An Improved Multiple Faults Reassignment based Recovery in Cluster Computing

TL;DR

This paper proposes a two-phase recovery scheme for cluster computing that efficiently handles multiple node failures by dynamically redistributing loads, improving performance and resource utilization compared to existing single-fault methods.

Contribution

It introduces a novel two-phase recovery approach with dynamic load redistribution and failure node reassignment algorithms for multiple fault tolerance in cluster computing.

Findings

Improved load balancing reduces recovery time.

Enhanced resource utilization during multiple node failures.

Lower communication overhead compared to traditional methods.

Abstract

In case of multiple node failures performance becomes very low as compare to single node failure. Failures of nodes in cluster computing can be tolerated by multiple fault tolerant computing. Existing recovery schemes are efficient for single fault but not with multiple faults. Recovery scheme proposed in this paper having two phases; sequentially phase, concurrent phase. In sequentially phase, loads of all working nodes are uniformly and evenly distributed by proposed dynamic rank based and load distribution algorithm. In concurrent phase, loads of all failure nodes as well as new job arrival are assigned equally to all available nodes by just finding the least loaded node among the several nodes by failure nodes job allocation algorithm. Sequential and concurrent executions of algorithms improve the performance as well better resource utilization. Dynamic rank based algorithm for load redistribution works as a sequential restoration algorithm and reassignment algorithm for distribution of failure nodes to least loaded computing nodes works as a concurrent recovery reassignment algorithm. Since load is evenly and uniformly distributed among all available working nodes with less number of iterations, low iterative time and communication overheads hence performance is improved. Dynamic ranking algorithm is low overhead, high convergence algorithm for reassignment of tasks uniformly among all available nodes. Reassignments of failure nodes are done by a low overhead efficient failure job allocation algorithm. Test results to show effectiveness of the proposed scheme are presented.