CoCOA: A Framework for Comparing Aggregate Client Operations in BPO Services

Ghosh, Rahul; Gupta, Avantika; Chattopadhyay, Sreya; Banerjee, Ansuman; Dasgupta, Koustuv

doi:10.1109/scc.2016.76

Cited by 4 publications

(1 citation statement)

References 15 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Some techniques are used to solve ranking problems, such as the Analytic Hierarchy Process (AHP), Analytic Network Process (ANP), Elimination and Choice Expressing Reality (ELECTRE III), and Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) approaches [11]. Other approaches adopted monitoring and historical data combining with ranking techniques for decision making [15]. In this paper, the concept of the TOPSIS method has been adopted for ranking cloud infrastructures.…”

Section: Multiple-criteria Decision-makingmentioning

confidence: 99%

Decision making in cloud environments: an approach based on multiple-criteria decision analysis and stochastic models

et al. 2018

View full text Add to dashboard Cite

Cloud computing is a paradigm that provides services through the Internet. The paradigm has been influenced by previously available technologies (for example cluster, peer-to-peer, and grid computing) and has now been adopted by almost all large organizations. Companies such as Google, Amazon, Microsoft and Facebook have made significant investments in cloud computing, and now provide services with high levels of dependability. The efficient and accurate assessment of cloud-based infrastructure is fundamental in guaranteeing both business continuity and uninterrupted public services, as much as is possible. This paper presents an approach for selecting cloud computing infrastructures, in terms of dependability and cost that best suits both company and customer needs. We use stochastic models to calculate dependability-related metrics for different cloud infrastructures. We then use a Multiple-Criteria Decision-Making (MCDM) method to rank the best cloud infrastructures, taking customer service constraints such as reliability, downtime, and cost into consideration. A case study demonstrates the practicability and usefulness of the proposed approach.

show abstract

Section: Multiple-criteria Decision-makingmentioning

confidence: 99%