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Energy efficient load balancing hybrid priority assigned laxity algorithm in fog computing

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Abstract

Fog computing has the capability to provide computing resources to end-to-end devices like Internet-of-Things (IoT), thereby reducing the burden on the cloud. However, due to the growth of IoT devices and an increase in resource consumption, load balancing in fog computing has turned into a challenging task, since improper load allocation may result in underutilization and overutilization while transferring the tasks from one node to another. In order to solve these challenges, we presented an Energy-efficient load balancing algorithm named Hybrid Priority Assigned Laxity (HPAL) algorithm that allocates the tasks to a suitable Virtual Machine (VM) and completes the task within the minimum time. After the task allocation, the load balancing is handled by calculating the fog optimal time and minimum execution time. Response Time (RT), Processing Time (PT), Delay Time (DT), Execution Time (ET) and Energy Consumption (EC) are the five factors considered in this work to design an energy-efficient load balancing in Fog Nodes (FNs). The proposed algorithm carries two phases, among which in the first phase the task is allocated to each VM according to priority within the fog optimal time and in the second phase, the reallocation of tasks is executed within the minimum execution time considering the energy factor. Therefore, the task migration between the FNs is handled in an energy-efficient manner without affecting the lifetime of the FNs.

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Authors and Affiliations

  1. School of Computer Science Engineering and Technology (SCSET), Bennett University, Greater Noida, India

    Simar Preet Singh

  2. Department of Computer Science & Engineering, Thapar Institute of Engineering and Technology, Patiala, Punjab, 147001, India

    Rajesh Kumar

  3. Department of Computational Sciences, Maharaja Ranjit Singh Punjab Technical University, Bathinda, Punjab, 151001, India

    Anju Sharma

  4. Faculty of Science, Engineering and Built Environment, Deakin University, Geelong, VIC, 3220, Australia

    Jemal H. Abawajy

  5. Department of Chemical Engineering, Sant Longowal Institute of Engineering and Technology, Longowal, Sangrur, India

    Ravneet Kaur

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  1. Simar Preet Singh
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Correspondence to Simar Preet Singh.

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Singh, S.P., Kumar, R., Sharma, A. et al. Energy efficient load balancing hybrid priority assigned laxity algorithm in fog computing. Cluster Comput 25, 3325–3342 (2022). https://doi.org/10.1007/s10586-022-03554-x

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  • DOI: https://doi.org/10.1007/s10586-022-03554-x

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