Research Area: Cloud Computing
Cloud computing is becoming more and more popular and has received considerable attention recently. As a new kind of Information Technology (IT) commercial model, understanding the economics of cloud computing becomes critically important. From the cloud service providers perspective, profit maximization is the top issue for them. Because a multi-server system is devoted to serving one type of service requests and application, service providers should build multiple multi-server systems to satisfy the market requirements of different application domains. Because available funding for a service provider is generally limited, it cannot afford to invest in all application domains. Hence, how to select appropriate application domains for investment and allocate funding such that the total profit is maximized are important issues for service providers. To address this problem, a fund-constrained profit maximization model is proposed. However, the exact solution of this optimization model is very difficult to formulate due to its complexity. Hence, this paper presents a heuristic strategy to search for a high quality solution. In our strategy, the optimization problem is solved in four stages, and the solution is optimized gradually. Through the proposed heuristic investment strategy, an appropriate investment scheme can be developed that synthesizes the market requirement, the fund constraint, the service level agreement, and so forth. A series of numerical calculations is executed to assess the performance of the proposed strategy. Then, six other investment strategies are compared to our strategy. Our results show that the investment scheme designed using our strategy can produce much more profit than these six other strategies.
Keywords:
Cloud computing
deadline
fund allocation
multi-server system
profit maximization
queuing model
service-level agreement
waiting time
Author(s) Name: Kenli Li; Jing Mei; Keqin Li
Journal name: IEEE Transactions on Services Computing
Conferrence name:
Publisher name: IEEE
DOI: 10.1109/TSC.2016.2589241
Volume Information: Volume: 11, Issue: 6, 01 Nov.-Dec. 2018, Page(s): 893 - 907
