Energy-efficient and Secure Wireless Communication for Telemedicine in IoT

被引:3
作者
Joshi, Shital [1 ]
Manimurugan, S. [2 ,3 ]
Aljuhani, Ahamed [2 ]
Albalawi, Umar [2 ]
Aljaedi, Amer [2 ]
机构
[1] Oklahoma State Univ, Dept Comp Sci, Stillwater, OK 74078 USA
[2] Univ Tabuk, Coll Comp & Informat Technol, Tabuk 71491, Saudi Arabia
[3] Univ Tabuk, Ind Innovat & Robot Ctr, Tabuk, Saudi Arabia
来源
COMPUTER SYSTEMS SCIENCE AND ENGINEERING | 2022年 / 43卷 / 03期
关键词
Energy-efficiency; energy consumption; Internet of Things; telemedicine; INTERNET; THINGS;
D O I
10.32604/csse.2022.024802
中图分类号
TP3 [计算技术、计算机技术];
学科分类号
0812 ;
摘要
The Internet of Things (IoT) represents a radical shifting paradigm for technological innovations as it can play critical roles in cyberspace applications in various sectors, such as security, monitoring, medical, and environmental sectors, and also in control and industrial applications. The IoT in E-medicine unleashed the design space for new technologies to give instant treatment to patients while also monitoring and tracking health conditions. This research presents a systemlevel architecture approach for IoT energy efficiency and security. The proposed architecture includes functional components that provide privacy management and system security. Components in the security function group provide secure communications through Multi-Authority Ciphertext-Policy Attributes-Based Encryption (MA-CPABE). Because MA-CPABE is assigned to unlimited devices, presuming that the devices are reliable, the user encodes data with Advanced Encryption Standard (AES) and protects the ABE approach using the solutions of symmetric key. The Johnson's algorithm with a new computation measure is used to increase network lifetime since an individual sensor node with limited energy represents the inevitable constraints for the broad usage of wireless sensor networks. The optimal route from a source to destination turns out as the cornerstone for longevity of network and its sustainability. To reduce the energy consumption of networks, the evaluation measures consider the node's residual energy, the number of neighbors, their distance, and the link dependability. The experiment results demonstrate that the proposed model increases network life and Dijkstra's algorithms, lowering consumption of energy by eliminating the necessity for re-routing the message as a result of connection failure.
引用
收藏
页码:1111 / 1130
页数:20
相关论文
共 43 条
  • [21] Review and Comparison of Spatial Localization Methods for Low-Power Wireless Sensor Networks
    Iliev, Nick
    Paprotny, Igor
    [J]. IEEE SENSORS JOURNAL, 2015, 15 (10) : 5971 - 5987
  • [22] Jebri S, 2017, INT WIREL COMMUN, P365, DOI 10.1109/IWCMC.2017.7986314
  • [23] Joshi S, 2017, 2017 IEEE INTERNATIONAL CONFERENCE ON POWER, CONTROL, SIGNALS AND INSTRUMENTATION ENGINEERING (ICPCSI), P3116, DOI 10.1109/ICPCSI.2017.8392299
  • [24] Khaan P., 2014, ANN IEEE INDIAN C, P1
  • [25] Manjeswar A., 2001, INT WORKSH PAR DISTR, P2009
  • [26] Reinforcement learning-enabled Intelligent Device-to-Device (I-D2D) communication in Narrowband Internet of Things (NB-IoT)
    Nauman, Ali
    Jamshed, Muhammad Ali
    Ali, Rashid
    Cengiz, Korhan
    Zulqarnain
    Kim, Sung Won
    [J]. COMPUTER COMMUNICATIONS, 2021, 176 : 13 - 22
  • [27] Ok C., 2007, IEEE INT C AUTOMATIO, P906
  • [28] Okwu M., 2020, J. Mech. Energy Eng., V4, P33
  • [29] Pawar AB, 2016, 2016 INTERNATIONAL CONFERENCE ON COMPUTING, ANALYTICS AND SECURITY TRENDS (CAST), P294, DOI 10.1109/CAST.2016.7914983
  • [30] Ramtin A., 2021, PERFORM EVALUATION, V151, P1