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Network Assisted Mobile Computing with Optimal Uplink Query Processing

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 midnetwork 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.




                                Ambit lick Solutions
                   Mail Id: Ambitlick@gmail.com , Ambitlicksolutions@gmail.Com

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Network assisted mobile computing with optimal uplink query processing

  • 1. Network Assisted Mobile Computing with Optimal Uplink Query Processing 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 midnetwork 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. Ambit lick Solutions Mail Id: Ambitlick@gmail.com , Ambitlicksolutions@gmail.Com