An Efficient Max-Min Resource Allocator and Task Scheduling Algorithm in Cloud Computing Environment

Konjaang, J. Kok; Maipan-uku, J.Y; Kubuga, Kumangkem Kennedy

doi:10.48550/arxiv.1611.08864

Cited by 1 publication

(1 citation statement)

References 0 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The developed algorithm is based on the Prediction of Tasks Computation Time (PTCT) approach. Experiments are run using MATLAB R2013a to evaluate the proposed algorithm and to compare it with four other algorithms: Enhanced Min-Min (Patel, et al, 2015), An Efficient Max-Min (Konjaang, et al, 2016), QoS guided (Han, et al, 2013) and MiM-MaM (Kfatheen & Banu, 2015), developed for heterogeneous systems. The authors claimed that the advanced algorithm provided a significant improvement in tasks makespan, tasks execution time and other parameters and reduced the computation and complexity by using the Principal Components Analysis (PCA) and reduced the Expected Time to Compute (ETC) matrix.…”

Section: Execution Time or Makespan Based Criteriamentioning

confidence: 99%

Classification and Performance Study of Task Scheduling Algorithms in Cloud Computing Environment

2022

IKM

View full text Add to dashboard Cite

Cloud computing is becoming very common in recent years and is growing rapidly due to its attractive benefits and features such as resource pooling, accessibility, availability, scalability, reliability, cost saving, security, flexibility, on-demand services, pay-per-use services, use from anywhere, quality of service, resilience, etc. With this rapid growth of cloud computing, there may exist too many users that require services or need to execute their tasks simultaneously by resources provided by service providers. To get these services with the best performance, and minimum cost, response time, makespan, effective use of resources, etc. an intelligent and efficient task scheduling technique is required and considered as one of the main and essential issues in the cloud computing environment. It is necessary for allocating tasks to the proper cloud resources and optimizing the overall system performance. To this end, researchers put huge efforts to develop several classes of scheduling algorithms to be suitable for the various computing environments and to satisfy the needs of the various types of individuals and organizations. This research article provides a classification of proposed scheduling strategies and developed algorithms in cloud computing environment along with the evaluation of their performance. A comparison of the performance of these algorithms with existing ones is also given. Additionally, the future research work in the reviewed articles (if available) is also pointed out. This research work includes a review of 88 task scheduling algorithms in cloud computing environment distributed over the seven scheduling classes suggested in this study. Each article deals with a novel scheduling technique and the performance improvement it introduces compared with previously existing task scheduling algorithms.

show abstract

Section: Execution Time or Makespan Based Criteriamentioning

confidence: 99%

Classification and Performance Study of Task Scheduling Algorithms in Cloud Computing Environment

2022

IKM

View full text Add to dashboard Cite

show abstract

An Efficient Max-Min Resource Allocator and Task Scheduling Algorithm in Cloud Computing Environment

Cited by 1 publication

References 0 publications

Classification and Performance Study of Task Scheduling Algorithms in Cloud Computing Environment

Classification and Performance Study of Task Scheduling Algorithms in Cloud Computing Environment

Contact Info

Product

Resources

About