An efficient routing protocol for wireless body sensor networks using reinforced learning algorithm in clusters

被引:0
|
作者
Jayabalan E. [1 ]
Pugazendi R. [1 ]
机构
[1] Department of Computer Science, Government Arts College (A), Tamil Nadu, Salem
来源
Measurement: Sensors | 2023年 / 27卷
关键词
Cluster based approach; Q-learning algorithm; Reinforcement learning; Wireless body sensor networks;
D O I
10.1016/j.measen.2023.100730
中图分类号
学科分类号
摘要
Wireless body sensor networks are intelligent enough to efficiently sense the signals for vital parameters of the patient, which aids in offering a better healthcare facility to the patients. Wearable bio-sensors with networking capability have led to the possibility of implementing WBSN and thus promising health care facility can be offered to the community with this upcoming technology. These WBSN basically consist of few sensors or nodes that observe the vital parameters of the patient and communicate them to the required destination with the help of the intermediate nodes, through the best possible paths. This paper proposes a Cluster-based routing Protocol using reinforcement learning with Q-Learning approach to achieve optimal route. Simulations are carried with a set of biomedical sensors covering an area of 1000 × 1000 m2. The simulation is carried out for … seconds. The reinforcement algorithm has been found to route the packets faster when compared with other algorithms. © 2023 The Authors
引用
收藏
相关论文
共 50 条
  • [21] Wireless communication protocol based on EDF for wireless body sensor networks
    Aquino-Santos, Raul
    Potes, Apolinar Gonzalez
    Rangel-Licea, Victor
    Garcia-Ruiz, Miguel A.
    Villasenor-Gonzalez, L. A.
    Edwards-Block, Arthur
    JOURNAL OF APPLIED RESEARCH AND TECHNOLOGY, 2008, 6 (02) : 120 - 130
  • [22] INTRODUCING A NEW ROUTING ALGORITHM FOR WIRELESS NETWORKS ON CHIP USING REINFORCEMENT LEARNING
    Harati, Zohreh
    Tahanian, Esmaeel
    Tajary, Alireza
    Fateh, Mansoor
    JORDANIAN JOURNAL OF COMPUTERS AND INFORMATION TECHNOLOGY, 2021, 7 (03): : 239 - 252
  • [23] Adaptive Routing in Wireless Mesh Networks Using Hybrid Reinforcement Learning Algorithm
    Mahajan, Smita
    HariKrishnan, R.
    Kotecha, Ketan
    IEEE ACCESS, 2022, 10 : 107961 - 107979
  • [24] Efficient Security Mechanisms for mHealth Applications Using Wireless Body Sensor Networks
    Sahoo, Prasan Kumar
    SENSORS, 2012, 12 (09) : 12606 - 12633
  • [25] Reinforcement Learning Aided Routing in Tactical Wireless Sensor Networks
    Okine, Andrews A.
    Adam, Nadir
    Kaddoum, Georges
    UBIQUITOUS NETWORKING, UNET 2022, 2023, 13853 : 211 - 224
  • [26] A Tailored Q-Learning for Routing in Wireless Sensor Networks
    Sharma, Varun K.
    Shukla, Shiv Shankar Prasad
    Singh, Varun
    2012 2ND IEEE INTERNATIONAL CONFERENCE ON PARALLEL, DISTRIBUTED AND GRID COMPUTING (PDGC), 2012, : 663 - 668
  • [27] Energy efficient and reliable routing in wireless body area networks based on reinforcement learning and fuzzy logic
    Wenjing Guo
    Yiran Wang
    Yanglan Gan
    Ting Lu
    Wireless Networks, 2022, 28 : 2669 - 2693
  • [28] QTAR: A Q-learning-based topology-aware routing protocol for underwater wireless sensor networks*
    Nandyala, Chandra Sukanya
    Kim, Hee-Won
    Cho, Ho-Shin
    COMPUTER NETWORKS, 2023, 222
  • [29] Intelligent routing algorithm for wireless sensor networks dynamically guided by distributed neural networks
    Liu, Zhibin
    Liu, Yuhan
    Wang, Xinshui
    COMPUTER COMMUNICATIONS, 2023, 207 : 100 - 112
  • [30] An Enhanced Tree Routing Based on Reinforcement Learning in Wireless Sensor Networks
    Kim, Beom-Su
    Suh, Beomkyu
    Seo, In Jin
    Lee, Han Byul
    Gong, Ji Seon
    Kim, Ki-Il
    SENSORS, 2023, 23 (01)