensor networks (WSNs) have recently achieved a great deal of attention due to its numerous attractive applications in many different fields. Sensors and WSNs possesses a number of special characteristics that make them very promising in many applications, but also put on them lots of constraints that make issues in sensor network particularly difficult. These issues may include topology control, routing, coverage, security, and data management. In this thesis, we focus our attention on the coverage problem. Firstly, we define the Sensor Energy-efficient Scheduling for k-coverage (SESK) problem. We then solve it by proposing a novel, completely localized and distributed scheduling approach, naming Distributed Energy-efficient Scheduling for k-coverage (DESK) such that the energy consumption among all the sensors is balanced, and the network lifetime is maximized while still satisfying the k-coverage requirement. Finally, in related work section we conduct an extensive survey of the existing work in literature that focuses on with the coverage problem

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

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

COVERAGE PROBLEM IN HETEROGENEOUS WIRELESS SENSOR NETWORKS

A heterogeneous wireless sensor network consists of different types of nodes in sequence. Some of these nodes have high process powers and significant energy, which are called the manager nodes or super-nodes. The second type nodes, which have normal process power, are only used as monitoring nodes or act as relay nodes in the path to the manager nodes are called the normal nodes. In this paper, an energy-aware algorithm is presented for the optimum selection of sensor and relay groups that are used for monitoring and sending messages from goals in point coverage, using the competition between the nodes. This algorithm is effective in decreasing the energy consumption of the network and increasing its life-time. Moreover, providing that no node saves the information about the routing table and relay nodes; therefore, it will have less complexity and overload

Perimeter coverage scheduling in wireless sensor networks using sensors with a single continuous cover range

In target monitoring problem, it is generally assumed that the whole target object can be monitored by a single sensor if the target falls within its sensing range. Unfortunately, this assumption becomes invalid when the target object is very large that a sensor can only monitor part of it. In this paper, we study the perimeter coverage problem where the perimeter of a big object needs to be monitored, but each sensor can only cover a single continuous portion of the perimeter. We describe how to schedule the sensors so as to maximize the network lifetime in this problem. We formally prove that the perimeter coverage scheduling problem is NP-hard in general. However, polynomial time solution exists in some special cases. We further identify the sufficient conditions for a scheduling algorithm to be a 2-approximation solution to the general problem, and propose a simple distributed 2-approximation solution with a small message overhead. Copyright © 2010 K.-S. Hung and K.-S. Lui.published_or_final_versio