Content service is a type of Internet cloud service that provides end-users plentiful contents. To ensure high performance for content delivering, content service utilizes a technology known as content multihoming: contents are generated from multiple geographically distributed data centers and delivered by multiple distributed content distribution networks (CDNs). The electricity costs for data centers and the usage costs for CDNs are major contributors to the contents service cost. As electricity prices vary across data centers and usage costs vary across CDNs, scheduling data centers and CDNs has a tremendous consequence for optimizing content service cost. In this paper, we propose a novel framework named COMIC (Cost Optimization for Internet Content Multihoming). COMIC dynamically balances end-users’ loads among data centers and CDNs so as to minimize the content service cost. Using real-life electricity prices and CDN traces, the experiments demonstrate that COMIC effectively reduces the content service cost by more than 20%. COMIC Cost Optimization for Internet Content Multihoming
Electricity cost minimization for data centers is an important research problem. Most existing work tackles this problem by exploiting the electricity price variation in location or time, and scheduling end-users’ load among geographically distributed data centers [6], [7], [8] or among time slots with different electricity prices [9], [10], [11]. Besides electricity costs for data centers, usage costs for CDNs are another major contributor to the content service cost. There is growing interest in how to choose CDNs for content delivery and minimize the CDN usage costs while the performance requirement is satisfied. A few recent studies took a constrained optimization approach to the usage cost minimization for CDNs
In this paper, we study how to choose data centers for content generation and CDNs for content delivery so as environment. The minimization of content service cost is formulated from service provider’s perspective and it can significantly reduce the operation cost so as to maximize the profits. Note that the content services we discuss are not real-time, such as VoIP. Hence, contents can be replicated in CDNs without compromising the quality of service. To this end, we propose a novel load scheduling framework named COMIC (Cost Optimization for Internet Content Multihoming). COMIC takes a holistic approach to the content service cost minimization by formulating an optimization problem that minimizes the sum of electricity costs for data centers and usage costs for CDNs as well as guaranteeing service performance requirements. The contributions of this paper are twofold: We study an important research problem: the content service cost minimization. To our best knowledge, our work is the first that takes a holistic approach by covering the content service cost from the content generation to the content delivery, i.e., the electricity costs for data centers and the usage costs for CDNs; Our extensive experiments show that COMIC is effective in reducing the content service cost. Moreover, COMIC is proposed with the real-world practicality in mind. COMIC takes as inputs the real-time electricity prices on data center sites and the real-time usage costs of CDNs, and satisfies the real-world constraints, such as the processing capacities of data centers and CDNs, and the data availability situation in data centers. Thus, COMIC is amenable to deployment in the real world.