Energy control in dependable wireless sensor networks: a modelling perspective Energy control in dependable wireless sensor networks: a modelling perspective

被引:11
|
作者
Bruneo, D. [1 ]
Puliafito, A. [1 ]
Scarpa, M. [1 ]
机构
[1] Univ Messina, Dipartimento Matemat, Messina, Italy
关键词
wireless sensor networks; reliability; producibility; energy consumption; network topology; Markov reward models; non-Markovian stochastic Petri nets;
D O I
10.1177/1748006X10397845
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
Wireless sensor networks (WSN) are composed of a large number of tiny sensor nodes randomly distributed over a geographical region. In order to reduce power consumption, battery-operated sensors undergo cycles of sleeping-active periods that reduce their ability to send/receive data. Starting from the Markov reward model theory, this paper presents a dependability model to analyse the reliability of a sensor node. Also, a new dependability parameter is introduced, referred to as producibility, which is able to capture the capability of a sensor to accomplish its mission. Two different model solution techniques are proposed, one based on the evaluation of the accumulated reward distribution and the other based on an equivalent model based on non-Markovian stochastic Petri nets. The obtained results are used to investigate the dependability of a whole WSN taking into account the presence of redundant nodes. Topological aspects are taken into account, providing a quantitative comparison among three typical network topologies: star, tree, and mesh. Numerical results are provided in order to highlight the advantages of the proposed technique and to demonstrate the equivalence of the proposed approaches.
引用
收藏
页码:424 / 434
页数:11
相关论文
共 50 条
  • [21] Dependable wireless sensor networks for reliable and secure humanitarian relief applications
    Khalil, Issa M.
    Khreishah, Abdallah
    Ahmed, Faheem
    Shuaib, Khaled
    AD HOC NETWORKS, 2014, 13 : 94 - 106
  • [22] Dependable data aggregation on cluster-based wireless sensor networks
    Chang, Yue-Shan
    Huang, Jiun-Hua
    Juang, Tong-Ying
    PROCEEDINGS OF THE 11TH WSEAS INTERNATIONAL CONFERENCE ON COMMUNICATIONS, VOL 3: ADVANCES IN COMMUNICATIONS, 2007, : 300 - +
  • [23] Maximum lifetime dependable barrier-coverage in wireless sensor networks
    Kim, Donghyun
    Kim, Hyunbum
    Li, Deying
    Kwon, Sung-Sik
    Tokuta, Alade O.
    Cobb, Jorge A.
    AD HOC NETWORKS, 2016, 36 : 296 - 307
  • [24] Minimum energy consumption topology control for wireless sensor networks
    Chen, Yong-Jun
    Yuan, Shen-Fang
    Dianzi Keji Daxue Xuebao/Journal of the University of Electronic Science and Technology of China, 2012, 41 (04): : 568 - 573
  • [25] An energy efficient topology control protocol in wireless sensor networks
    Hong, Seungki
    Choi, Yeon-Jun
    Kim, Sun-Joong
    9TH INTERNATIONAL CONFERENCE ON ADVANCED COMMUNICATION TECHNOLOGY: TOWARD NETWORK INNOVATION BEYOND EVOLUTION, VOLS 1-3, 2007, : 537 - +
  • [26] An Energy Efficient Congestion Control Protocol for Wireless Sensor Networks
    Enigo, V. S. Felix
    Ramachandran, V.
    2009 IEEE INTERNATIONAL ADVANCE COMPUTING CONFERENCE, VOLS 1-3, 2009, : 1573 - +
  • [27] Energy Efficient Medium Access Control for Wireless Sensor Networks
    Ramakrishnan, Sabitha
    Thyagarajan, T.
    INTERNATIONAL JOURNAL OF COMPUTER SCIENCE AND NETWORK SECURITY, 2009, 9 (06): : 273 - 279
  • [28] EFCon: Energy flow control for sustainable wireless sensor networks
    Shen, Xingfa
    Bo, Cheng
    Zhang, Jianhui
    Tang, Shaojie
    Mao, Xufei
    Dai, Guojun
    AD HOC NETWORKS, 2013, 11 (04) : 1421 - 1431
  • [29] An Energy Effective Method for Topology Control in Wireless Sensor Networks
    Wawrvszczuk, Marcin
    Amanowicz, Marek
    2012 19TH INTERNATIONAL CONFERENCE ON MICROWAVE RADAR AND WIRELESS COMMUNICATIONS (MIKON), VOLS 1 AND 2, 2012, : 647 - 651
  • [30] Energy Efficient Transmission Control Protocol in Wireless Sensor Networks
    Mohanty, Prabhudutta
    Kabat, Manas Ranjan
    Patel, Manoj Kumar
    WIRELESS NETWORKS AND COMPUTATIONAL INTELLIGENCE, ICIP 2012, 2012, 292 : 56 - 65