Cloud monitoring data challenges: A systematic review

© Springer International Publishing AG 2016. Organizations need to continuously monitor, source and process large amount of operational data for optimizing the cloud computing environment. The research problem is: what are cloud monitoring data challenges – in particular virtual CPU monitoring data? This paper adopts a Systematic Literature Review (SLR) approach to identify and report cloud monitoring data challenges. SLR approach was applied to initially identify a large set of 1861 papers. Finally, 24 of 1861 relevant papers were selected and reviewed to identify the five major challenges of cloud monitoring data: monitoring technology, virtualization technology, energy, availability and performance. The results of this review are expected to help researchers and practitioners to understand cloud computing data challenges and develop innovative techniques and strategies to deal with these challenges

Optimal Framework for Level Based Access Control for VM Auditing on Cloud

The growth in the cloud computing have motivated and enable lot of application developer to deploy the applications on cloud. The major challenge of hosting on cloud is the service provider or the application provider must comply to a good number of rules. These compliance reports are time to time validated and checked by external auditors. The auditing process for the cloud services are critical and the access controls must be enabled. Due to the higher complexity and less flexibility of the virtual machines, most of the cases this access control mechanism is compromised. This work proposes four algorithms to identify and enhance the LBAC mechanism for cloud services with access updates based on time variant characteristics analysis and predictive analysis with selective cryptographic methods. The proposed model produces significantly improved results to overcome three major issues in the cloud service management as selective LBAC, static privileges and open access control for the auditors.  &nbsp

Auditing Cloud Service Level Agreement on VM CPU Speed

Abstract—In this paper, we present a novel scheme for auditing Service Level Agreement (SLA) in a semi-trusted or untrusted cloud. A SLA is a contract formed between a cloud service provider (CSP)and a user which specifies, in measurable terms, what resources a the CSP will provide the user. CSP’s being profit based companies have incentive to cheat on the SLA. By providing a user with less resources than specified in the SLA the CSP can support more users on the same hardware and increase their profits. As the monitoring and verification of the SLA is typically performed on the cloud system itself it is straightforward for the CSP to lie on reports and hide their intentional breach of the SLA. To prevent such cheating we introduce a framework which makes use of a third party auditor (TPA). In this paper we are interested in CPU cheating only. To detect CPU cheating, we develop an algorithm which makes use of a commonly used CPU intensive calculation, transpose matrix multiplication, to randomly detect cheating by a CSP. Using real experiments we show that our algorithm can detect CPU cheating quite effectively even if the extent of the cheating is fairly small