Open Access

ARTICLE

Adaptive Runtime Monitoring of Service Level Agreement Violations in Cloud Computing

Sami Ullah Khan¹, Babar Nazir¹, Muhammad Hanif^2,*, Akhtar Ali³, Sardar Alam¹, Usman Habib⁴

1 Department of Computer Science, COMSATS University, Abbottabad Campus, Pakistan
2 Faculty of Computer Science and Engineering, Ghulam Ishaq Khan (GIK) Institute of Engineering Sciences and Technology Topi, Pakistan
3 IFahja Pvt Limited, Peshawar, Pakistan
4 Department of Computer Science, National University of Computer and Emerging Sciences Islamabad, Chiniot-Faisalabad Campus, Pakistan

* Corresponding Author: Muhammad Hanif. Email:

(This article belongs to the Special Issue: AI for Wearable Sensing--Smartphone / Smartwatch User Identification / Authentication)

Computers, Materials & Continua 2022, 71(3), 4199-4220. https://doi.org/10.32604/cmc.2022.020852

Received 28 May 2021; Accepted 17 August 2021; Issue published 14 January 2022

Abstract

The cloud service level agreement (SLA) manage the relationship between service providers and consumers in cloud computing. SLA is an integral and critical part of modern era IT vendors and communication contracts. Due to low cost and flexibility more and more consumers delegate their tasks to cloud providers, the SLA emerges as a key aspect between the consumers and providers. Continuous monitoring of Quality of Service (QoS) attributes is required to implement SLAs because of the complex nature of cloud communication. Many other factors, such as user reliability, satisfaction, and penalty on violations are also taken into account. Currently, there is no such policy of cloud SLA monitoring to minimize SLA violations. In this work, we have proposed a cloud SLA monitoring policy by dividing a monitoring session into two parts, for critical and non-critical parameters. The critical and non-critical parameters will be decided on the interest of the consumer during SLA negotiation. This will help to shape a new comprehensive SLA based Proactive Resource Allocation Approach (RPAA) which will monitor SLA at runtime, analyze the SLA parameters and try to find the possibility of SLA violations. We also have implemented an adaptive system for allocating cloud IT resources based on SLA violations and detection. We have defined two main components of SLA-PRAA i.e., (a) Handler and (b) Accounting and Billing Manager. We have also described the function of both components through algorithms. The experimental results validate the performance of our proposed method in comparison with state-of-the-art cloud SLA policies.

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Keywords

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