An Agent-Based Migration Transparency and Fault Tolerance in Computational Grid

2009 ◽  
Author(s):  
Srimathi Chandrasekaran ◽  
Eunmi Choi ◽  
Venkat Viswanadh
Keyword(s):  
Fault Tolerance ◽  
Computational Grid ◽  
Agent Based

scholarly journals Towards Integration of Fault Tolerance in Agent-based Systems

2018 ◽  
Vol 127 ◽  
pp. 264-273
Author(s):  
Abdelhay Haqiq ◽  
Bouchaib Bounabat
Keyword(s):  
Fault Tolerance ◽  
Agent Based

scholarly journals Hybrid multi‐agent‐based adaptive control scheme for AC microgrids with increased fault‐tolerance needs

2019 ◽  
Vol 14 (1) ◽  
pp. 13-26
Author(s):  
Angelina D. Bintoudi ◽  
Lampros Zyglakis ◽  
Apostolos C. Tsolakis ◽  
Dimosthenis Ioannidis ◽  
Lenos Hadjidemetriou ◽  
...  
Keyword(s):  
Adaptive Control ◽  
Fault Tolerance ◽  
Agent Based ◽  
Control Scheme ◽  
Multi Agent ◽  
Adaptive Control Scheme

A Replica Based Co-Scheduler (RBS) for Fault Tolerant Computational Grid

2011 ◽  
pp. 101-116
Author(s):  
Zahid Raza ◽  
Deo P. Vidyarthi
Keyword(s):  
Fault Tolerance ◽  
Performance Optimization ◽  
Large Scale ◽  
Heterogeneous Computing ◽  
Fault Tolerant ◽  
Turnaround Time ◽  
Computational Grid ◽  
Successful Execution ◽  
Computational Resources ◽  
The Cost

Grid is a parallel and distributed computing network system comprising of heterogeneous computing resources spread over multiple administrative domains that offers high throughput computing. Since the Grid operates at a large scale, there is always a possibility of failure ranging from hardware to software. The penalty paid of these failures may be on a very large scale. System needs to be tolerant to various possible failures which, in spite of many precautions, are bound to happen. Replication is a strategy often used to introduce fault tolerance in the system to ensure successful execution of the job, even when some of the computational resources fail. Though replication incurs a heavy cost, a selective degree of replication can offer a good compromise between the performance and the cost. This chapter proposes a co-scheduler that can be integrated with main scheduler for the execution of the jobs submitted to computational Grid. The main scheduler may have any performance optimization criteria; the integration of co-scheduler will be an added advantage towards fault tolerance. The chapter evaluates the performance of the co-scheduler with the main scheduler designed to minimize the turnaround time of a modular job by introducing module replication to counter the effects of node failures in a Grid. Simulation study reveals that the model works well under various conditions resulting in a graceful degradation of the scheduler’s performance with improving the overall reliability offered to the job.

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