Network lifetime and energy consumption of data transmission have been primary Quality of Service (QoS) obligations in Wireless Sensor Networks (WSNs). The environment of a WSN is often organized into clusters to mitigate the management complexity of such obligations. However, the distance between Sensor Nodes (SNs) and the number of clusters per round are vital factors that affect QoS performance of a WSN. A designer's conundrum resolves around the desire to sustain a balance between the limited residual energy of SNs and the demand for prolonged network lifetime. Any imbalance in controlling such objectives results in either QoS penalties due to draining SN energies, or an over-cost environment that is significantly difficult to distribute and operate. Low-Energy Adaptive Clustering Hierarchy (LEACH) is a distributed algorithm proposed to tackle such difficulties. Proposed LEACH-based algorithms focus on residual energies of SNs to compute a probability function that selects cluster-heads and an optimal energy-efficient path toward a destination SN. Nevertheless, these algorithms do not consider variations in network's state at run-time. Such a state changes in an adaptive manner according to existing network structures and conditions. Thus, cluster-heads per round are not elected adaptively depending on the state and distances between SNs. This paper proposes an energy-efficient adaptive distance-based clustering called Adapt-P, in which an adaptive probability function is developed to formulate clusters. A near-optimal distance between each cluster-head and its cluster-members is formulated so that energy consumption of the network is mitigated and network lifetime is maximized. The cluster-head selection probability is adapted at the end of each round based on the maximum number of cluster-heads permitted per round found a priori and the number of alive SNs in the network.
翻译:数据传输的网络存在期和能源消耗是无线传感器网络(WSNNs)中服务(QOS)义务的首要质量。WSN的环境往往被组织成集群,以缓解这些义务的管理复杂性。然而,传感器节点(SNS)与每轮组群之间的距离是影响WSN绩效的重要因素。设计师的难题在于希望维持SNS剩余能量有限和对网络寿命延长期的需求之间的平衡。控制此类目标的任何不平衡都会导致由于SNN能源耗竭而导致的距离处罚;或者由于成本过高的环境,很难分配和操作这些义务。但是,低能源调调控聚点(SNSN)和每轮组群群之间的距离是用来应对这类困难的一种分布式算法。基于LACH的算法侧重于SNP的剩余能量,用以计算基于集点头头的概率函数和最佳节能调整通向目的地的路径。然而,这些算法并不考虑网络中最接近的流流流流点的流流流流流流,因此,在网络的流流流流流流点和流流流流点中,电的能量选择的流流流流流值是当前周期的流流流、流流流流流、流、流、流流的流的流的流、流到流到流到流到流到流到流到流到流到流到流到流到流到流到流到流到流到流到流到流到流到流到流到流到流到流到流到流到流到流到流到流到流到流到流到流到流到流到流到流到流到流到流到流到流到流到流到流到流到流到流到流到流到流到流到流到流到流到流到流到流到流到流到流到流到流到流到流到流到流到流到流到流到流到流到流到流到流到流到流到流到流到流到流到流到流到流到流到流到流到流到流到流到流到流到流到流到流到流到流到流到流到流到流到流到流到流到流到流到流到流到流到流到流