Download Scheduling in Distributed Computing Systems: Analysis, by Deo Prakash Vidyarthi, Biplab Kumer Sarker, Anil Kumar PDF
By Deo Prakash Vidyarthi, Biplab Kumer Sarker, Anil Kumar Tripathi, Laurence Tianruo Yang
This publication intends to inculcate the cutting edge rules for the scheduling element in dispensed computing platforms. It offers completely with the scheduling element and may dramatically increase the layout and administration of the techniques for professionals.
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Additional info for Scheduling in Distributed Computing Systems: Analysis, Design and Models
Sometimes, the random arrival of tasks in such environment can cause some nodes to be heavily loaded while other nodes are idle or lightly loaded. Load distribution improves the performance by transferring tasks from heavily loaded nodes, where service is poor, to lightly loaded nodes where the tasks can take advantages of computing capacity that would otherwise go unused . If workloads at some nodes are typically heavier than at others, or if some nodes execute tasks more slowly than others, the situation of lightly loaded/ heav- 48 Scheduling in Distributed Computing Systems ily loaded/ moderately loaded nodes are likely to occur often.
These files for the job may be located on different nodes of the system. Suppose the owner of the job changes a file on any of the node. Before execution of the job, it needs to check if any file has been modified and if so to 28 Scheduling in Distributed Computing Systems compile it afresh. Whether a file has been modified or not will be indicated by the time of creation and execution only. Suppose the machine on which the file is being compiled gives more time than on which it has been modified, the modification will not be noticed and the job will execute only the old version of the object file.
5 Conflicts between TA and LB 56 Scheduling in Distributed Computing Systems The main purpose of a single task allocation in a DCS is to reduce job turn- around time. It is done by maximizing the utilization of resources while minimizing any communication between processing nodes. The benefits of task allocation can make distributed processing desirable but several problems must be solved before they can be realized. For example, when the number of processors in a system increases beyond a certain level, then throughput decreases.