Multi criteria biased randomized method for resource allocation in distributed systems
Volunteer computing is a type of distributed computing in which a part or all the resources (processing power and storage) necessary to run the system are donated by users. In other words, participants contribute their idle computing resources to help running the system. Due to the fact that the nod...
| Autores: | , , , |
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| Tipo de recurso: | artículo |
| Fecha de publicación: | 2018 |
| País: | España |
| Institución: | Universitat Autònoma de Barcelona |
| Repositorio: | Dipòsit Digital de Documents de la UAB |
| Idioma: | inglés |
| OAI Identifier: | oai:ddd.uab.cat:294242 |
| Acceso en línea: | https://ddd.uab.cat/record/294242 https://dx.doi.org/urn:doi:10.1016/j.future.2017.11.039 |
| Access Level: | acceso abierto |
| Palabra clave: | Allocation methods Distributed computing Resource provisioning User assignment Volunteer systems |
| Sumario: | Volunteer computing is a type of distributed computing in which a part or all the resources (processing power and storage) necessary to run the system are donated by users. In other words, participants contribute their idle computing resources to help running the system. Due to the fact that the nodes which compose the system are provided by a large number of users instead of a single (or a few) institution, a main drawback of volunteer computing is the unreliability of these nodes. For this reason, the selection of nodes to be involved in each task becomes a key issue. In this paper, we propose the Multi Criteria Biased Randomized (MCBR) method, a novel selection method for large-scale systems that use unreliable nodes. MCBR method is based on a multicriteria optimization strategy. We evaluated the method in a microblogging social network formed by a large number of microservices hosted in nodes voluntarily contributed by their participants. Simulation results show that our proposal is able to select nodes in a fast and efficient manner while requiring low computational power. |
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