A Hybrid Heuristic Algorithm Using Artificial Agents for Data Replication Problem in Distributed Systems

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Udgivet i:Symmetry vol. 15, no. 2 (2023), p. 487
Hovedforfatter: Arasteh, Bahman
Andre forfattere: Seyed Salar Sefati, Halunga, Simona, Fratu, Octavian, Tofigh Allahviranloo
Udgivet:
MDPI AG
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022 |a 2073-8994 
024 7 |a 10.3390/sym15020487  |2 doi 
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100 1 |a Arasteh, Bahman  |u Department of Software Engineering, Faculty of Engineering and Natural Science, Istinye University, Istanbul 34460, Turkey 
245 1 |a A Hybrid Heuristic Algorithm Using Artificial Agents for Data Replication Problem in Distributed Systems 
260 |b MDPI AG  |c 2023 
513 |a Journal Article 
520 3 |a One of the key issues with large distributed systems, such as IoT platforms, is gaining timely access to data objects. As a result, decreasing the operation time of reading and writing data in distributed communication systems become essential demands for asymmetric system. A common method is to replicate the data objects across multiple servers. Replica placement, which can be performed statically or dynamically, is critical to the effectiveness of distributed systems in general. Replication and placing them on the best available data servers in an optimal manner is an NP-complete optimization problem. As a result, several heuristic strategies for replica placement in distributed systems have been presented. The primary goals of this research are to reduce the cost of data access time, reduce the number of replicas, and increase the reliability of the algorithms for placing replicas. In this paper, a discretized heuristic algorithm with artificial individuals and a hybrid imitation method were developed. In the proposed method, particle and gray-wolf-based individuals use a local memory and velocity to search for optimal solutions. The proposed method includes symmetry in both local and global searches. Another contribution of this research is the development of the proposed optimization algorithm for solving the data object replication problem in distributed systems. Regarding the results of simulations on the standard benchmark, the suggested method gives a 35% reduction in data access time with about six replicates. Furthermore, the standard deviation among the results obtained by the proposed method is about 0.015 which is lower than the other methods in the same experiments; hence, the method is more stable than the previous methods during different executions. 
653 |a Customer services 
653 |a Velocity 
653 |a Placement 
653 |a Agents (artificial intelligence) 
653 |a Data replication 
653 |a Optimization 
653 |a Communications systems 
653 |a Algorithms 
653 |a Methods 
653 |a System effectiveness 
653 |a Access time 
653 |a Cloud computing 
653 |a Workloads 
653 |a Servers 
653 |a Heuristic methods 
653 |a Computer networks 
653 |a Efficiency 
700 1 |a Seyed Salar Sefati  |u Faculty of Electronics, Telecommunications and Information Technology, University Politehnica of Bucharest, 060042 București, Romania 
700 1 |a Halunga, Simona  |u Faculty of Electronics, Telecommunications and Information Technology, University Politehnica of Bucharest, 060042 București, Romania 
700 1 |a Fratu, Octavian  |u Faculty of Electronics, Telecommunications and Information Technology, University Politehnica of Bucharest, 060042 București, Romania 
700 1 |a Tofigh Allahviranloo  |u Department of Software Engineering, Faculty of Engineering and Natural Science, Istinye University, Istanbul 34460, Turkey 
773 0 |t Symmetry  |g vol. 15, no. 2 (2023), p. 487 
786 0 |d ProQuest  |t Engineering Database 
856 4 1 |3 Citation/Abstract  |u https://www.proquest.com/docview/2779626705/abstract/embedded/7BTGNMKEMPT1V9Z2?source=fedsrch 
856 4 0 |3 Full Text + Graphics  |u https://www.proquest.com/docview/2779626705/fulltextwithgraphics/embedded/7BTGNMKEMPT1V9Z2?source=fedsrch 
856 4 0 |3 Full Text - PDF  |u https://www.proquest.com/docview/2779626705/fulltextPDF/embedded/7BTGNMKEMPT1V9Z2?source=fedsrch