Optimization of resource-aware parallel and distributed computing: a review

This paper presents a review of state-of-the-art solutions concerning the optimization of computing in the field of parallel and distributed systems. Firstly, we contribute by identifying resources and quality metrics in this context including servers, network interconnects, storage systems, computa...

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Veröffentlicht in:	The Journal of supercomputing Jg. 81; H. 7; S. 848
Hauptverfasser:	Czarnul, Paweł, Antal, Marcel, Baniata, Hamza, Griebler, Dalvan, Kertesz, Attila, Kessler, Christoph W., Kouloumpris, Andreas, Kovačić, Salko, Markus, Andras, Michael, Maria K., Nikolaou, Panagiota, Öz, Isil, Prodan, Radu, Rakić, Gordana
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	New York Springer Nature B.V 09.05.2025
Schlagworte:	Algorithms Ant colony optimization Blockchain Cloud computing Computer centers Computer networks Distributed processing Dynamic programming Energy consumption Game theory Genetic algorithms Greedy algorithms High performance computing Integer programming Internet of Things Linear programming Optimization Particle swarm optimization Power Software State-of-the-art reviews Storage systems Workloads Parallel and distributed architectures Parallel and distributed computing Optimization Review of resource-aware parallel and distributed computing
ISSN:	1573-0484, 0920-8542, 1573-0484
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Abstract	This paper presents a review of state-of-the-art solutions concerning the optimization of computing in the field of parallel and distributed systems. Firstly, we contribute by identifying resources and quality metrics in this context including servers, network interconnects, storage systems, computational devices as well as execution time/performance, energy, security, and error vulnerability, respectively. We subsequently identify commonly used problem formulations and algorithms for integer linear programming, greedy algorithms, dynamic programming, genetic algorithms, particle swarm optimization, ant colony optimization, game theory, and reinforcement learning. Afterward, we characterize frequently considered optimization problems by stating these terms in domains such as data centers, cloud, fog, blockchain, high performance, and volunteer computing. Based on the extensive analysis, we identify how particular resources and corresponding quality metrics are considered in these domains and which problem formulations are used for which system types, either parallel or distributed environments. This allows us to formulate open research problems and challenges in this field and analyze research interest in problem formulations/domains in recent years.
AbstractList	This paper presents a review of state-of-the-art solutions concerning the optimization of computing in the field of parallel and distributed systems. Firstly, we contribute by identifying resources and quality metrics in this context including servers, network interconnects, storage systems, computational devices as well as execution time/performance, energy, security, and error vulnerability, respectively. We subsequently identify commonly used problem formulations and algorithms for integer linear programming, greedy algorithms, dynamic programming, genetic algorithms, particle swarm optimization, ant colony optimization, game theory, and reinforcement learning. Afterward, we characterize frequently considered optimization problems by stating these terms in domains such as data centers, cloud, fog, blockchain, high performance, and volunteer computing. Based on the extensive analysis, we identify how particular resources and corresponding quality metrics are considered in these domains and which problem formulations are used for which system types, either parallel or distributed environments. This allows us to formulate open research problems and challenges in this field and analyze research interest in problem formulations/domains in recent years.
ArticleNumber	848
Author	Kovačić, Salko Czarnul, Paweł Kouloumpris, Andreas Antal, Marcel Öz, Isil Kessler, Christoph W. Markus, Andras Nikolaou, Panagiota Kertesz, Attila Prodan, Radu Griebler, Dalvan Baniata, Hamza Michael, Maria K. Rakić, Gordana
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Snippet	This paper presents a review of state-of-the-art solutions concerning the optimization of computing in the field of parallel and distributed systems. Firstly,...
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SubjectTerms	Algorithms Ant colony optimization Blockchain Cloud computing Computer centers Computer networks Distributed processing Dynamic programming Energy consumption Game theory Genetic algorithms Greedy algorithms High performance computing Integer programming Internet of Things Linear programming Optimization Particle swarm optimization Power Software State-of-the-art reviews Storage systems Workloads
Title	Optimization of resource-aware parallel and distributed computing: a review
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