Network Lifetime and Coverage Fraction Analysis for Wireless Sensor Networks

285-291In Wireless Sensor Networks, two crucial parameters are lifetime of the network and optimal coverage for sensed region. This paper addresses the issues and challenges pertaining to these parameters for further investigation, and provides a method to approximate the energy utilization and optimal coverage inside the bottleneck zone for wireless sensor networks. The proposed analytical framework calculates correctly the network lifetime upper bound of wireless sensor networks. The derivation of the network lifetime upper bound is carried out using (i) network coding and (ii) network coding with duty cycle. Based on that, an approximate derivation is made and the corresponding results are obtained from the simulation study. The comparison of the results of the previous study and those obtained in this paper reveals that the actual network lifetime upper bound is lower in the present case. This is due to the assumption made by authors of previous work, on coder nodes’ presence throughout the bottleneck zone instead of only one hop distance away from the sink. In addition, the effect of coverage fraction in case of node failure, on network lifetime upper bound is derived for the previously reported and present model. The simulated results obtained from new derivation show that the coverage fraction is lesser than that obtained by previous model

Achieving Minimum Coverage Breach under Bandwidth Constraints in Wireless Sensor Networks

This paper addresses the coverage breach problem in wireless sensor networks with limited bandwidths. In wireless sensor networks, sensor nodes are powered by batteries. To make efficient use of battery energy is critical to sensor network lifetimes. When targets are redundantly covered by multiple sensors, especially in stochastically deployed sensor networks, it is possible to save battery energy by organizing sensors into mutually exclusive subsets and alternatively activating only one subset at any time. Active nodes are responsible for sensing, computing and communicating. While the coverage of each subset is an important metric for sensor organization, the size of each subset also plays an important role in sensor network performance because when active sensors periodically send data to base stations, contention for channel access must be considered. The number of available channels imposes a limit on the cardinality of each subset. Coverage breach happens when a subset of sensors cannot completely cover all the targets. To make efficient use of both energy and bandwidth with a minimum coverage breach is the goal of sensor network design. This paper presents the minimum breach problem using a mathematical model, studies the computational complexity of the problem, and provides two approximate heuristics. Effects of increasing the number of channels and increasing the number of sensors on sensor network coverage are studied through numerical simulations. Overall, the simulation results reveal that when the number of sensors increases, network lifetimes can be improved without loss of network coverage if there is no bandwidth constraint; with bandwidth constraints, network lifetimes may be improved further at the cost of coverage breach

Network Lifetime and Coverage Fraction Analysis for Wireless Sensor Networks

In Wireless Sensor Networks, two crucial parameters are lifetime of the network and optimal coverage for sensed region. This paper addresses the issues and challenges pertaining to these parameters for further investigation, and provides a method to approximate the energy utilization and optimal coverage inside the bottleneck zone for wireless sensor networks. The proposed analytical framework calculates correctly the network lifetime upper bound of wireless sensor networks. The derivation of the network lifetime upper bound is carried out using (i) network coding and (ii) network coding with duty cycle. Based on that, an approximate derivation is made and the corresponding results are obtained from the simulation study.  The comparison of the results of the previous study and those obtained in this paper reveals that the actual network lifetime upper bound is lower in the present case. This is due to the assumption made by authors of previous work, on coder nodes’ presence throughout the bottleneck zone instead of only one hop distance away from the sink. In addition, the effect of coverage fraction in case of node failure, on network lifetime upper bound is derived for the previously reported and present model. The simulated results obtained from new derivation show that the coverage fraction is lesser than that obtained by previous model

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

Sizes of Minimum Connected Dominating Sets of a Class of Wireless Sensor Networks

We consider an important performance measure of wireless sensor networks, namely, the least number of nodes, N, required to facilitate routing between any pair of nodes, allowing other nodes to remain in sleep mode in order to conserve energy. We derive the expected value and the distribution of N for single dimensional dense networks

Homology-based Distributed Coverage Hole Detection in Wireless Sensor Networks

Homology theory provides new and powerful solutions to address the coverage problems in wireless sensor networks (WSNs). They are based on algebraic objects, such as Cech complex and Rips complex. Cech complex gives accurate information about coverage quality but requires a precise knowledge of the relative locations of nodes. This assumption is rather strong and hard to implement in practical deployments. Rips complex provides an approximation of Cech complex. It is easier to build and does not require any knowledge of nodes location. This simplicity is at the expense of accuracy. Rips complex can not always detect all coverage holes. It is then necessary to evaluate its accuracy. This work proposes to use the proportion of the area of undiscovered coverage holes as performance criteria. Investigations show that it depends on the ratio between communication and sensing radii of a sensor. Closed-form expressions for lower and upper bounds of the accuracy are also derived. For those coverage holes which can be discovered by Rips complex, a homology-based distributed algorithm is proposed to detect them. Simulation results are consistent with the proposed analytical lower bound, with a maximum difference of 0.5%. Upper bound performance depends on the ratio of communication and sensing radii. Simulations also show that the algorithm can localize about 99% coverage holes in about 99% cases