An Energy Efficient Adaptive Scheduling Scheme (EASS) for Mesh Grid Wireless Sensor Networks

摘要

The technology-driven shift in distributed network systems, Internet technology and energy grid digitization have changed the traditional spoke-hub distribution models to the more flexible and giant network-to-networks paradigm known as Energy Cloud. This energy cloud paradigm has the ability to adapt to the large-scale distributed energy resources with dynamic demand-response associated with smart grid and smart homes applications, which allows customers/users to have connectivity of electrical devices with supply grid into one giant energy cloud network. If efficient policies are not adapted in the design and operations of such networks, sensor devices may sense and forward redundant data packets. Hence, valuable energy of the node will be depleted quickly and as a resu the network will be down before accomplishing its intended task. To address the issue of energy-efficiency in energy-cloud at embedded networks, this paper proposes a novel scheme, "Energy Efficient Adaptive Scheduling Scheme (EASS) for Mesh Grid Wireless Sensor Networks". In EASS, a sensor node configures and schedules its functions/roles according to the contents of sensed data packets and frequency of generated traffic. Like energy cloud, tasks are uniformly distributed on all nodes in mesh-grid in four states - each state of a node is responsible for configuring its components on a specific energy level - which aims to avoid link disconnection and vanish redundant data packets generation. Simulation results show that EASS increases energy-efficiency by 50% due to the four-states model, 62.5% due to alive nodes, 92.60% due to minimized Cluster-Heads overhead and 38.11% due to the reduction in dead nodes ratio.