Energy-Aware Control of Data Compression and Sensing Rate for Wireless Rechargeable Sensor Networks

被引:6
作者
Yoon, Ikjune [1 ]
Noh, Dong Kun [2 ]
机构
[1] Soongsil Univ, Dept Smart Syst Software, Seoul 06978, South Korea
[2] Soongsil Univ, Dept Software Convergence, Seoul 06978, South Korea
基金
新加坡国家研究基金会;
关键词
wireless sensor networks; rechargeable; compression; sensing rate control; PREDICTION MODEL; SCHEME; SOLAR;
D O I
10.3390/s18082609
中图分类号
O65 [分析化学];
学科分类号
070302 ; 081704 ;
摘要
Wireless rechargeable sensor nodes can collect additional data, which leads to an increase in the precision of data analysis, when enough harvested energy is acquired. However, because such nodes increase the amount of sensory data, some nodes (especially near the sink) may blackout because more transmitted data can make relaying nodes expend more energy. In this paper, we propose an energy-aware control scheme of data compression and sensing rate to maximize the amount of data collected at the sink, while minimizing the blackout time. In this scheme, each dominant node determines the data quota that all its descendant nodes can transmit during the next period, which operates with an efficient energy allocation scheme. Then, the node receiving the quota selects an appropriate data compression algorithm and sensing rate according to both its quota and allocated energy during the next period, so as not to exhaust the energy of nodes near the sink. Experimental results verify that the proposed scheme collects more data than other schemes, while suppressing the blackout of nodes. We also found that it adapts better to changes in node density and harvesting environments.
引用
收藏
页数:18
相关论文
共 39 条
  • [1] Wireless sensor networks: a survey
    Akyildiz, IF
    Su, W
    Sankarasubramaniam, Y
    Cayirci, E
    [J]. COMPUTER NETWORKS, 2002, 38 (04) : 393 - 422
  • [2] Energy conservation in wireless sensor networks: A survey
    Anastasi, Giuseppe
    Conti, Marco
    Di Francesco, Mario
    Passarella, Andrea
    [J]. AD HOC NETWORKS, 2009, 7 (03) : 537 - 568
  • [3] [Anonymous], 1994, TECHNICAL REPORT
  • [4] Arampatzis T, 2005, 2005 IEEE INTERNATIONAL SYMPOSIUM ON INTELLIGENT CONTROL & 13TH MEDITERRANEAN CONFERENCE ON CONTROL AND AUTOMATION, VOLS 1 AND 2, P719
  • [5] PINCO: a pipelined in-network COmpression scheme for data collection in wireless sensor networks
    Arici, T
    Gedik, B
    Altunbasak, Y
    Liu, L
    [J]. ICCCN 2003: 12TH INTERNATIONAL CONFERENCE ON COMPUTER COMMUNICATIONS AND NETWORKS, PROCEEDINGS, 2003, : 539 - 544
  • [6] Basagni S., 2013, Mobile Ad Hoc Networking: The Cutting Edge Directions, P701
  • [7] Cammarano A, 2012, IEEE INT CONF MOB, P75, DOI 10.1109/MASS.2012.6502504
  • [8] A Joint QRS Detection and Data Compression Scheme for Wearable Sensors
    Deepu, C. J.
    Lian, Y.
    [J]. IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING, 2015, 62 (01) : 165 - 175
  • [9] Wireless sensors for wildfire monitoring
    Doolin, DM
    Sitar, N
    [J]. Smart Structures and Materials 2005: Sensors and Smart Structures Technologies for Civil, Mechanical, and Aerospace, Pts 1 and 2, 2005, 5765 : 477 - 484
  • [10] A new approach for damage detection in asphalt concrete pavements using battery-free wireless sensors with non-constant injection rates
    Hasni, Hassene
    Alavi, Amir H.
    Jiao, Pengcheng
    Lajnef, Nizar
    Chatti, Karim
    Aono, Kenji
    Chakrabartty, Shantanu
    [J]. MEASUREMENT, 2017, 110 : 217 - 229