KNOWLEDGE BASED MANAGEMENT OF JOBS IN HETEROGENEOUS DISTRIBUTED COMPUTING ENVIRONMENT

Author(s):  
A. G. Feoktistov ◽  
R. O. Kostromin ◽  
Yu. A. Dyadkin

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.


2021 ◽  
Vol 11 (1) ◽  
pp. 8
Author(s):  
Alexander Feoktistov ◽  
Sergey Gorsky ◽  
Roman Kostromin ◽  
Roman Fedorov ◽  
Igor Bychkov

Nowadays, developing and applying advanced digital technologies for monitoring protected natural territories are critical problems. Collecting, digitalizing, storing, and analyzing spatiotemporal data on various aspects of the life cycle of such territories play a significant role in monitoring. Often, data processing requires the utilization of high-performance computing. To this end, the paper addresses a new approach to automation of implementing resource-intensive computational operations of web processing services in a heterogeneous distributed computing environment. To implement such an operation, we develop a workflow-based scientific application executed under the control of a multi-agent system. Agents represent heterogeneous resources of the environment and distribute the computational load among themselves. Software development is realized in the Orlando Tools framework, which we apply to creating and operating problem-oriented applications. The advantages of the proposed approach are in integrating geographic information services and high-performance computing tools, as well as in increasing computation speedup, balancing computational load, and improving the efficiency of resource use in the heterogeneous distributed computing environment. These advantages are shown in analyzing multidimensional time series.


2017 ◽  
Vol 103 ◽  
pp. 162-167 ◽  
Author(s):  
I. Bychkov ◽  
G. Oparin ◽  
A. Tchernykh ◽  
A. Feoktistov ◽  
V. Bogdanova ◽  
...  

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