Sleep scheduling for energy conservation in wireless sensor networks with partial coverage

Cataloged from PDF version of article.Wireless sensor networks, which consist of many sensor devices communicating with each other in order to sense the environment, is an emerging field in the area of wireless networking. The primary objective in these wireless networks is the efficiency of energy consumption. Since these networks consist of a large number of sensors, allowing some of the nodes to sleep intermittently can greatly increase the network lifetime. Furthermore, some applications do not require 100% coverage of the network field and allowing the coverage to drop below 100%, i.e., partial coverage, can further increase the network lifetime. A sleep scheduling algorithm must be distributed, simple, scalable and energy efficient. In this thesis, the problem of designing such an algorithm which extends network lifetime while maintaining a target level of partial coverage is investigated. An algorithm called Distributed Adaptive Sleep Scheduling Algorithm (DASSA) which does not require location information is proposed. The performance of DASSA is compared with an integer linear programming (ILP) based optimum sleep scheduling algorithm, an oblivious algorithm and with an existing algorithm in the literature. DASSA attains network lifetimes up to 89% of the optimum solution, and it achieves significantly longer lifetimes compared with the other two algorithms. Furthermore, the minimum number of sensors that should be deployed in order to satisfy a given partial coverage target with a certain probability while maintaining connectivity is computed and an ILP formulation is presented for finding the minimum number of sensors that should be activated within the set of deployed sensors.Yardibi, TarıkM.S

A Coverage Monitoring algorithm based on Learning Automata for Wireless Sensor Networks

To cover a set of targets with known locations within an area with limited or prohibited ground access using a wireless sensor network, one approach is to deploy the sensors remotely, from an aircraft. In this approach, the lack of precise sensor placement is compensated by redundant de-ployment of sensor nodes. This redundancy can also be used for extending the lifetime of the network, if a proper scheduling mechanism is available for scheduling the active and sleep times of sensor nodes in such a way that each node is in active mode only if it is required to. In this pa-per, we propose an efficient scheduling method based on learning automata and we called it LAML, in which each node is equipped with a learning automaton, which helps the node to select its proper state (active or sleep), at any given time. To study the performance of the proposed method, computer simulations are conducted. Results of these simulations show that the pro-posed scheduling method can better prolong the lifetime of the network in comparison to similar existing method

Markov Decision Processes with Applications in Wireless Sensor Networks: A Survey

Wireless sensor networks (WSNs) consist of autonomous and resource-limited devices. The devices cooperate to monitor one or more physical phenomena within an area of interest. WSNs operate as stochastic systems because of randomness in the monitored environments. For long service time and low maintenance cost, WSNs require adaptive and robust methods to address data exchange, topology formulation, resource and power optimization, sensing coverage and object detection, and security challenges. In these problems, sensor nodes are to make optimized decisions from a set of accessible strategies to achieve design goals. This survey reviews numerous applications of the Markov decision process (MDP) framework, a powerful decision-making tool to develop adaptive algorithms and protocols for WSNs. Furthermore, various solution methods are discussed and compared to serve as a guide for using MDPs in WSNs

Locating sensors with fuzzy logic algorithms

In a system formed by hundreds of sensors deployed in a huge area it is important to know the position where every sensor is. This information can be obtained using several methods. However, if the number of sensors is high and the deployment is based on ad-hoc manner, some auto-locating techniques must be implemented. In this paper we describe a novel algorithm based on fuzzy logic with the objective of estimating the location of sensors according to the knowledge of the position of some reference nodes. This algorithm, called LIS (Localization based on Intelligent Sensors) is executed distributively along a wireless sensor network formed by hundreds of nodes, covering a huge area. The evaluation of LIS is led by simulation tests. The result obtained shows that LIS is a promising method that can easily solve the problem of knowing where the sensors are located.Junta de Andalucía P07-TIC-0247

Design of Combined Coverage Area Reporting and Geo-casting of Queries for Wireless Sensor Networks

In order to efficiently deal with queries or other location dependent information, it is key that the wireless sensor network informs gateways what geographical area is serviced by which gateway. The gateways are then able to e.g. efficiently route queries which are only valid in particular regions of the deployment. The proposed algorithms combine coverage area reporting and geographical routing of queries which are injected by gateways.\u