Opportunistic Routing (OR) is adapted to improve the performance of low Duty-cycled Wireless Sensor Networks by exploiting its broadcast nature. In contrast to traditional routing, where packets are transmitted along pre-determined paths, OR uses a prioritization metric to select a set of candidates as potential forwarders. This solves the sender's waiting time problem. However, too many candidates may simultaneously wake-up, generating more duplicate packets, occupying the restricted resources and hinder the packet delivery performance. Consciously, to restrict the number of candidates and to counterbalance between the waiting time problem and the duplicate packets problem, this paper proposed a new protocol that combines two main parts. First, each node defines a Candidates Zone (CZ) by a regular geometric shape of four corners. The packets generated by the node will be routed via any path within the CZ. Expressly, the nodes within the CZ are allowed to be selected as candidates. The size of CZ is controlled by the network density. Second, the candidates within the CZ are prioritized based on the OR metric, which is defined as the multiplication of four-distributions: direction distribution, transmission-distance distribution, perpendicular-distance distribution and residual energy distribution. Through an extensive performance evaluation study and simulation of large-scale scenarios, the results demonstrated that our protocol achieved better performance compared to the state-of-the-art solutions in terms of network lifetime, energy consumption, routing efficiency, sender waiting time and duplicate packets.

Grid Coverage Algorithm & Analyzing for wireless sensor networks

The use of wireless sensor networks (WSN) in tracking applications is growing rapidly. In these applications, the nodes detect, monitor, and track a target, object, or event. In this paper, we consider the problem of tracking mobile objects in wireless sensor networks (WSN). We present a novel tracking model, named Grouping based Location Tracking (GLT), scaling well with the number of nodes and the number of mobile objects. GLT is based on the Grouping Hierarchy Structure, GHS. In GHS, nodes are partitioned into groups (not clusters) according to their maximum covered region (MCR) such that each group contains a number of nodes and a number of leaders. GLT consists of two tiers. The first tier, which is called the Notification Tree (NT), enhances the activation mechanism, the data cleaning mechanism, and the energy balancing mechanism. On the other hand, the second tier, which is called the Hierarchical Spanning Tree (HST), supports the data reporting mechanism and the lifetime prolonging mechanism. Simulations results show that GLT reduces the communication node selections overhead without diminishing object tracking accuracy and achieves a significant energy consumption reduction and network lifetime extension compared with the state-of-the-art approaches.