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

Cloud computing is an attractive technology for providing computing resourcesover the Internet. Task scheduling is a critical issue in cloud computing,where an efficient task scheduling method can improve overall cloudperformance. Since cloud computing is a large-scale and geographicallydistributed environment, traditional scheduling methods that allocate resourcesin a centralized manner are ineffective. Besides, traditional methods aredifficult to make rational decisions timely when the external environmentchanges. This paper proposes a decentralized BDI (belief-desire-intention)agent-based scheduling framework for cloud computing. BDI agents haveadvantages in modelling dynamic environments because BDI agents can updatetheir beliefs, change desires, and trigger behaviours based on environmentalchanges. Besides, to avoid communication stuck caused by environmentaluncertainties, the asynchronous communication mode with a notify listener isemployed. The proposed framework covers both the task scheduling andrescheduling stages with the consideration of uncertain events that caninterrupt task executions. Two agent-based algorithms are proposed to implementthe task scheduling and rescheduling processes, and a novel recommendationmechanism is presented in the scheduling stage to reduce the impact ofinformation synchronization delays. The proposed framework is implemented byJADEX and tested on CloudSim. The experimental results show that our frameworkcan minimize the task makespan, balance the resource utilization in alarge-scale environment, and maximize the task success rate when uncertainevents occur.

A BDI Agent-Based Task Scheduling Framework for Cloud Computing