scholarly journals Fault-Tolerance Aware Multi Objective Scheduling Algorithm for Task Scheduling in Computational Grid

2015 ◽  
Author(s):  
Dinesh Prasad Sahu ◽  
Karan Singh ◽  
Shiv Prakash
Keyword(s):  
Fault Tolerance ◽  
Task Scheduling ◽  
Scheduling Algorithm ◽  
Computational Grid ◽  
Multi Objective

Multi Objective Task Scheduling Algorithm in Cloud Computing Using the Hybridization of Particle Swarm Optimization and Cuckoo Search

2020 ◽  
Vol 17 (12) ◽  
pp. 5346-5357
Author(s):  
Sudheer Mangalampalli ◽  
Vamsi Krishna Mangalampalli ◽  
Sangram Keshari Swain
Keyword(s):  
Cloud Computing ◽  
Task Scheduling ◽  
Scheduling Algorithm ◽  
Unit Cost ◽  
Cuckoo Search ◽  
Migration Time ◽  
Total Power ◽  
It Industry ◽  
Power Cost ◽  
Multi Objective

Rapid growth has been occurred in the IT industry with the emergence of Cloud computing in terms of the resources provisioned to the users in a seamless and flexible way. Task Scheduling is a prodigious challenge in the Cloud Computing. It is difficult to schedule the continuously varying requests to schedule on continuously varying resources. The existing approaches haven’t considered all the metrics while considering only the metrics like makespan and waiting time. In this paper, our focus is to formulate a Multi objective approach which is used to optimally map and load balance the tasks in the cloud by calculating the task priority and VM priority based on the electricity price per unit cost while minimizing the makespan, migration time and the power cost in the datacenters. The proposed algorithm is modeled using the hybridized approach by combining PSO and Cuckoo search algorithms. It is simulated on cloudsim simulator and it is compared against the basic ACO, GA, PSO and CS algorithms and our algorithm is outperformed against these basic algorithms with concerned parameters such as makespan, Migration time and the Total Power cost in the datacenters.

Multi-objective task scheduling in cloud computing environment by hybridized bat algorithm

2021 ◽  
pp. 1-13
Author(s):  
Timea Bezdan ◽  
Miodrag Zivkovic ◽  
Nebojsa Bacanin ◽  
Ivana Strumberger ◽  
Eva Tuba ◽  
...  
Keyword(s):  
Cloud Computing ◽  
Task Scheduling ◽  
Scheduling Algorithm ◽  
Search Time ◽  
Optimal Solution ◽  
Bat Algorithm ◽  
Search Space ◽  
Resource Provisioning ◽  
New Paradigm ◽  
Multi Objective

Cloud computing represents relatively new paradigm of utilizing remote computing resources and is becoming increasingly important and popular technology, that supports on-demand (as needed) resource provisioning and releasing in almost real-time. Task scheduling has a crucial role in cloud computing and it represents one of the most challenging issues from this domain. Therefore, to establish more efficient resource employment, an effective and robust task allocation (scheduling) method is required. By using an efficient task scheduling algorithm, the overall performance and service quality, as well as end-users experience can be improved. As the number of tasks increases, the problem complexity rises as well, which results in a huge search space. This kind of problem belongs to the class of NP-hard optimization challenges. The objective of this paper is to propose an approach that is able to find approximate (near-optimal) solution for multi-objective task scheduling problem in cloud environment, and at the same time to reduce the search time. In the proposed manuscript, we present a swarm-intelligence based approach, the hybridized bat algorithm, for multi-objective task scheduling. We conducted experiments on the CloudSim toolkit using standard parallel workloads and synthetic workloads. The obtained results are compared to other similar, metaheuristic-based techniques that were evaluated under the same conditions. Simulation results prove great potential of our proposed approach in this domain.

scholarly journals Multi-objective Task Scheduling Algorithm Based on Harmony Search for Grid Microservice Optimization

2021 ◽  
Vol 1746 ◽  
pp. 012040
Author(s):  
Yuqing Xie ◽  
Yuan Wang ◽  
Ying Jiang ◽  
Zirong Peng ◽  
Yongli Wang
Keyword(s):  
Task Scheduling ◽  
Scheduling Algorithm ◽  
Harmony Search ◽  
Multi Objective ◽  
Task Scheduling Algorithm
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