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Mobile Wireless Sensors Networks (MWSNs) are used in several applications presenting difficult/dangerous environment and/or requiring the movement of sensors after initial deployment. Optimizing the use of the limited energy resource in a MWSN is a key challenge for researchers to maintain longer network survival. This paper attempts to provide an energy-efficient data routing solution for large MWSNs. The aim of this work is to propose a cluster-based scheduling protocol for MWSN.  The network is firstly divided into an optimal number of clusters according to sensors connectivity. Secondly, a sleep scheduling algorithm is proposed to save the energy consumption by turning off the overlapped nodes in the sensing field. This method is distributed among sensor nodes in each cluster. It is based on the perimeter coverage level of mobile sensor nodes to schedule their activities according to their weights. The weight is used to balance the energy consumption for all sensor nodes in a cluster. The proposed approach ranges from sensors deployment, their organization to their operational mode. Experimental results demonstrate that the proposed cluster-based scheduling algorithm, based on the perimeter coverage of sensors, provides higher energy efficiency and longer lifetime coverage for MWSNs as compared to other protocols.

The random deployment of sensors in the area of interest triggers several research issues. Among them, we can cite connectivity, localization and coverage. In this paper, we focus on the latter one. Our objective is to monitor the perimeter of a region of interest with circular shape from intrusions. We propose a new approach to define the minimum coverage set based on points of tangency and strong barrier coverage. Furthermore, in order to exploit the redundancy of information due to the random deployment of nodes, we also suggest a new approach to generate the scheduling sets, which consists on the creation of multiple virtual perimeters around the area of interest, upon which the minimum coverage sets is constructed. In other words, the objective is to minimize the number of nodes in coverage set and to maximize the number of coverage sets for scheduling. These disjoint sets of sensors can be activated one after the other to further extend the network lifetime or multiple sets at time and reach k-barrier coverage for strong surveillance applications. Simulation results show that to generate the minimum coverage set, our approach gives better results compared to those proposed in the literature. Moreover, the approach of constructing the scheduling sets significantly increases the network lifetime.

In a randomly deployed and large scale wireless sensor network, coverage-redundant nodes consume much unnecessary energy. As a result, turning off these redundant nodes can prolong the network lifetime, while maintaining the degree of sensing coverage with a limited number of on-duty nodes. None of the off-duty eligibility rules in the literature, however, are sufficient and necessary conditions for eligible nodes. Hence redundancy or blind points might be incurred. In this paper we propose a complete Eligibility Rule based on Perimeter Coverage (ERPC) for a node to determine its eligibility for sleeping. ERPC has a computational complexity of O(N2log(N)), lower than the eligibility rule in the Coverage Control Protocol (CCP), O(N3), where N is the number of neighboring nodes. We then present a Coverage Preserving Protocol (CPP) to schedule the work state of eligible nodes. The main advantage of CPP over the Ottawa protocol lies in its ability to configure the network to any specific coverage degree, while the Ottawa protocol does not support different coverage configuration. Moreover, as a localized protocol, CPP has better adaptability to dynamic topologies than centralized protocols. Simulation results indicate that CPP can preserve network coverage with fewer active nodes than the Ottawa protocol. In addition, CPP is capable of identifying all the eligible nodes exactly while the CCP protocol might result in blind points due to error decisions. Quantitative analysis and experiments demonstrate that CPP can extend the network lifetime significantly while maintaining a given coverage degree.