Immediate/on-line and Batch mode heuristics are two methods used for scheduling in the computatio... more Immediate/on-line and Batch mode heuristics are two methods used for scheduling in the computational grid environment. In the former, task is mapped onto a resource as soon as it arrives at the scheduler, while the later, tasks are not mapped onto resource as they arrive, instead they are collected into a set that is examined for mapping at prescheduled times called mapping events. This paper reviews the literature concerning Minimum Execution Time (MET) along with Minimum Completion Time (MCT) algorithms of online mode heuristics and more emphasis on Min-Min along with Max-Min algorithms of batch mode heuristics, while focusing on the details of their basic concepts, approaches, techniques, and open problems.
International Journal of Research -GRANTHAALAYAH, 2017
Immediate/on-line and Batch mode heuristics are two methods used for scheduling in the computatio... more Immediate/on-line and Batch mode heuristics are two methods used for scheduling in the computational grid environment. In the former, task is mapped onto a resource as soon as it arrives at the scheduler, while the later, tasks are not mapped onto resource as they arrive, instead they are collected into a set that is examined for mapping at prescheduled times called mapping events. This paper reviews the literature concerning Minimum Execution Time (MET) along with Minimum Completion Time (MCT) algorithms of online mode heuristics and more emphasis on Min-Min along with Max-Min algorithms of batch mode heuristics, while focusing on the details of their basic concepts, approaches, techniques, and open problems.
The demand for high computational power has developed more rapidly in the past few years. The eve... more The demand for high computational power has developed more rapidly in the past few years. The ever-increasing lack of computational resources are less able to satisfy these needs, leading to the development of grid computing. This technology was able to fulfill the increasing demand for computational power, storage capacity, bandwidth availability and resources. Grid computing is considered as a distributed system that utilises resources from multiple geographically distributed computers. This system usually handles workloads that are not interactive and include huge amount of data. The current challenge facing researchers is to determine the optimal task scheduling method that provides optimal resource utilisation in this extremely heterogeneous environment. The main goal of this work is to present an evaluation of resources utilisation for certain heuristic scheduling algorithms in Grid Computing Environment. The results of the two experimental scenarios showed that suf rage algor...
International Journal of Computer Applications, 2016
Cloud computing is a new archetype that provides dynamic computing services to cloud users throug... more Cloud computing is a new archetype that provides dynamic computing services to cloud users through the support of datacenters that employs the services of datacenter brokers which discover resources and assign them Virtually. The focus of this research is to efficiently optimize resource allocation in the cloud by exploiting the Max-Min scheduling algorithm and enhancing it to increase efficiency in terms of completion time (makespan). This is key to enhancing the performance of cloud scheduling and narrowing the performance gap between cloud service providers and cloud resources consumers/users. The current Max-Min algorithm selects tasks with maximum execution time on a faster available machine or resource that is capable of giving minimum completion time. The concern of this algorithm is to give priority to tasks with maximum execution time first before assigning those with the minimum execution time for the purpose of minimizing makespan. The drawback of this algorithm is that, the execution of tasks with maximum execution time first may increase the makespan, and leads to a delay in executing tasks with minimum execution time if the number of tasks with maximum execution time exceeds that of tasks with minimum execution time, hence the need to improve it to mitigate the delay in executing tasks with minimum execution time. CloudSim is used to compare the effectiveness of the improved Max-Min algorithm with the traditional one. The experimented results show that the improved algorithm is efficient and can produce better makespan than Max-Min and DataAware.
An Extended Min-Min Scheduling Algorithm in Cloud Computing
—Cloudlet scheduling seems to be the most fundamental problem of cloud computing as per Infrastru... more —Cloudlet scheduling seems to be the most fundamental problem of cloud computing as per Infrastructure as a Service (IaaS). Proper scheduling in cloud lead to load balancing, minimization of makespan, and adequate resources utilization. To meet consumers' expectations, the execution of cloudlet simultaneously is required. Many algorithms have been implemented to solve the cloud scheduling problem. This include Min-Min which gave priority to cloudlet with minimum completion time. Min-Min scheduling algorithm has two clear weaknesses; a high value of makespan being generated and low resource utilization. To address these problems, this research proposes an Extended Min-Min Algorithm which assign cloudlet base on the differences between maximum and minimum execution time of cloudlets. Cloudsim was used to implement and compare the performances of the proposed algorithm with the benchmarks. The results of the extensive experiments show that the proposed algorithm is able to performed better in terms of makespan minimization in compare to the existing heuristics.
Immediate/on-line and Batch mode heuristics are two methods used for scheduling in the computatio... more Immediate/on-line and Batch mode heuristics are two methods used for scheduling in the computational grid environment. In the former, task is mapped onto a resource as soon as it arrives at the scheduler, while the later, tasks are not mapped onto resource as they arrive, instead they are collected into a set that is examined for mapping at prescheduled times called mapping events. This paper reviews the literature concerning Minimum Execution Time (MET) along with Minimum Completion Time (MCT) algorithms of online mode heuristics and more emphasis on Min-Min along with Max-Min algorithms of batch mode heuristics, while focusing on the details of their basic concepts, approaches, techniques, and open problems.
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Papers by Jamilu Yahaya