Papers by Pradeep Kumar Yadav
INTERNATIONAL JOURNAL OF COMPUTERS & TECHNOLOGY, 2005
Distributed Computing System [DCS] has attracted several researchers by posing several challengin... more Distributed Computing System [DCS] has attracted several researchers by posing several challenging problems. In this paper 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. Most of the researchers have considered the cost for relocating the task from one processor to another processor at the end of the phase as a constant. But in real life situations the reallocating cost of the tasks may very processor to processor this is due to the execution efficiency of the processors. Phase-wise execution cost [EC], inter task communication cost [ITCT], residence cost [RC] of each task on different processors and relocation cost [REC] for each task have been considered while pre...
International Journal of Distributed Systems and Technologies, 2018
Tasks allocation is an important step for obtaining high performance in distributed computing sys... more Tasks allocation is an important step for obtaining high performance in distributed computing system (DCS). This article attempts to develop a mathematical model for allocating the tasks to the processors in order to achieve optimal cost and optimal reliability of the system. The proposed model has been divided into two stages. Stage-I, makes the ‘n' clusters of set of ‘m' tasks by using k-means clustering technique. To use the k-means clustering techniques, the inter-task communication costs have been modified in such a way that highly communicated tasks are clustered together to minimize the communication costs between tasks. Stage-II, allocates the ‘n' clusters of tasks onto ‘n' processors to minimize the system cost. To design the mathematical model, executions costs and inter tasks communication costs have been taken in the form of matrices. To test the performance of the proposed model, many examples are considered from different research papers and results of ...
Dynamic Tasks Scheduling Model for Performance Evaluation of a Distributed Computing System through Artificial Neural Network
Advances in Intelligent and Soft Computing, 2012
ABSTRACT As technology has quickly and relentlessly advanced in the field of computer hardware, D... more ABSTRACT As technology has quickly and relentlessly advanced in the field of computer hardware, Distributed Computing System [DCS] has become increasingly popular. Performance enhancement is one of the most important issues in distributed systems. In this paper we have proposed a dynamic task allocation model based on artificial neural network [ANN] scheduling approach to arrange the tasks to the processors. 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. Phase-wise Execution Cost [EC], Inter Task Communication Cost [ITCC], Residence Cost [RC] of each task on different processors and Relocation Cost [REC] for each task has been considered while preparing the model.
International Journal of Computer Applications, 2013
Distributed computing system [DCS] offer the potential for improved performance and resource shar... more Distributed computing system [DCS] 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 to that processor whose characteristics are most appropriate for the execution. In this paper we have investigated a tasks allocation problem with fuzzy execution times e ?_(i,j) and fuzzy inter tasks communication times c ?_(i,j) which is more realistic and general in nature. Times e ?_(i,j) and c ?_(i,j) have been considered to be triangular and trapezoidal numbers. The fuzzy tasks allocation problem is defuzzified and converted into crisp ones using fuzzy number ranking method. A mathematical model has been developed to determine the optimal allocation of the tasks for the crisp problem that minimizes the total cost of the program. The allocation plan that minimizes the total cost for the new crisp problem also minimizes the total time for the original fuzzy tasks allocation. Numerical examples show that the model presented in this paper offers an effective tool for handling the fuzzy tasks allocation problem Refer ences
A Tasks Allocation Algorithm for Optimum Utilization of Processor's in Heterogeneous Distributing Computing Systems
In Distributed Processing System (DPS), partitioning of the application software into small tasks... more In Distributed Processing System (DPS), partitioning of the application software into small tasks and the proper mapping of these tasks among processors are one of the important parameter which determine the efficient utilization of available Processor's Capacity. The model discussed here performs static task mapping/ allocation of a set of 'm' tasks of a program to a set of 'n' processors (where m > n) with the constraints of minimizing Inter Task communication (ITC) cost and maximize the overall throughput of the system in such a way that allocated load on all the processors is balanced. While designing the model Per Bit Processor Service Rate PSR(,)and Inter Task Communication Cost ITCC(,) and Task Size TS (,) have taken into consideration.
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Papers by Pradeep Kumar Yadav