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Energy Efficient Resource Allocation and Latency Reduction in Mobile Cloud Computing Environments

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Abstract

Each mobile user in a typical multi-user mobile cloud computing (MCC) system has a number of independent tasks to do. In the modern world of finite resources and growing demands, it is critical to make the best use of multiple available resources in order to optimize their edge server placements. In this article, we explore the best ways to deploy edge servers in a cost-effective and efficient manner. The issue of reducing the quantity of edge servers while maintaining the need for access delay in MCC setting has been addressed. The selection of the fewer computational access points co-located with an edge server to ensure optimal service for all users is one of the primary issues. The other is determining how to appropriately allocate offloading tasks to edge servers. We partition the mobile networks into clusters in response to these difficulties, and the cluster heads are co-located with edge servers. We redefine the term “dominating set” and convert the problem under consideration into the dual-modeled game theory (DGT) equivalent of the minimal dominating set problem. We provide new optimizer-based techniques to find the best solutions depending on various scenarios. Resource sharing and clustering can be done using an adapted Gaussian distribution function with the whale optimization algorithm (AGDF-WOA). The offloading choices can be made by each user using AGDF-WOA-DGT progress. Its effective reduction of edge servers and load balance that leads to lower energy and cost make it a desirable option for MCC through simulations.

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Authors and Affiliations

  1. Department of Computing - Data Science, Coimbatore Institute of Technology, Coimbatore, Tamil Nadu, 641014, India

    J. Rathika

  2. Department of Information Technology, Government Arts College, Coimbatore, Tamil Nadu, 641018, India

    M. Soranamageswari

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J. Rathika Conceptualization, methodology, software, visualization, data duration, writing—original draft, validation. M. Soranamageswari resources, investigation, writing—review and editing, supervision, project administration.

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Rathika, J., Soranamageswari, M. Energy Efficient Resource Allocation and Latency Reduction in Mobile Cloud Computing Environments. Wireless Pers Commun 136, 657–687 (2024). https://doi.org/10.1007/s11277-024-11244-7

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