TASK ALLOCATION MODEL FOR RELIABILITY AND COST OPTIMIZATION IN DISTRIBUTED COMPUTING SYSTEM

2011 ◽  
Vol 02 (02) ◽  
pp. 131-149 ◽  
Author(s):  
PRADEEP KUMAR YADAV ◽  
M. P. SINGH ◽  
KULDEEP SHARMA
Keyword(s):  
Mathematical Model ◽  
Distributed Computing ◽  
Task Allocation ◽  
Cost Optimization ◽  
Computing System ◽  
System Efficiency ◽  
Allocation Model ◽  
Processing Elements ◽  
Communication Time ◽  
Communication Links

A Distributed Computing System (DCS) is defined as a set of processing elements interconnected by communication links. Reliability analysis of these processing elements and communication links is one of the important parameters to achieve the system efficiency. The system efficiency can be improved by making the task allocation properly in DCS. In this paper, we have presented a mathematical model, considering DCS with heterogeneous processors in order to achieve optimal cost and optimal reliability by allocating the tasks to the processors, in such a way that the allocated load on each processor is balanced. The task allocation in DCS is known as NP-hard problem even in the best conditions, and based on the present model, an efficient algorithm have been proposed to obtain optimal solutions. To design the mathematical model, execution time of the tasks on each processor as well as communication time between the tasks has been taken in the form of matrices.

scholarly journals Optimal Tasks Assignment for Multiple Heterogeneous Processors with Dynamic Re-assignment

2005 ◽  
Vol 4 (2) ◽  
pp. 528-535 ◽  
Author(s):  
Harendra Kumar ◽  
M. P. Singh ◽  
Pradeep Kumar Yadav
Keyword(s):  
Mathematical Model ◽  
Distributed Computing ◽  
Real Life ◽  
Computing System ◽  
Communication Cost ◽  
Allocation Model ◽  
Heterogeneous Processors ◽  
Total Cost ◽  
Multiple Processors ◽  
The Cost

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 preparing a dynamic tasks allocation model.

scholarly journals Fuzzy based Amalgamated Technique for Optimal Service Time in Distributed Computing System

2019 ◽  
Vol 8 (3) ◽  
pp. 6763-6768
Keyword(s):  
Distributed Computing ◽  
Task Allocation ◽  
New Technologies ◽  
Computer Network ◽  
Task Assignment ◽  
Computing System ◽  
Communication Time ◽  
Single Number ◽  
Transient System ◽  
Microprocessor Technology

Due to the continuous progress of microprocessor technology and computer network, the distributed computing system (DCS) is currently one of the key areas of interest. The distributed computing system [DCS] provides the ability to share better performance and resources. There are a few registering nodes that communicate with one another through the message transient system. The advancement of new technologies in communication and information leads to the development of distributed systems. Task assignment is a critical step in the distributed computing system. For the proper utilization of available enumeration strength, it is necessary to allocate tasks to the processors, whose features are vastly suitable for execution. In this research paper, we have examined a task allocation problem with fuzzy performance time and fuzzy communication time, which is more realistic and general in nature. The problem of fuzzy task allocation is impure and it has been converted into a single number (i.e crisp one) using the fuzzy magnitude ranking method. Here, a serviceable model has been evolved to establish the system's optimum impedance time by optimal assignment of tasks based on triangular fuzzy execution time and triangular fuzzy communication time processor speed

A High Performance Model for Task Allocation in Distributed Computing System Using K-Means Clustering Technique

2018 ◽  
Vol 9 (3) ◽  
pp. 1-23 ◽  
Author(s):  
Harendra Kumar ◽  
Nutan Kumari Chauhan ◽  
Pradeep Kumar Yadav
Keyword(s):  
Mathematical Model ◽  
Distributed Computing ◽  
High Performance ◽  
Computing System ◽  
Performance Model ◽  
Communication Costs ◽  
Clustering Technique ◽  
Proposed Model ◽  
Two Stages ◽  
The Mathematical Model

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 examples have compared with some existing models.

scholarly journals A hybrid Method to augment the efficiency of Distributed Computing System by DAG -Using Finest Task Allocation with Dual Mode Processors

2019 ◽  
Vol 8 (11) ◽  
pp. 4275-4284
Keyword(s):  
Distributed Computing ◽  
Task Allocation ◽  
Scheduling Algorithm ◽  
Computing System ◽  
Service Rate ◽  
Additional Parameter ◽  
Computing Environment ◽  
Dual Mode ◽  
New Approach ◽  
Heterogeneous Distributed Computing

Distributed computing system creates or provides a platform having multiple computing nodes linked in a specified manner. On the basis of literature review of last few decades it has been noticed that most of distributed computing researchers have shown their effort to maintain load balancing between processors ,effective task scheduling and optimizing different parameters affecting execution cost and throughput .With these above scenario an additional parameter “Self reconfiguration of CPU” is also a countable parameter to augment the efficiency of distributed computing system .Through this research paper we want to present new approach of adaptive scheduling algorithm which is the mix output of effective task allocation to processor involved in computing and self-reconfiguration of those processors as per need of computing. By this proposed method we will optimize the execution cost, service rate and maximize the throughput as an outcome of organized processors consist in heterogeneous distributed computing system, resulting provide the considerable enhancement in the performance of Distributed computing environment.

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