Dynamic Tasks Scheduling Algorithm for Distributed Computing Systems under Fuzzy Environment

2016 ◽  
Vol 5 (4) ◽  
pp. 77-95 ◽  
Author(s):  
Harendra Kumar ◽  
Nutan Kumari Chauhan ◽  
Pradeep Kumar Yadav
Keyword(s):  
Distributed Computing ◽  
Present Model ◽  
Scheduling Algorithm ◽  
Distributed Computing Systems ◽  
Computing Systems ◽  
Fuzzy Environment ◽  
Multiple Processors ◽  
Tasks Scheduling ◽  
Present Algorithm ◽  
System Phase

Distributed computing systems [DCS] offer the potential for allocating a number of tasks to different processors for execution. It is desired to assign the tasks dynamically to that processor whose characteristics are most appropriate for the execution in order to make the best use of the computational power available. This paper proposes a new mathematical model for allocating the tasks of distributed program to multiple processors in order to achieve optimal cost and optimal reliability of the system. Phase-wise execution cost, residence cost of each task on different processors, inter task communication cost and relocation cost for each task have been considered as a fuzzy number which is more realistic and general in nature. The fuzzy problem has been transformed into crisp one by using the defuzzification method. The present algorithm is formulated and applied to numerical examples to demonstrate its effectiveness. The present model is suitable for arbitrary number of phases and processors with random program structure.

A Survey of Tasks Scheduling Algorithms in Distributed Computing Systems

2021 ◽  
pp. 1269-1281
Author(s):  
Nutan Kumari Chauhan ◽  
Harendra Kumar
Keyword(s):  
Distributed Computing ◽  
Scheduling Algorithms ◽  
Computing System ◽  
Communication Link ◽  
Scheduling Problems ◽  
Distributed Computing Systems ◽  
Computing Systems ◽  
Tasks Scheduling ◽  
Scheduling Strategies ◽  
User Tasks

Distributed computing system (DCS) is a very popular field of computer science. DCS consists of various computers (processors) located at possibly different sites and connected by a communication link in such a manner that it appears as one system to the user. Tasks scheduling is a very interesting field of research in DCS. The main objectives of tasks scheduling problems are load balancing of processors, maximization of system reliability, minimizing the system cost, and minimizing the response time. Obviously, it is very complicated to satisfy all of the above objectives simultaneously. So, most of the researchers have solved the tasks scheduling problem with one or more objectives. The purpose of this chapter is to produce an overview of much (certainly not all) of tasks scheduling algorithms. The chapter is covering the little much valuable survey, tasks scheduling strategies, and different approaches used for tasks scheduling with one or more objectives.

scholarly journals Scheduling Algorithm: Tasks Scheduling Algorithm for Multiple Processors with Dynamic Reassignment

2008 ◽  
Vol 2008 ◽  
pp. 1-9 ◽  
Author(s):  
Pradeep Kumar Yadav ◽  
M. P. Singh ◽  
Harendra Kumar
Keyword(s):  
Resource Sharing ◽  
Scheduling Algorithm ◽  
Distributed Processing ◽  
Processing System ◽  
Distributed Computing Systems ◽  
Allocation Model ◽  
Total Cost ◽  
Multiple Processors ◽  
Tasks Scheduling ◽  
Improved Performance

Distributed computing systems [DCSs] offer the potential for improved performance and resource sharing. To make the best use of the computational power available, it is essential to assign the tasks dynamically to that processor whose characteristics are most appropriate for the execution of the tasks in distributed processing system. We have developed a mathematical model for allocating “M” tasks of distributed program to “N” multiple processors (M>N) that minimizes the total cost of the program. Relocating the tasks from one processor to another at certain points during the course of execution of the program that contributes to the total cost of the running program has been taken into account. Phasewise execution cost [EC], intertask communication cost [ITCT], residence cost [RC] of each task on different processors, and relocation cost [REC] for each task have been considered while preparing a dynamic tasks allocation model. The present model is suitable for arbitrary number of phases and processors with random program structure.

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