원문정보
초록
영어
Nowadays, different types of bandwidth eater are growing rapidly. Cloud computing as an Internet computing has propagate day by day to provide different type of accommodations and resources to web utilizer. Cloud computing employs Internet resources to execute sizably voluminous-scale tasks. Ergo, to cull felicitous node to execute a task is able to enhance the performance of astronomically immense-scale cloud computing environment. There are several different nodes in a cloud computing system. Namely, each node has different capability to execute task; hence, only consider the CPU remaining of the node is not enough when a node is opted to execute a task. Consequently, how to select an efficient node to execute a task is very consequential in a cloud computing.In this paper, we propose a scheduling algorithm, Load Balancing through Arranging Task with Completion Time, LBATCT which combines minimum completion time and load balancing strategies. For the case study, LBATCT can provide efficient utilization of computing resources and maintain the load balancing in cloud computing environment.
목차
I. Introduction
II. Challenges in Cloud Computing Load Balancing
A. Spatial Distribution of the Cloud Nodes
B. Storage/ Replication
C. Algorithm Complexity
D. Point of Failure
III. Load Balancing Algorithms Review
A. Static Load Balancing Algorithms
B. Dynamic Load Balancing Algorithms
c. The Proposed Method
IV. Comparison
V. Conclusion
Acknowledgement
References