TY - GEN
T1 - Delay-minimized energy-efficient data aggregation in wireless sensor networks
AU - Le, Huu Nghia
AU - Zalyubovskiy, Vyacheslav
AU - Choo, Hyunseung
PY - 2012
Y1 - 2012
N2 - Data aggregation is a fundamental problem in wireless sensor networks that has attracted great attention in recent years. To design a data aggregation scheme, delay and energy efficiencies are two crucial issues that require much consideration. In this paper, we propose a distributed, energy-efficient algorithm for collecting data from all sensor nodes with minimum latency called Delay-minimized Energy-efficient Data Aggregation algorithm (DEDA). The DEDA algorithm minimizes data aggregation latency by building a delay-efficient network structure. At the same time, it also considers the distances between network nodes for saving sensor transmission power and network energy. Energy consumption is also well-balanced between sensors to achieve an acceptable network lifetime. The simulation results show that the scheme could significantly decrease data aggregation delay and obtain a reasonable network lifetime compared with other approaches.
AB - Data aggregation is a fundamental problem in wireless sensor networks that has attracted great attention in recent years. To design a data aggregation scheme, delay and energy efficiencies are two crucial issues that require much consideration. In this paper, we propose a distributed, energy-efficient algorithm for collecting data from all sensor nodes with minimum latency called Delay-minimized Energy-efficient Data Aggregation algorithm (DEDA). The DEDA algorithm minimizes data aggregation latency by building a delay-efficient network structure. At the same time, it also considers the distances between network nodes for saving sensor transmission power and network energy. Energy consumption is also well-balanced between sensors to achieve an acceptable network lifetime. The simulation results show that the scheme could significantly decrease data aggregation delay and obtain a reasonable network lifetime compared with other approaches.
KW - data aggregation
KW - delay-constrained
KW - energy-efficient
KW - wireless sensor networks
UR - https://www.scopus.com/pages/publications/84872358793
U2 - 10.1109/CyberC.2012.73
DO - 10.1109/CyberC.2012.73
M3 - Conference contribution
AN - SCOPUS:84872358793
SN - 9780769548104
T3 - Proceedings of the 2012 International Conference on Cyber-Enabled Distributed Computing and Knowledge Discovery, CyberC 2012
SP - 401
EP - 407
BT - Proceedings of the 2012 International Conference on Cyber-Enabled Distributed Computing and Knowledge Discovery, CyberC 2012
T2 - 4th International Conference on Cyber-Enabled Distributed Computing and Knowledge Discovery, CyberC 2012
Y2 - 10 October 2012 through 12 October 2012
ER -