A Self-adaptive Energy-Aware Data Gathering Mechanism for Wireless Sensor Networks

Author(s):  
Li-Min Sun ◽  
Ting-Xin Yan ◽  
Yan-Zhong Bi ◽  
Hong-Song Zhu
2020 ◽  
Vol 10 (5) ◽  
pp. 1821 ◽  
Author(s):  
Liangrui Tang ◽  
Haobo Guo ◽  
Runze Wu ◽  
Bing Fan

Great improvement recently appeared in terms of efficient service delivery in wireless sensor networks (WSNs) for Internet of things (IoT). The IoT is mainly dependent on optimal routing of energy-aware WSNs for gathering data. In addition, as the wireless charging technology develops in leaps and bounds, the performance of rechargeable wireless sensor networks (RWSNs) is greatly ameliorated. Many researches integrated wireless energy transfer into data gathering to prolong network lifetime. However, the mobile collector cannot visit all nodes under the constraints of charging efficiency and gathering delay. Thus, energy consumption differences caused by different upload distances to collectors impose a great challenge in balancing energy. In this paper, we propose an adaptive dual-mode routing-based mobile data gathering algorithm (ADRMDGA) in RWSNs for IoT. The energy replenishment capability is reasonably allocated to low-energy nodes according to our objective function. Furthermore, the innovative adaptive dual-mode routing allows nodes to choose direct or multi-hop upload modes according to their relative upload distances. The empirical study confirms that ADRMDGA has excellent energy equilibrium and effectively extends the network lifetime.


Author(s):  
Natarajan Meghanathan

This paper develops an energy-aware connected dominating set based data gathering (ECDS-DG) algorithm for wireless sensor networks. The algorithm includes only nodes that have a relatively higher energy level in ECDS. For every round, a data gathering tree (ECDS-DG tree) rooted at the ECDS Leader, that is, the node with the largest available energy, which transmits the data packet to the sink, is formed by considering only the nodes in the ECDS as the intermediate nodes of the tree. The non-ECDS nodes are leaf nodes of the tree, and the upstream node of an intermediate ECDS node in the ECDS-DG tree is the closest ECDS node that is also relatively closer to the ECDS Leader. Performance comparison studies involving well-known LEACH and PEGASIS algorithms indicate that ECDS-DG incurs the lowest energy consumption per round and sustains the largest number of rounds before first node failure.


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