Open AccessAlgorithm for energy consumption minimisation in wireless sensor network
Author(s) -
Kumar Shah Indra,
Maity Tanmoy,
Singh Dohare Yogendra
Publication year - 2020
Publication title -
iet communications
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.355
H-Index - 62
eISSN - 1751-8636
pISSN - 1751-8628
DOI - 10.1049/iet-com.2019.0465
Subject(s) - computer science , energy consumption , wireless sensor network , computer network , network packet , real time computing , efficient energy use , bottleneck , timeout , network performance , key distribution in wireless sensor networks , duty cycle , wireless network , wireless , power (physics) , embedded system , telecommunications , engineering , electrical engineering , physics , quantum mechanics
Wireless sensor network (WSN) consists of spatially distributed miniature size and autonomous nodes along with batteries as a power source. The major bottleneck of WSN is efficient energy utilization. The energy consumption for transmission of signals increases with the distance. This problem of energy consumption is addressed in this study. This study presents a strategy, namely distance‐based dynamic duty‐cycle allocation (DBDDCA) algorithm. In DBDDCA, longer distance nodes from cluster head (CH) transmit relatively less time in order to save energy. Conversely, transmit for the higher time when the distance is near to CH. The proposed DBDDCA is compared with the other existing strategies: low‐energy adaptive cluster hierarchy (LEACH), modified leach, and stable election protocol and with two existing medium access control (MAC) protocols: sensor (S)‐MAC and timeout (T)‐MAC. The performance of the proposed and existing strategies is evaluated with the following network parameters: energy consumption, network energy utilization, network lifetime, latency, and packets delivery. These parameters have been evaluated with different network scenarios such as number of nodes increases, number of rounds, and with variation in initial energy of nodes. Simulation results show the performance of the proposed strategy is significantly better than the existing strategies under the investigated network parameters.