Abstract
A key challenge in wide adoption of sophisticated context-aware applications is the requirement of continuous sensing and context computing. This paper presents Panorama, a middleware that identifies collaboration opportunities to offload context computing tasks to nearby mobile devices as well as cloudlets/cloud. At the heart of Panorama is a multi-objective optimizer that takes into account different constraints such as access cost, computation capability, access latency, energy consumption and data privacy, and efficiently computes a collaboration plan optimized simultaneously for different objectives such as minimizing cost, energy and/or execution time. Panorama provides support for discovering nearby devices and cloudlets/cloud, computing an optimal collaboration plan, distributing computation to participating devices, and getting the results back. The paper provides an extensive evaluation of Panorama via two representative context monitoring applications over a set of Android devices and a cloudlet/cloud under different constraints.
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Notes
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Notice that here the word “payment” is used in a general sense. It can be a monetary payment, or virtual payment such as credit for reputation.
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© 2015 Institute for Computer Sciences, Social Informatics and Telecommunications Engineering
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Alanezi, K., Zhou, X., Chen, L., Mishra, S. (2015). Panorama: A Framework to Support Collaborative Context Monitoring on Co-located Mobile Devices. In: Sigg, S., Nurmi, P., Salim, F. (eds) Mobile Computing, Applications, and Services. MobiCASE 2015. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 162. Springer, Cham. https://doi.org/10.1007/978-3-319-29003-4_9
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DOI: https://doi.org/10.1007/978-3-319-29003-4_9
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