A weighted resource discovery approach in grid computing

Abstract

Purpose Grid computing is an effective environment for the execution of parallel applications that requires great computing power. This paper aims to present, based on the hierarchical architecture, an improved weighted resource discovery (WRD) algorithm to manage allocation of resources and minimize cost of communications between grid nodes. Design/methodology/approach A behavioral modeling method is addressed to prove the proposed method correctness. The behavioral model of the proposed algorithm is implemented by StarUML tool with two different model-checking mechanisms. Then, the resource discovery correctness is analyzed in terms of reachability condition, fairness condition and deadlock-free using NuSMV model checker. Findings The results show that WRD algorithm has better performance in requiring re-discovery process, the number of examined nodes in each request and discovering the free resources with high-bandwidth links. Originality/value To store information of resources, a new data structure called resource information table is proposed which facilitates resource finding of the algorithm. A behavioral modeling method is addressed to prove the proposed method correctness.

Swarm intelligence‐based optimal device deployment in heterogeneous Internet of Things networks for wind farm application

“…Since the RDs are used for connectivity establishment, it is better to find a solution for RDDP with optimized placement of RDs for inter‐target connectivity establishment and to reduce the cost of the network deployment. The RDDP has proved an NP‐hard problem 20–22 . To the best of knowledge of the authors of this paper, this is the first time RDDP is solved using bio‐inspired particle swarm optimization (PSO) algorithm.…”