Open AccessDelay constraint energy‐efficient routing based on Lagrange relaxation in wireless sensor networks
Author(s) -
Huynh TrongThua,
Tran ThongNhat,
Tran CongHung,
DinhDuc AnhVu
Publication year - 2017
Publication title -
iet wireless sensor systems
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.433
H-Index - 27
ISSN - 2043-6394
DOI - 10.1049/iet-wss.2017.0038
Subject(s) - wireless sensor network , energy consumption , computer science , network delay , sink (geography) , lagrange multiplier , elmore delay , end to end delay , transmission delay , mathematical optimization , efficient energy use , routing (electronic design automation) , real time computing , computer network , propagation delay , mathematics , network packet , delay calculation , engineering , cartography , geography , electrical engineering
Most of researches on wireless sensor network (WSN) are focused on how to reduce energy consumption to increase the network lifetime. There are few researches solving the problem of energy optimization ensuring delay constraint. Whereas, the delay is important factor for applications that require delay‐sensitive data. Several works have been published to balance the energy consumption and delay. They achieved many different results but each proposal has certain limitations. Some proposals have high computational and messaging complexity. Some others have not found the optimal solution. In this study, we investigate in finding solution to improve the energy efficiency of sensor nodes satisfying end‐to‐end delay to transmit data from sensor nodes to sink in multi‐hop WSNs. Based on Lagrange relaxation method, we propose an aggregate cost function between energy consumption and delay as well as an efficient method to find the optimal multiplier for that objective function. We provide two algorithms to find paths with least energy consumption while maintaining end‐to‐end delay requirement from any sensor node to sink. Besides analyzing the complexity and convergence of the algorithm, the simulation results also show that the proposed algorithm achieved good balance between energy consumption and delay compared with the previous proposals.