Time-, Energy-, and Monetary Cost-Aware Query Processing in a Mobile-Cloud Database Environment

Growing demand for more mobile access to data is only matched by the growth of large and complex data. The availability and scalability of cloud resources when combined with techniques of caching and distributed computation provide tools to address these problems, but bring up new multi-dimensional optimization challenges such as execution time, monetary cost, and power consumption. The plethora of various cloud providers with varying pricing schemes only further complicates the user’s problem. To address these issues we present a three-tier model that formalizes the query planning and execution between mobile users, data owners and cloud providers, allowing state holders to impose constraints on time, money and energy consumption and understand the possible tradeoffs between them.