Scheduling in Distributed Computing Environment Using Dynamic Load Balancing

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Chapter 3.1 PREAMBLE:
As we have seen in previous chapter, DLB is one of the distributed scheduling techniques, used extensively to improve scalability and overall system throughput in the rapidly growing resource intensive distributed applications. It is responsible for task scheduling as well as monitoring load variation in the system. In such distributed applications, uneven process arrival may cause load imbalance, where some nodes are overloaded while some other nodes are idle. DLB technique distributes processing workload as evenly as possible among the nodes in a cluster. This helps in improving response time by minimizing job's execution time, minimizing communication overheads and maximizing resource utilization. It also tries to preserve fairness in individual job execution so that a low priority process should not be overtaken by an arbitrary number of higher priority processes [Kanungo,2002). DLB is realized through process migration. DLB allows cluster of nodes to be used as a cost effective alternative to mainframe computing as well as parallel computing [Amiri,2000]. Dynamic load balancing is also used to balance load in a cluster of web servers deployed by websites for processing clients' requests [Abdelzaher,2000]. In present chapter, we have investigated some important issues like measurement of processing workload for taking process transfer decisions and measurement of performance of load balancing algorithms [Petri,1995].
DLB approach can create additional overhead in collecting system state, analyzing the data, making load balancing decisions and transferring the processes from one node to another [Wilson,1998]. Performance of load balancing is closely related to the process information made available to the load balancer, accuracy of the load measurement and the efficiency with which such information is used. Load balancing yields greater performance improvement when workload is heavy and unbalanced. The index used to measure

Dr Priyesh Kanungo is working as a Professor and Senior Systems Engineer in Computer Centre at School of Computer Science and Information Technology, Devi Ahilya Vishwavidyalaya (DAVV), Indore.
He received B.E. (Industrial and Production Engg.), M.E. (Computer Engineering) from SGSITS, Indore and M Phil and Ph D. in Computer Engineering.
He is having more than 26 years of teaching experience in M Tech, Ph D, M.C.A., M.B.A., B.E. etc. in DAVV, Indore. He has been teaching various subjects like Operating Systems, Systems Programming, Data Structures, DBMS and AI.
His main areas of research are Advance Operating Systems Distributed Computing, Grid Computing, and Cloud Computing. He has published around 50 research papers in reputed international journals and conferences (including IEEE, ACM and Springer). He is also UGC expert for Computer Science, Applications and Engineering.