76,113 research outputs found

    Leveraging Program Analysis to Reduce User-Perceived Latency in Mobile Applications

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    Reducing network latency in mobile applications is an effective way of improving the mobile user experience and has tangible economic benefits. This paper presents PALOMA, a novel client-centric technique for reducing the network latency by prefetching HTTP requests in Android apps. Our work leverages string analysis and callback control-flow analysis to automatically instrument apps using PALOMA's rigorous formulation of scenarios that address "what" and "when" to prefetch. PALOMA has been shown to incur significant runtime savings (several hundred milliseconds per prefetchable HTTP request), both when applied on a reusable evaluation benchmark we have developed and on real applicationsComment: ICSE 201

    The Contributory Effect of Latency on the Quality of Voice Transmitted over the Internet

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    Deployment of Voice over Internet Protocol (VoIP) is rapidly growing worldwide due to the new services it provides and cost savings derived from using a converged IP network. However, voice quality is affected by bandwidth, delay, latency, jitter, packet loss e.t.c. Latency is the dominant factor that degrades quality of voice transfer. There is therefore strong need for a study on the effect of Latency with the view to improving Quality of Voice (QoV) in VoIP network. In this work, Poisson probability theorem, Markov Chain, Probability distribution theorems and Network performance metric were used to study the effect of latency on QoS in VoIP network. This is achieved by considering the effect of latency resulting from several components between two points in multiple networks. The NetQoS Latency Calculator, Net-Cracker Professional® for Modeling and Matlab/Simulink® for simulating network were tools used and the results obtained compare favourably well with theoretical facts

    A First Step Towards Automatically Building Network Representations

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    To fully harness Grids, users or middlewares must have some knowledge on the topology of the platform interconnection network. As such knowledge is usually not available, one must uses tools which automatically build a topological network model through some measurements. In this article, we define a methodology to assess the quality of these network model building tools, and we apply this methodology to representatives of the main classes of model builders and to two new algorithms. We show that none of the main existing techniques build models that enable to accurately predict the running time of simple application kernels for actual platforms. However some of the new algorithms we propose give excellent results in a wide range of situations
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