Mammu Aboobeker Sidhik Koyamparambil, Hernandez-Jayo Unai, Sainz Nekane, de la Iglesia Idoia
DeustoTech, Department of Engineering, University of Deusto, Bilbao 48007, Spain.
Sensors (Basel). 2015 Apr 9;15(4):8314-36. doi: 10.3390/s150408314.
Recent developments in electronics and wireless communications have enabled the improvement of low-power and low-cost wireless sensors networks (WSNs). One of the most important challenges in WSNs is to increase the network lifetime due to the limited energy capacity of the network nodes. Another major challenge in WSNs is the hot spots that emerge as locations under heavy traffic load. Nodes in such areas quickly drain energy resources, leading to disconnection in network services. In such an environment, cross-layer cluster-based energy-efficient algorithms (CCBE) can prolong the network lifetime and energy efficiency. CCBE is based on clustering the nodes to different hexagonal structures. A hexagonal cluster consists of cluster members (CMs) and a cluster head (CH). The CHs are selected from the CMs based on nodes near the optimal CH distance and the residual energy of the nodes. Additionally, the optimal CH distance that links to optimal energy consumption is derived. To balance the energy consumption and the traffic load in the network, the CHs are rotated among all CMs. In WSNs, energy is mostly consumed during transmission and reception. Transmission collisions can further decrease the energy efficiency. These collisions can be avoided by using a contention-free protocol during the transmission period. Additionally, the CH allocates slots to the CMs based on their residual energy to increase sleep time. Furthermore, the energy consumption of CH can be further reduced by data aggregation. In this paper, we propose a data aggregation level based on the residual energy of CH and a cost-aware decision scheme for the fusion of data. Performance results show that the CCBE scheme performs better in terms of network lifetime, energy consumption and throughput compared to low-energy adaptive clustering hierarchy (LEACH) and hybrid energy-efficient distributed clustering (HEED).
电子学和无线通信领域的最新进展推动了低功耗、低成本无线传感器网络（WSN）的改进。由于网络节点的能量容量有限，WSN面临的最重要挑战之一是延长网络寿命。WSN的另一个主要挑战是在高流量负载区域出现的热点。这些区域的节点会迅速耗尽能源，导致网络服务中断。在这样的环境中，基于跨层聚类的节能算法（CCBE）可以延长网络寿命并提高能源效率。CCBE基于将节点聚类为不同的六边形结构。一个六边形簇由簇成员（CM）和簇头（CH）组成。CH是根据接近最优CH距离的节点和节点的剩余能量从CM中选择的。此外，还推导出了与最优能量消耗相关的最优CH距离。为了平衡网络中的能量消耗和流量负载，CH在所有CM之间轮换。在WSN中，能量主要在发送和接收过程中消耗。传输冲突会进一步降低能源效率。在传输期间使用无竞争协议可以避免这些冲突。此外，CH根据CM的剩余能量为其分配时隙，以增加睡眠时间。此外，通过数据聚合可以进一步降低CH的能量消耗。在本文中，我们提出了一种基于CH剩余能量的数据聚合级别以及一种用于数据融合的成本感知决策方案。性能结果表明，与低能量自适应聚类分层协议（LEACH）和混合节能分布式聚类协议（HEED）相比，CCBE方案在网络寿命、能量消耗和吞吐量方面表现更好。
