Visible to the public iDaaS: Inter-Datacenter Network as a Service

TitleiDaaS: Inter-Datacenter Network as a Service
Publication TypeJournal Article
Year of Publication2018
AuthorsLi, W., Guo, D., Li, K., Qi, H., Zhang, J.
JournalIEEE Transactions on Parallel and Distributed Systems
Date PublishedJuly 1 2018
KeywordsBandwidth, bandwidth allocation, bandwidth guarantee, bandwidth price, bandwidth reservation algorithms, bandwidth trading market, cloud computing, Collaboration, composability, computer centres, Distributed databases, efficient bandwidth pricing algorithm, game theory, Games, Google, Human Behavior, human factors, iDaaS provider, Inter-datacenter network, Inter-Datacenter Network as a Service, Internet, Internet giants, Internet-scale applications, Internet-scale Computing Security, lower bandwidth price, Metrics, multiple iDaaS providers, Policy Based Governance, predictable network performance, Pricing, private wide area networks, pubcrawl, resilience, Resiliency, Scalability, service-inter-datacenter network, Stackelberg game, telecommunication traffic, traditional application providers, unpredictable network performance, video streaming, WANs, wide area networks, wide area traffic

Increasing number of Internet-scale applications, such as video streaming, incur huge amount of wide area traffic. Such traffic over the unreliable Internet without bandwidth guarantee suffers unpredictable network performance. This result, however, is unappealing to the application providers. Fortunately, Internet giants like Google and Microsoft are increasingly deploying their private wide area networks (WANs) to connect their global datacenters. Such high-speed private WANs are reliable, and can provide predictable network performance. In this paper, we propose a new type of service-inter-datacenter network as a service (iDaaS), where traditional application providers can reserve bandwidth from those Internet giants to guarantee their wide area traffic. Specifically, we design a bandwidth trading market among multiple iDaaS providers and application providers, and concentrate on the essential bandwidth pricing problem. The involved challenging issue is that the bandwidth price of each iDaaS provider is not only influenced by other iDaaS providers, but also affected by the application providers. To address this issue, we characterize the interaction between iDaaS providers and application providers using a Stackelberg game model, and analyze the existence and uniqueness of the equilibrium. We further present an efficient bandwidth pricing algorithm by blending the advantage of a geometrical Nash bargaining solution and the demand segmentation method. For comparison, we present two bandwidth reservation algorithms, where each iDaaS provider's bandwidth is reserved in a weighted fair manner and a max-min fair manner, respectively. Finally, we conduct comprehensive trace-driven experiments. The evaluation results show that our proposed algorithms not only ensure the revenue of iDaaS providers, but also provide bandwidth guarantee for application providers with lower bandwidth price per unit.

Citation Keyli_idaas_2018