Coverage and Connectivity Aware Neural Network Based Energy Efficient Routing in Wireless Sensor Networks

There are many challenges when designing and deploying wireless sensor networks (WSNs). One of the key challenges is how to make full use of the limited energy to prolong the lifetime of the network, because energy is a valuable resource in WSNs. The status of energy consumption should be continuously monitored after network deployment. In this paper, we propose coverage and connectivity aware neural network based energy efficient routing in WSN with the objective of maximizing the network lifetime. In the proposed scheme, the problem is formulated as linear programming (LP) with coverage and connectivity aware constraints. Cluster head selection is proposed using adaptive learning in neural networks followed by coverage and connectivity aware routing with data transmission. The proposed scheme is compared with existing schemes with respect to the parameters such as number of alive nodes, packet delivery fraction, and node residual energy. The simulation results show that the proposed scheme can be used in wide area of applications in WSNs.Comment: 16 Pages, JGraph-Hoc Journa

Θ(1) Time Algorithm for Master Selection in Ad-hoc Wireless Networks

This paper details a hardware implementation of a distributed Θ(1) time algorithm allows to select dynamically the master device in ad-hoc or cluster-based networks in a constant time regardless the number of devices in the same cluster. The algorithm allows each device to automatically detect its own status; master or slave; based on identifier without adding extra overheads or exchanging packets that slow down the network. We propose a baseband design that implements algorithm functions and we detail the hardware implementation using Matlab/Simulink and Ettus B210 USRP. Tests held in laboratory prove that algorithm works as expected

ENERGY AWARE ROUTING FOR WIRELESS SENSOR NETWORKS

Wireless sensor networks are used in improving conditions in the practical field and real life which lead researchers and developers to further research it and work into improving this field. These networks consist of sensor nodes that can help acquire data and information about temperature and pressure dependent on the environment of the location which are sent from. After all that, we are bounded by a really important factor which can determine everything which is Energy. Since sensor nodes send data and information to web applications, they need an energy source to operate. Their main energy source is their batteries which offer limited source of energy. Hence, various protocols are introduced to help in many parameters of a wireless sensor network such as increasing lifetime and decreasing consumption of energy, in other words, increasing the Energy Efficiency (EF). In this paper, we evaluate consumption of average energy for various protocols used in this context after each complete logical round for these protocols, such as Energy Efficient Clustering Scheme and Stable Election Protocol. Finally, we used Matlab tool to generate results which indicate that the protocol used in this paper is efficient and reliable

Coverage Protocols for Wireless Sensor Networks: Review and Future Directions

The coverage problem in wireless sensor networks (WSNs) can be generally defined as a measure of how effectively a network field is monitored by its sensor nodes. This problem has attracted a lot of interest over the years and as a result, many coverage protocols were proposed. In this survey, we first propose a taxonomy for classifying coverage protocols in WSNs. Then, we classify the coverage protocols into three categories (i.e. coverage aware deployment protocols, sleep scheduling protocols for flat networks, and cluster-based sleep scheduling protocols) based on the network stage where the coverage is optimized. For each category, relevant protocols are thoroughly reviewed and classified based on the adopted coverage techniques. Finally, we discuss open issues (and recommend future directions to resolve them) associated with the design of realistic coverage protocols. Issues such as realistic sensing models, realistic energy consumption models, realistic connectivity models and sensor localization are covered

Θ(1) Time Algorithm for Master Selection in Ad-hoc Wireless Networks

This paper details a hardware implementation of a distributed Θ(1) time algorithm allows to select dynamically the master device in ad-hoc or cluster-based networks in a constant time regardless the number of devices in the same cluster. The algorithm allows each device to automatically detect its own status; master or slave; based on identifier without adding extra overheads or exchanging packets that slow down the network. We propose a baseband design that implements algorithm functions and we detail the hardware implementation using Matlab/Simulink and Ettus B210 USRP. Tests held in laboratory prove that algorithm works as expected