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GSAGA: A hybrid algorithm for task scheduling in cloud infrastructure

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Abstract

Cloud computing is becoming a very popular form of distributed computing, in which digital resources are shared via the Internet. The user is provided with an overview of many available resources. Cloud providers want to get the most out of their resources, and users are inclined to pay less for better performance. Task scheduling is one of the most important aspects of cloud computing. In order to achieve high performance from cloud computing systems, tasks need to be scheduled for processing by appropriate computing resources. The large search space of this issue makes it an NP-hard problem, and more random search methods are required to solve this problem. Multiple solutions have been proposed with several algorithms to solve this problem until now. This paper presents a hybrid algorithm called GSAGA to solve the Task Scheduling Problem (TSP) in cloud computing. Although it has a high ability to search the problem space, the Genetic Algorithm (GA) performs poorly in terms of stability and local search. It is therefore possible to create a stable algorithm by combining the general search capacities of the GA with the Gravitational Search Algorithm (GSA). Our experimental results indicate that the proposed algorithm can solve the problem with higher efficiency compared with the state-of-the-art.

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Author information

Authors and Affiliations

  1. School of Computer and Software, Dalian Neusoft University of Information, Dalian, 116023, China

    Poria Pirozmand

  2. ADiT-Lab, Electrotechnics and Telecommunications Department, Instituto Politécnico de Viana do Castelo, Porto, Portugal

    Amir Javadpour & Pedro Pinto

  3. Department of Computer Science and Technology, Harbin Institute of Technology, Shenzhen, China

    Amir Javadpour

  4. Department of Management, Alzahra University, Tehran, Iran

    Hamideh Nazarian

  5. Department of Computer Engineering and IT, Payame Noor University (PNU), Tehran, Iran

    Seyedsaeid Mirkamali

  6. Department of Computer Engineering, Sharif University of Technology, Tehran, Iran

    Forough Ja’fari

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  1. Poria Pirozmand
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Correspondence to Amir Javadpour.

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Pirozmand, P., Javadpour, A., Nazarian, H. et al. GSAGA: A hybrid algorithm for task scheduling in cloud infrastructure. J Supercomput 78, 17423–17449 (2022). https://doi.org/10.1007/s11227-022-04539-8

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