A Delay-Aware Network Structure for Wireless Sensor Networks With In-Network Data Fusion

被引:60
作者
Cheng, Chi-Tsun [1 ]
Leung, Henry [2 ]
Maupin, Patrick
机构
[1] Hong Kong Polytech Univ, Dept Elect & Informat Engn, Kowloon, Hong Kong, Peoples R China
[2] Univ Calgary, Dept Elect & Comp Engn, Calgary, AB T2N 1N4, Canada
关键词
Clustering; in-network data fusion; network topology; wireless communications; wireless sensor networks; AGGREGATION; ALGORITHM; PROTOCOL; TIME;
D O I
10.1109/JSEN.2013.2240617
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
A wireless sensor network (WSN) comprises a large number of wireless sensor nodes. Wireless sensor nodes are battery-powered devices with limited processing and transmission power. Therefore, energy consumption is a critical issue in system designs of WSNs. In-network data fusion and clustering have been shown to be effective techniques in reducing energy consumption in WSNs. However, clustering can introduce bottlenecks to a network, which causes extra delays in a data aggregation process. The problem will be more severe when in-network data fusion does not yield any size reduction in outgoing data. Such problems can be greatly alleviated by modifying the network structure. In this paper, a delay-aware network structure for WSNs with in-network data fusion is proposed. The proposed structure organizes sensor nodes into clusters of different sizes so that each cluster can communicate with the fusion center in an interleaved manner. An optimization process is proposed to optimize intra-cluster communication distance. Simulation results show that, when compared with other existing aggregation structures, the proposed network structure can reduce delays in data aggregation processes and keep the total energy consumption at low levels provided that data are only partially fusible.
引用
收藏
页码:1622 / 1631
页数:10
相关论文
共 26 条
[1]   Routing techniques in wireless sensor networks: A survey [J].
Al-Karaki, JN ;
Kamal, AE .
IEEE WIRELESS COMMUNICATIONS, 2004, 11 (06) :6-28
[2]  
Atmel Corporation, 2009, ATMEGA128L 8 BIT AVR
[3]   Minimizing energy consumption in large-scale sensor networks through distributed data compression and hierarchical aggregation [J].
Baek, SJ ;
de Veciana, G ;
Su, X .
IEEE JOURNAL ON SELECTED AREAS IN COMMUNICATIONS, 2004, 22 (06) :1130-1140
[4]  
Barnawi A., 2008, P CAN C EL COMP ENG
[5]   A Delay-Aware Data Collection Network Structure for Wireless Sensor Networks [J].
Cheng, Chi-Tsun ;
Tse, Chi K. ;
Lau, Francis C. M. .
IEEE SENSORS JOURNAL, 2011, 11 (03) :699-710
[6]   A Clustering Algorithm for Wireless Sensor Networks Based on Social Insect Colonies [J].
Cheng, Chi-Tsun ;
Tse, Chi K. ;
Lau, Francis C. M. .
IEEE SENSORS JOURNAL, 2011, 11 (03) :711-721
[7]   An Energy-Aware Scheduling Scheme for Wireless Sensor Networks [J].
Cheng, Chi-Tsun ;
Tse, Chi K. ;
Lau, Francis C. M. .
IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY, 2010, 59 (07) :3427-3444
[8]   A Distributed Multihop Time Synchronization Protocol for Wireless Sensor Networks using Pairwise Broadcast Synchronization [J].
Cheng, King-Yip ;
Lui, King-Shan ;
Wu, Yik-Chung ;
Tam, Vincent .
IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS, 2009, 8 (04) :1764-1772
[9]  
Crossbow Technology Inc., 2009, MICAZ WIR MEAS SYST
[10]   Lower bounds on data collection time in sensory networks [J].
Florens, C ;
Franceschetti, M ;
McEliece, RJ .
IEEE JOURNAL ON SELECTED AREAS IN COMMUNICATIONS, 2004, 22 (06) :1110-1120