2018_EJRNL_PP_Sobhanayak_Srichandan_1.pdf
Terbatas Irwan Sofiyan
» ITB
Terbatas Irwan Sofiyan
» ITB
2019_TA_PP_LASTRI_NAIBAHO_1-ABSTRAK1.pdf
PUBLIC Irwan Sofiyan 2019_TA_PP_LASTRI_NAIBAHO_1-ABSTRAK11.pdf
PUBLIC Irwan Sofiyan
Cloud computing is the delivery of computing services over the internet. Cloud services allow individuals and other businesses organization
to use data that are managed by third parties or another person at remote locations. Most Cloud providers support services under constraints of
Service Level Agreement (SLA) definitions. The SLAs are composed of different quality of service (QoS) rules promised by the provider.
A cloud environment can be classified into two types: computing clouds and data clouds. In computing cloud, task scheduling plays a vital role
in maintaining the quality of service and SLA. Efficient task scheduling is one of the major steps for effectively harnessing the potential of cloud
computing. This paper explores the task scheduling algorithm using a hybrid approach, which combines desirable characteristics of two of the
most widely used biologically-inspired heuristic algorithms, the genetic algorithms (GAs) and the bacterial foraging (BF) algorithms in the
computing cloud. The main contributions of this article are twofold. First, the scheduling algorithm minimizes the makespan and second; it
reduces the energy consumption, both economic and ecological perspectives. Experimental results show that the performance of the proposed
algorithm outperforms than those of other algorithms regarding convergence, stability, and solution diversity.