English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

Resource sharing, selection, and aggregation are vital functions of grid computing. However, managing resources in a grid-based environment is a stimulating task. It is necessary to update the topographical dispersal of resources possessed by various organisations with various usage guidelines, financial frameworks, load, and availability patterns. Users and servers have different objectives, methods, and needs. This article suggests a cost-effective framework for resource management in grid computing to look at and address these resource management difficulties. The proposed framework has three main functions, which help in grid construction, load balancing, and resource allocation. A Genetic engineering approach has been implemented to establish a relationship between the resource pool and the jobs of the nodes that improve the resource utilization. The proposed methodology also optimizes the overall cost by minimizing turnaround time. The results of proposed research are compared with commonly used algorithms and claiming 1.5 to 10% better results.

GEMM, a Genetic Engineering-based Mutual Model for Resource Allocation of Grid Computing