Intelligent Model for Predicting the Quality of Services Violation

Abstract

Cloud computing is providing IT services to its customer based on Service level agreements (SLAs). It is important for cloud service providers to provide reliable Quality of service (QoS) and to maintain SLAs accountability. Cloud service providers need to predict possible service violations before the emergence of an issue to perform remedial actions for it. Cloud users' major concerns; the factors for service reliability are based on response time, accessibility, availability, and speed. In this paper, we, therefore, experiment with the parallel mutant-Particle swarm optimization (PSO) for the detection and predictions of QoS violations in terms of response time, speed, accessibility, and availability. This paper also compares Simple-PSO and Parallel Mutant-PSO. In simulation results, it is observed that the proposed Parallel Mutant-PSO solution for cloud QoS violation prediction achieves 94% accuracy which is many accurate results and is computationally the fastest technique in comparison of conventional PSO technique.

Packet Loss Optimization in Router Forwarding Tasks Based on the Particle Swarm Algorithm

“…The result shows that it has a lower cost, better throughput, and less delay than using only one queue or different algorithm. Khan et al [25] investigated IT services provided to customers by cloud environments and the service level agreements (SLAs). They proposed an algorithm to provide cloud service with reliable Quality of service (QoS) and to maintain Service level agreements.…”

ReSQoV: A Scalable Resource Allocation Model for QoS-Satisfied Cloud Services

“…It is in line with Equation ( 1), where machine resources are proportionate, and with the number of processes. Furthermore, Equation (2) indicates that when contention and coherence are null in an ideal scenario, the process node is optimized to its best QoS, resulting in linear scalability. As consistency is defined as the exchange of data across non-local resources, it is most likely to decrease coherence (λ) to zero, where each process node only works with a single resource.…”

“…Cloud consumers focus on QoS, availability, service cost, and many other factors. Examination of the dynamics that influence the appropriate allocation of cloud resources from both the service provider and user viewpoints is challenging [1,2].…”