SciELO - Scientific Electronic Library Online

 
vol.27 número2Cyber Hygiene in Smart Metering SystemsAdding Semantics for Solving ‘PP Attachment’ in Spanish índice de autoresíndice de assuntospesquisa de artigos
Home Pagelista alfabética de periódicos  

Serviços Personalizados

Journal

Artigo

Indicadores

Links relacionados

  • Não possue artigos similaresSimilares em SciELO

Compartilhar


Computación y Sistemas

versão On-line ISSN 2007-9737versão impressa ISSN 1405-5546

Resumo

MATHUR, Robin Prakash  e  SHARMA, Manmohan. A Multi-Objective Task Scheduling Scheme GMOPSO-BFO in Mobile Cloud Computing. Comp. y Sist. [online]. 2023, vol.27, n.2, pp.477-488.  Epub 18-Set-2023. ISSN 2007-9737.  https://doi.org/10.13053/cys-27-2-3953.

Mobile cloud computing is currently an encouraging field in the cyber-physical world. It is an amalgamation of mobile computing and cloud computing. Computational offloading is one feature in the mobile cloud application that offloads the task to the cloud server, processes it, and gets the results back on the mobile device. During offload, the job needs to be queued on the cloud servers and allocated to the virtual machines. Task scheduling is an important step where the mobile task is assigned to the servers and processed somehow. In the overall offloading process, energy conservation is a significant concern. The scheduling problem involves mapping the offloaded task to the cloud server while satisfying the energy and time constraints. This paper proposes a hybrid scheduling scheme based on Gaussian-based multi-objective particle swarm optimization(GMOPSO) and bacterial foraging optimization(BFO). This scheme performs better when compared to other variants of PSO in terms of makespan and energy efficiency.

Palavras-chave : Computational offloading; mobile cloud computing; MOPSO; bacteria foraging optimization; energy consumption; makespan.

        · texto em Inglês     · Inglês ( pdf )