Performance enhancement of scheduling algorithms in clusters and grids using improved dynamic load balancing techniques

Abstract

This paper describes the research work done for during PhD study. Cluster computing, grid computing and cloud computing are distributed computing environments (DCEs) widely accepted for the next generation Web based commercial and scientific applications. These applications work around the globally distributed data of petabyte scale that can only be processed by the aggregating the capability of globally distributed resources. The resource management and process scheduling in large scale distributed computing environment are a challenging task. In this research work we have devised new scheduling algorithms and resource management strategies specially designed for the cluster and grid cloud and peer-to-peer computing. The research work finally presented the distributed computing solutions to one scientific and one commercial application viz. e-Learning and data mining.

A Survey of Job Scheduling Algorithms Whit Hierarchical Structure to LoadBalancing In Grid Computing Environments

“…In dynamic balancing, the request allocation decisions are decided at run time based on the current state of the system. In adaptive balancing, the allocation parameters and polices can vary depending on the run time information about the system, such as the current state of the system, previous decisions, etc [3,4].…”

A model for dynamic load balancing in open source software for distributed computing environment

“…Now there are variety of OSS are available to support Mail (POP3, IMAP, SMTP), HTTP/S, TCP, UDP, SMS, database, proxy, OS etc [3]. The SimGrid and SimGrid v2 are among the most popular grid simulation tools presently available to the researchers [2], [6].…”

“…These services can be Software as a Service (SaaS), Platform as a Service (PaaS) and Infrastructure as a Service (IaaS) [3]. The clients can easily acquire these facilities without handling the complexity of set up, maintenance and expertise of the environments [2].…”

“…In case of static load balancing, the decision regarding the allotment of a request to a resource is known well in advance. On the other hand, in Dynamic Load Balancing (DLB), the request allotment decisions are taken at run time based on the current state of the system [1], [2].…”

“…Algorithm 1) Parameters, LDB and weight values are initialized2) Step ( i) to step (vii) will be repeated infinitely i) LC waits for trigger ii) As soon as it receives changed parameter value, calculates the load and update LDB. iii) LC checks the health condition of resources.…”