Query Timing Analysis for Content-Based Wake-Up Realizing Informative IoT Data Collection

被引:4
|
作者
Shiraishi, Junya [1 ]
Kalor, Anders E. E. [2 ]
Chiariotti, Federico [2 ]
Leyva-Mayorga, Israel [2 ]
Popovski, Petar [2 ]
Yomo, Hiroyuki [1 ]
机构
[1] Kansai Univ, Grad Sch Sci & Engn, Suita 5648680, Japan
[2] Aalborg Univ, Dept Elect Syst, DK-9100 Aalborg, Denmark
关键词
Timing; Receivers; Wireless sensor networks; Power demand; Markov processes; Data collection; Actuators; query age of information; wake-up radio; content-based wake-up; WIRELESS SENSOR; ENERGY-EFFICIENT;
D O I
10.1109/LWC.2022.3225333
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Information freshness and high energy-efficiency are key requirements for sensor nodes serving Industrial Internet of Things (IIoT) applications, where a sink node must collect informative data before a deadline to control an external element. Pull-based communication is an interesting approach for optimizing information freshness and saving wasteful energy. To this end, we apply Content-based Wake-up (CoWu), in which the sink can activate a subset of nodes observing informative data at the time that wake-up signal is received. In this case, the timing of the wake-up signal plays an important role: early transmission leads to high reliability in data collection, but the received data may become obsolete by the deadline, while later transmission ensures a higher timeliness of the sensed data, but some nodes might not manage to communicate their data before the deadline. This letter investigates the timing for data collection using CoWu and characterizes the gain of CoWu. The obtained numerical results show that CoWu improves accuracy, while reducing energy consumption by about 75% with respect to round-robin scheduling.
引用
收藏
页码:327 / 331
页数:5
相关论文
共 50 条
  • [21] BEE-DRONES: Energy-efficient Data Collection on Wake-Up Radio-based Wireless Sensor Networks
    Trotta, Angelo
    Di Felice, Marco
    Bononi, Luciano
    Natalizio, Enrico
    Perilli, Luca
    Scarselli, Eleonora Franchi
    Cinotti, Tullio Salmon
    Canegallo, Roberto
    IEEE CONFERENCE ON COMPUTER COMMUNICATIONS WORKSHOPS (IEEE INFOCOM 2019 WKSHPS), 2019, : 547 - 553
  • [22] System Analysis of a Wake-Up Receiver Based on Surface Acoustic Wave Correlator
    Abughannam, Saed
    Scheytt, J. Christoph
    2018 2ND URSI ATLANTIC RADIO SCIENCE MEETING (AT-RASC), 2018,
  • [23] Energy-Efficient Data Collection Method for Sensor Networks by Integrating Asymmetric Communication and Wake-Up Radio
    Iwata, Masanari
    Tang, Suhua
    Obana, Sadao
    SENSORS, 2018, 18 (04)
  • [24] An approach to content-based approximate query processing in peer-to-peer data systems
    Wang, CK
    Li, JZ
    Shi, SF
    GRID AND COOPERATIVE COMPUTING, PT 1, 2004, 3032 : 348 - 355
  • [25] Content-Based Textual Big Data Analysis and Compression
    Gao, Fei
    Dutta, Ananya
    Liu, Jiangjiang
    2018 INTERNATIONAL CONFERENCE ON COMPUTING AND BIG DATA (ICCBD 2018), 2018, : 7 - 12
  • [26] Scaling Up Integrated Structural and Content-Based Network Analysis
    Golbeck, Jennifer
    Gerhard, Jeff
    O'Colman, Farrah
    O'Colman, Ryan
    INFORMATION SYSTEMS FRONTIERS, 2018, 20 (06) : 1191 - 1202
  • [27] Scaling Up Integrated Structural and Content-Based Network Analysis
    Jennifer Golbeck
    Jeff Gerhard
    Farrah O’Colman
    Ryan O’Colman
    Information Systems Frontiers, 2018, 20 : 1191 - 1202
  • [28] Optimal Wake-Up Time Determination Based on Sleep Cycle Analysis of Electroencephalography Signals
    Khai Le Quoc
    Linh Nguyen Khac Hoai
    Tran Nguyen Thi Bao
    Linh Huynh Quang
    2023 1ST INTERNATIONAL CONFERENCE ON HEALTH SCIENCE AND TECHNOLOGY, ICHST 2023, 2023,
  • [29] Achieving Ultra Energy-efficient and Collision-free Data Collection in Wake-up Radio Enabled mIoT
    Hsu, Chia-An
    Li, Frank Y.
    Chen, Chiuyuan
    Tseng, Yu-Chee
    ICC 2020 - 2020 IEEE INTERNATIONAL CONFERENCE ON COMMUNICATIONS (ICC), 2020,
  • [30] Thrombolysis for Wake-Up Stroke Versus Non-Wake-Up Unwitnessed Stroke: EOS Individual Patient Data Meta-Analysis
    Kamogawa, Naruhiko
    Miwa, Kaori
    Toyoda, Kazunori
    Jensen, Marit
    Inoue, Manabu
    Yoshimura, Sohei
    Fukuda-Doi, Mayumi
    Kitazono, Takanari
    Boutitie, Florent
    Ma, Henry
    Ringleb, Peter
    Wu, Ona
    Schwamm, Lee H.
    Warach, Steven
    Hacke, Werner
    Davis, Stephen M.
    Donnan, Geoffrey A.
    Gerloff, Christian
    Thomalla, Gotz
    Koga, Masatoshi
    STROKE, 2024, 55 (04) : 895 - 904