A Principled Design of Intelligent Agent for the SLA negotiation process in cloud computing

Kumar, R. and Hassan, M.F. and Adnan, M.H.M. (2022) A Principled Design of Intelligent Agent for the SLA negotiation process in cloud computing. In: UNSPECIFIED.

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Abstract

Cloud Service Providers (CSPs) are in massive demand with the growing field of information technology. CSP produces enormous solutions and support for cloud, IoT, Fog, and Edge computing. In the current era of the competitive cloud market, consumer satisfaction plays an important role. Quality of Services (QoS) fulfilment for service level agreement (SLA) for CSP and consumers is always given more attention. Consumers face problems over resource delivery after signing SLA and CSP issues to provide over-demanded resources. In the dynamic market of cloud and heterogeneous environments, the existing system needs an intelligent agent-based negotiation system (IANS) to handle responsibilities. IANS will perform the negotiation process and measure the key factors to make fast decisions with maximum utility value at an affordable price. IANS uses a behavioural learning analysis algorithm between consumers and CSP to select a reliable, secure server at a minimum cost. The negotiation process will be using metrics, performance factors, evaluation measures, and behaviour learning for decision making. © 2022 IEEE.

Item Type: Conference or Workshop Item (UNSPECIFIED)
Additional Information: cited By 3; Conference of 2nd International Conference on Computing and Information Technology, ICCIT 2022 ; Conference Date: 25 January 2022 Through 27 January 2022; Conference Code:177361
Uncontrolled Keywords: Cloud computing; Commerce; Decision making; Distributed database systems; Intelligent agents; Quality of service; Web services, Agent-based negotiation system; Behavioral learning architecture; Cloud service providers; Cloud services; Cloud-computing; Edge computing; Learning architectures; Negotiation; Negotiation process; Servicelevel agreement (SLA), Intelligent systems
Depositing User: Mr Ahmad Suhairi UTP
Date Deposited: 19 Dec 2023 03:24
Last Modified: 19 Dec 2023 03:24
URI: https://khub.utp.edu.my/scholars/id/eprint/17714

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