Service Level Agreement Monitoring as a Service: An Independent Monitoring Service for Service Level Agreements in Clouds.

Journal: Big data
Published Date:

Abstract

The cloud network is rapidly growing due to a massive increase in interconnected devices and the emergence of different technologies such as the Internet of things, fog computing, and artificial intelligence. In response, cloud computing needs reliable dealings among the service providers, brokers, and consumers. The existing cloud monitoring frameworks such as Amazon Cloud Watch, Paraleap Azure Watch, and Rack Space Cloud Kick work under the control of service providers. They work fine; however, this may create dissatisfaction among customers over Service Level Agreement (SLA) violations. Customers' dissatisfaction may drastically reduce the businesses of service providers. To cope with the earlier mentioned issue and get in line with cloud philosophy, Monitoring as a Service (MaaS), completely independent in nature, is needed for observing and regulating the cloud businesses. However, the existing MaaS frameworks do not address the comprehensive SLA for customer satisfaction and penalties management. This article proposes a reliable framework for monitoring the provider's services by adopting third-party monitoring services with clearcut SLA and penalties management. Since this framework monitors SLA as a cloud monitoring service, it is named as SLA-MaaS. On violations, it penalizes those who are found in breach of terms and condition enlisted in SLA. Simulation results confirmed that the proposed framework adequately satisfies the customers (as well as service providers). This helps in developing a trustworthy relationship among cloud partners and increases customer attention and retention.

Authors

  • Afzal Badshah
    Department of Computer Science and Software Engineering, International Islamic University, Islamabad, Pakistan.
  • Ateeqa Jalal
    Department of Computer Science, University of Science and Technology, Bannu, Pakistan.
  • Umar Farooq
    Department of Computer Science, University of Science and Technology, Bannu, Pakistan.
  • Ghani-Ur Rehman
    Department of Computer Science and Bioinformatics, Khushal Khan Khattak University, Karak, Pakistan.
  • Shahab S Band
    Future Technology Research Center, College of Future, National Yunlin University of Science and Technology, Yunlin, Taiwan.
  • Celestine Iwendi
    BCC of Central South University of Forestry and Technology, Changsha, China.