Analytics in/for cloud-an interdependence: A review. (15th January 2018)

• Record Type: Journal Article
• Authors: Ravi, Kumar; Khandelwal, Yogesh; Krishna, Boora Shiva; Ravi, Vadlamani
• Is Part Of: Journal of network and computer applications. Volume 102(2018)
• Page Start: 17
• Page End: 37
• Publication Date: 2018-01-15
• Subjects: Analytics in cloud -- Analytics for cloud -- Cloud resource demand prediction -- Cloud resource usage optimization -- Cloud provisioning; Microcomputers -- Periodicals; Computer networks -- Periodicals; Application software -- Periodicals; Micro-ordinateurs -- Périodiques; Réseaux d'ordinateurs -- Périodiques; Logiciels d'application -- Périodiques; Application software; Computer networks; Microcomputers; Periodicals; 004.05; 004
• DOI: 10.1016/j.jnca.2017.11.006
• Languages: English
• ISSNs: 1084-8045

Abstract

Abstract: Cloud computing has brought a paradigmatic shift in providing data storage as well as computing resources. With the ever-increasing demand for cloud computing, the number of cloud providers is also increasing evidently, which poses challenges as well as opportunities for consumers and providers. From a consumer point of view, efficient selection of cloud resources at a minimum cost is a big challenge. On the other hand, a provider has to meet consumers' requirements with sufficient profit in the fiercely competitive market. The relationship between cloud computing is truly symbiotic in the sense that cloud computing makes the practice of analytics more pervasive while analytics makes cloud computing more efficient and optimal in a lot of ways. In addressing these issues, analytics plays an important role. In this paper, we reviewed some important research articles, which focus on cloud computing from the viewpoint of analytics. Analytics and cloud computing are found to be quite interdependent. From analytics perspective, cloud computing makes available high-end computing resources even to an individual customer at an affordable price. We call this thread "Analytics in Cloud". From the point of view of cloud computing, efficient management, allocation, and demand prediction can be performed using analytics. We call this thread "Analytics for Cloud". This review paper is mainly based on these two threads of thought process. In this regard, we reviewed eighty-eight research articles published during 2003–2017 related to the formidable duo of cloud computing and analytics.