scholarly journals HAMM: A Hybrid Algorithm of Min-Min and Max-Min Task Scheduling Algorithms in Cloud Computing

2020 ◽  
Vol 9 (4) ◽  
pp. 209-218
Keyword(s):  
Cloud Computing ◽  
Load Balancing ◽  
Task Scheduling ◽  
Hybrid Algorithm ◽  
Heuristic Algorithms ◽  
Scheduling Algorithms ◽  
Cloud Computing Environment ◽  
Concurrent Execution ◽  
Optimization Parameters ◽  
Better Than

Nowadays, with the huge development of information and computing technologies, the cloud computing is becoming the highly scalable and widely computing technology used in the world that bases on pay-per-use, remotely access, Internet-based and on-demand concepts in which providing customers with a shared of configurable resources. But, with the highly incoming user’s requests, the task scheduling and resource allocation are becoming major requirements for efficient and effective load balancing of a workload among cloud resources to enhance the overall cloud system performance. For these reasons, various types of task scheduling algorithms are introduced such as traditional, heuristic, and meta-heuristic. A heuristic task scheduling algorithms like MET, MCT, Min-Min, and Max-Min are playing an important role for solving the task scheduling problem. This paper proposes a new hybrid algorithm in cloud computing environment that based on two heuristic algorithms; Min-Min and Max-Min algorithms. To evaluate this algorithm, the Cloudsim simulator has been used with different optimization parameters; makespan, average of resource utilization, load balancing, average of waiting time and concurrent execution between small length tasks and long size tasks. The results show that the proposed algorithm is better than the two algorithms Min-Min and Max-Min for those parameters

scholarly journals An efficient Task Scheduling and Load Balancing in Cloud Computing using KD-Tree Algorithm

2019 ◽  
Vol 9 (2) ◽  
pp. 2426-2433
Keyword(s):  
Cloud Computing ◽  
Load Balancing ◽  
Task Scheduling ◽  
Heuristic Algorithms ◽  
Research Work ◽  
Tree Algorithm ◽  
Cloud Resource Management ◽  
High Resource ◽  
Cloud Resource ◽  
And Task

Cloud Computing provides the sharing ability and access for available cloud host and various distributed environments, namely Load Balancing (LB), virtualization technologies and scheduling techniques. The satisfaction of both users and cloud providers are the major issues for effective LB and task scheduling algorithms in cloud resource management, where the requirements namely high resource utilization, low monetary costs and minimum makespan. Many researchers tried to develop various heuristic and meta-heuristic algorithms to attain the aforementioned user requirements. But, when the number of tasks grows exponentially, these algorithms failed to achieve LB, lower running time, and it faces the high time complexity. In this research work, a KD-Tree algorithm is developed to address the issues of heuristic algorithms and provide efficient LB by partitioning the environments into several tasks. According to the deadline of task execution, the remaining tasks are adjusted dynamically by the proposed KD-tree algorithm in the virtual environment. The experiments are conducted to evaluate the efficiency of KD-Tree algorithm with existing heuristic techniques by using makespan, energy consumption and task migrations. When the number of tasks is 20, the proposed KD-Tree algorithm achieved 71.33% makespan and 5% task migrations.

scholarly journals Task Scheduling Algorithms in Cloud Computing: A Review

2021 ◽  
Vol 12 (4) ◽  
pp. 1041-1053
Author(s):  
Ibrahim Mahmood Ibrahim, Et. al.
Keyword(s):  
Cloud Computing ◽  
Task Scheduling ◽  
Completion Time ◽  
Scheduling Algorithms ◽  
Task Completion ◽  
The Internet ◽  
Computing Environment ◽  
Cloud Computing Environment

Cloud computing is the requirement based on clients and provides many resources that aim to share it as a service through the internet. For optimal use, Cloud computing resources such as storage, application, and other services need managing and scheduling these services. The principal idea behind the scheduling is to minimize loss time, workload, and maximize throughput. So, the scheduling task is essential to achieve accuracy and correctness on task completion. This paper gives an idea about various task scheduling algorithms in the cloud computing environment used by researchers. Finally, many authors applied different parameters like completion time, throughput, and cost to evaluate the system.

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