Study on distributed and dynamic resource management for delay-sensitive sensor network

被引:0
|
作者
Liu W. [1 ]
Liu J. [1 ]
机构
[1] National Key Laboratory of Science and Technology on Communications, University of Science and Technology of China, Chengdu
来源
基金
中国国家自然科学基金;
关键词
Delay-sensitive; Dynamic resource management; Sensor network; Stochastic optimization problem;
D O I
10.11959/j.issn.1000-436x.2017144
中图分类号
学科分类号
摘要
The delay-aware dynamic resource management problem was investigated in sensor network, with a focus on resource allocation among the sensors and power control along the time. By taking account of average delay requirements and power constraints, the considered problem was formulated into a stochastic optimization problem. Inspired by Lyapunov optimization theory, the intractable stochastic optimization problem was transformed into a tractable deterministic optimization problem, which was a mixed-integer resource management problem. By exploiting the specific problem structure, the mixed-integer resource management problem was equivalently transformed into a single variable problem, and the cooperative distributed method was present to effectively solve it with guaranteed global optimality. Finally, a dynamic resource management algorithm was proposed to solve the original stochastic optimization problem. Simulation results show the performance of the proposed dynamic algorithm and reveal that there exists a fundamental tradeoff between delay requirements and power consumption. © 2017, Editorial Board of Journal on Communications. All right reserved.
引用
收藏
页码:70 / 77
页数:7
相关论文
共 17 条
  • [1] Akyildiz I.F., Su W., Sankarasubramaniam Y., Et al., Wireless sensor networks: a survey, Computer Networks, 38, 4, pp. 393-422, (2002)
  • [2] Yick J., Mukherjee B., Ghosal D., Wireless sensor network survey, Computer Networks, 52, pp. 2292-2330, (2008)
  • [3] Dbibih I., Zytoune O., Aboutajdine D., ON/OFF Markov model based energy-delay aware MAC protocol for wireless sensor network, Wireless Personal Communications, 78, 2, pp. 1157-1158, (2014)
  • [4] Zhang X.L., Liang W., Yu H.B., Et al., A survey on transmission scheduling method in wireless sensor networks, Journal on Communications, 33, 5, pp. 143-157, (2012)
  • [5] Huang P.K., Lin X.J., Wang C.C., A low-complexity congestion control and scheduling algorithm for multihop wireless networks with order-optimal per-flow delay, IEEE INFOCOM, pp. 2588-2596, (2011)
  • [6] Pradeep C.W., Marian C., Matti L.A., Et al., Resource allocation for cross-layer utility maximization in wireless networks, IEEE Transactions on Vehicular Technology, 66, 6, pp. 2790-2809, (2011)
  • [7] Zimmerman A.T., Lynch J.P., Ferrese F.T., Market-based resource allocation for distributed data processing in wireless sensor networks, ACM Transactions on Embedded Computing Systems, 12, 3, pp. 1-28, (2013)
  • [8] Uchitelava E., Shami A., Refaey A., Virtualization of wireless sensor networks through MAC layer resource scheduling, IEEE Sensors Journal, 17, 5, pp. 1562-1576, (2017)
  • [9] Albert S., Joint scheduling and sensing allocation in energy harvesting sensor networks with fusion centers, IEEE Journal on Selected Areas in Communications, 34, 12, pp. 3577-3589, (2016)
  • [10] He S., Chen J., Yau D., Et al., Cross-layer optimization of correlated data gathering in wireless sensor networks, IEEE Transactions on Mobile Computing, 11, 11, pp. 1678-1691, (2012)