Abstract
Energy efficiency is very important for wireless sensor networks (WSNs) since sensor nodes have a limited energy supply from a battery. So far, a lot research has focused on this issue, while less emphasis has been placed on the adaptive sleep time for each node with a consideration for the application constraints. In this paper, we propose a hierarchically coordinated power management (HCPM) approach, which both addresses the energy conservation problem and reduces the packet forwarding delay for target tracking WSNs based on a virtual-grid-based network structure. We extend the network lifetime by adopting an adaptive sleep scheduling scheme that combines the local power management (PM) and the adaptive coordinate PM strategies to schedule the activities of the sensor nodes at the surveillance stage. Furthermore, we propose a hierarchical structure for the tracking stage. Experimental results show that the proposed approach has a greater capability of extending the network lifetime while maintaining a short transmission delay when compared with the protocol which does not consider the application constraints in target tracking sensor networks.
Highlights
In a wireless sensor network (WSN), sensor nodes are always deployed in an unattended natural environment and are of an enormous amount
We consider a static WSN which is composed of one sink and some randomly and evenly distributed sensor nodes Ni, i [1, n] in a two‐dimensional sensing field, where n is the number of the deployed nodes
The main reasons for the large lifetime extension are three folds: 1) hierarchically coordinated power management (HCPM) adopts an adaptive sleep time for grid members (GMs) and the GMs far from the target have a long term sleep time; 2) the transmitting costs of the detected information are reduced since the information is transmitted only among the grid head (GH); 3) the energy consumption between the border and the interior nodes are balanced because the interior nodes have more sleep time in the surveillance stage and they always take more relay tasks in the tracking stage
Summary
In a wireless sensor network (WSN), sensor nodes are always deployed in an unattended natural environment and are of an enormous amount. Since the sensed data is sent to the sink by multi‐hop routing, more nodes are in the sleep state and longer delays are introduced in the packet delivery because during the sleep phases nodes cannot communicate and packets cannot be transmitted until the relay or destination nodes wake up With these issues in mind, we propose a hierarchically coordinated power management (HCPM) approach that considers the application constraints in order to exploit sleep and active intervals. In my work, dividing the network into grid based on the geographical information is a highly efficient method because the tracking application always relates to the geographical position of the target. One sub‐area uses the tracking stage sleep policy, while others can still use the surveillance sleep policy This makes the network more adaptive and energy efficient.
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