Energy expenses are becoming an increasingly important fraction of data center operating costs. At the same time, the energy expense per unit of computation can vary significantly between two different locations. In this paper, we characterize the variation due to fluctuating electricity prices and argue that existing distributed systems should be able to exploit this variation for significant economic gains. Electricity prices exhibit both temporal and geographic variation, due to regional demand differences, transmission inefficiencies, and generation diversity. Starting with historical electricity prices, for twenty nine locations in the US, and network traffic data collected on Akamai's CDN, we use simulation to quantify the possible economic gains for a realistic workload. Our results imply that existing systems may be able to save millions of dollars a year in electricity costs, by being cognizant of locational computation cost differences.

Tavarua is a multimedia streaming system that leverages network-striping to deliver relatively high bit rate video over present-day cellular wireless wide-area networks. The Tavarua system achieves this by building on our previously developed flexible network-striping middleware. This paper describes a motivating mobile telemedicine application, and the design of the Tavarua system. It also describes experiments in which our initial Tavarua implementation was used to stripe video over multiple 3G cellular-phones from different providers.

Inverse multiplexing, or network striping, allows the construction of a high-bandwidth virtual channel from a collection of multiple low-bandwidth network channels. Striping systems usually employ an immutable packet scheduling policy and allow applications to be oblivious of the way in which packets are routed to specific network channels. Though this is appropriate for many applications, other applications can benefit from an approach that explicitly involves the application in the dynamic determination of the striping policy.Horde is middleware that facilitates flexible striping in wireless environments for a diverse range of applications. Horde separates the striping policy from routing and scheduling. It allows applications to specify network quality-of-service objectives that the striping mechanism attempts to satisfy. Horde can be used by a set of application data streams, each with its own quality-of-service policy, to flexibly stripe data over a highly heterogeneous set of dynamically varying wireless network channels.We present the Horde architecture, describe an early implementation, and examine how different policies can be used to modulate the quality-of-service observed across different independent data streams.