An Energy Efficient Cluster Formation and Maintenance Scheme for Wireless Sensor Networks

Abstract

The vast potential applications of wireless sensor networks (WSNs) have attracted extensive research efforts. Conventional networks support mostly point-to-point or point-to-multipoint data forwarding [1].On the other hand, WSNs are often deployed to sense, process, and disseminate information on targeted physical environments. Furthermore, sensor nodes are deployed in large numbers and high density, thus resulting in a potentially huge amount of sensory data, which is often impractical to transmit to the sink directly, particularly from the perspective of energy conservation. Also, the deployed sensors are capable of communicating with each other across short distances. Therefore, data aggregation is required with cluster formation to effectively gather the data from the widespread sensors, and a hierarchical structure is needed to forward the data to the sink in order to curtail the network load and hence reduce energy consumption [2,3].The traditional topology-based WSN routing protocols are quite susceptible to node mobility mainly due to the predetermination of an end-to-end route before data transmits.Owing to the frequent and constant changing of the network topology, it is actually difficult to maintain a deterministic route. Therefore, link failure discovery and recovery procedures also consume time and energy.The most critical requirements of WSNs are achieving the expected throughput as well as covering the entire network efficiently. According to some previous studies on WSNs, it is a challenging job to maintain the mobile sensors in network construction and data forwarding. The flooding/ multicasting technique is an efficient approach to broadcasting the control/data packets in an environment AbstractNowadays, wireless sensor networks (WSNs) comprise a tremendously growing infrastructure for monitoring the physical or environmental conditions of objects. WSNs pose challenges to mitigating energy dissipation by constructing a reliable and energy saving network. In this paper, we propose a novel network construction and routing method by defining three different duties for sensor nodes, that is, node gateways, cluster heads, and cluster members, and then by applying a hierarchical structure from the sink to the normal sensing nodes. This method provides an efficient rationale to support the maximum coverage, to recover missing data with node mobility, and to reduce overall energy dissipation. All this should lengthen the lifetime of the network significantly.

Dynamic cluster heads selection and data aggregation for efficient target monitoring and tracking in wireless sensor networks

“…CHs are responsible for collecting the sensed data from their members and reporting the data to the sink. The literature 11 proposed a novel network construction and routing method by defining three different duties for sensor nodes, that is, node gateways, CHs and cluster members. And then a hierarchical structure from the sink to the normal sensing nodes was applied.…”

Energy-efficient and reliable routing protocol for dynamic-property-based clustering mobile ad hoc networks

“…In addition, equation ( 10) is interpreted (or induced by) equations ( 11)-( 13) by the location of the intermediate node. Equation (11) means that the source node directly sends the packet to the base station. Equation ( 12) means that the intermediate node is located in the circle between the source node and base station.…”

“…However, large number of hops is required for the packet to reach the destination node. [10][11][12][13][14][15][16][17][18] In this article, we therefore propose an advanced energy-conserving optimal path schedule (A-ECOPS) algorithm. Using the algorithm, when the intermediate node is selected, the relative angle between the nodes and the coverage is employed.…”

Effective Relay-Node Selection for Clustering Ad Hoc Network

“…So in this paper, an energy context clustering approach is used. Otherwise, in this paper, the cluster technique use weight-based for multi-hops ad hoc network, which nodes use weight cost function based on residual energy and node mobility and the number of neighbor nodes to form clusters and choose a cluster-head [7][8] [9][10] [11].…”