A cost-oriented methodology for the design of web based IT architectures
Proceedings of the 2002 ACM symposium on Applied computing
An integrated system for designing minimum cost survivable telecommunications networks
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
Approximating performance measures for public services
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
Joint Optimization of Hardware and Network Costs for Distributed Computer Systems
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
User-level QoS-adaptive resource management in server end-systems
IEEE Transactions on Computers
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In industry, the total cost of ownership (TCO) for developing a communication service such as video streaming, comprises from two components; CAPital EXpenditure (CAPEX) and OPerational EXpenditure (OPEX). These two types of costs are interrelated and affect any service provider's deployment strategy. In many traditional methods, selection of critical elements of a new service is performed in a heuristic manner aimed at reducing only the OPEX part of the TCO which is not necessarily optimal. Furthermore, exact cost modeling for such services is not always possible and contains some uncertainties. In the current work, the TCO optimization problem for video streaming over IP networks is formulated as a stochastic optimization problem using cost modeling of each video streaming element and capturing the effect of the model uncertainties. The solution of the proposed optimization problem can cope with the cost modeling uncertainties and track the dynamic features of the TCO and lead to a time-varying optimal solution. Numerical analysis results verify the developed method and analyze its sensitivity to input parameters variations. Using the proposed stochastic optimization approach, the video streaming service providers can improve their return on investment (ROI) through selecting the optimal number of the deployed edge servers in the presence of uncertainties in ownership costs.