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Energy and Cache Aware Routing for Socially Aware Networking in the Big Data Environment

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Abstract

In the big data environment, Socially Aware Networking (SAN) can obtain a large amount of status data and social contacts of network nodes. If the information is fully analyzed and utilized, it will effectively improve the energy efficiency and performance of SAN. To address this issue, Energy and Cache Aware Routing Algorithm (ECARA) is proposed that comprehensively utilizes node energy and cache information. First, a probability model of encounters is established by using the historical encounter information between nodes in the network. Then, the residual energy ratio of the node is introduced. They are used to predict the delivery probability of the current node. At the same time, a node cache utilization ratio model is also established. In the end, the algorithm comprehensively considers the prediction value of delivery probability and node cache utilization ratio. The optimal relay node is selected to forward the message. Through the forwarding of many relay nodes, the message is finally delivered to the destination node. Simulation results demonstrate that the ECARA exhibits a superior message delivery ratio compared to other classical algorithms. It also can effectively prevent network congestion and improve network throughput.

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Data available on request from the authors.

Code Availability

Code available on request from the authors.

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Funding

This research was supported by the MOE (Ministry of Education of China) Project of Humanities and Social Sciences (23YJAZH169), the Hubei Provincial Department of Education Outstanding Youth Scientific Innovation Team Support Foundation (T2020017), the Natural Science Foundation of Xiaogan City (XGKJ2022010095).

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Authors and Affiliations

  1. School of Computer and Information Science, Hubei Engineering Univerisity, Xiaogan, 432000, China

    Min Deng, Songhao Jiang, Fang Xu, Chunmeng Yang, Na Yang, Yuanlin Lyu, Zenggang Xiong & Manzoor Ahmed

  2. School of Computer Science and Information Engineering, Hubei University, Wuhan, 430062, China

    Songhao Jiang, Fang Xu, Chunmeng Yang, Na Yang, Yuanlin Lyu & Zenggang Xiong

  3. Artificial Intelligence Industrial Technology Research Institute, Hubei Engineering University, Xiaogan, 432000, China

    Min Deng, Fang Xu, Zenggang Xiong & Manzoor Ahmed

Authors
  1. Min Deng
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  2. Songhao Jiang
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  3. Fang Xu
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  4. Chunmeng Yang
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  5. Na Yang
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  6. Yuanlin Lyu
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  7. Zenggang Xiong
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  8. Manzoor Ahmed
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Contributions

Min Deng: Supervision, Conceptualization, Methodology, Writing Review & Editing. Songhao Jiang: Software, Validation, Formal analysis, Writing - Original Draft, Visualization. Fang Xu: Project administration, Conceptualization, Corresponding. Chunmeng Yang: Methodology, algorithm implementation. Na Yang: Visualization. Yuanlin Lyu: algorithm implementation. Zenggang Xiong: Simulation, Formal analysis. Manzoor Ahmed: Methodology, Review & Editing.

Corresponding author

Correspondence to Fang Xu.

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Deng, M., Jiang, S., Xu, F. et al. Energy and Cache Aware Routing for Socially Aware Networking in the Big Data Environment. J Sign Process Syst 96, 169–178 (2024). https://doi.org/10.1007/s11265-024-01914-x

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  • DOI: https://doi.org/10.1007/s11265-024-01914-x

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