Many
mobile applications retrieve content from remote servers via user generated
queries. Processing these queries is often needed before the desired content
can be identified. Processing the request on the mobile devices can quickly sap
the limited battery resources. Conversely, processing user-queries at remote
servers can have slow response times due communication latency incurred during
transmission of the potentially large query. We evaluate a network-assisted
mobile computing scenario where mid-network nodes with "leasing"
capabilities are deployed by a service provider. Leasing computation power can
reduce battery usage on the mobile devices and improve response times. However,
borrowing processing power from mid-network nodes comes at a leasing cost which
must be accounted for when making the decision of where processing should
occur. We study the tradeoff between battery usage, processing and transmission
latency, and mid-network leasing. We use the dynamic programming framework to
solve for the optimal processing policies that suggest the amount of processing
to be done at each mid-network node in order to minimize the processing and
communication latency and processing costs. Through numerical studies, we
examine the properties of the optimal processing policy and the core tradeoffs
in such systems.
Keywords: IEEE Project Titles 2012, Mobile Computing Titles, Wireless Communication Titles, Networking Titles, Cloud Computing Titles.
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