Diploma Thesis DIP-3207

BibliographyBerg, Florian: Efficient Energy-Constrained Distribution of Context in Mobile Systems.
University of Stuttgart, Faculty of Computer Science, Electrical Engineering, and Information Technology, Diploma Thesis No. 3207 (2011).
77 pages, english.
CR-SchemaG.1.6 (Numerical Analysis Optimization)
C.2.2 (Network Protocols)
Abstract

The recent improvements in smartphones nowadays offer a widespread application of sensor-based services. Each mobile phone is equipped with several sensors like a GPS module, a gyroscope, or a high-resolution camera. As a result of this sensor integration, a whole new way of usage is opened up for the end-user, like a location-based search or people-centric sensing. The main drawback related to a smartphone is an overall high energy consumption, combined with a limited energy capacity. Due to this fact, a continuous and fine grained sensing of the user's context is not possible, as it utilizes at least one acceleration sensor. Furthermore, the captured data is transmitted via a (mobile) communication infrastructure to post the context on the Internet. Both drain the battery very quickly. For that reason, an efficient energy-constrained distribution is required to minimize the update occurrence of a producer, while simultaneously maximizing the accuracy of a consumer. The primary issues to be addressed include a modeling of user behavior as well as a determination of optimal points in time for an update. Therefore, a probabilistic approach is used to forecast the user's context pattern. The prediction is based upon a Markov chain and enables the extraction of meaningful information. The proper times for an update are determined with the help of a constrained optimization problem. Different methods from mathematical optimization are applied like linear and nonlinear programming or a constrained Markov decision process, which obtain an update policy. For a better comparison of the weaknesses and strengths related to the developed methods, dynamic programming is used to achieve the optimal points in time for an update. The evaluation upon a real trace shows that an accuracy gain of more than 30% is achieved by sending the equal amount of messages.

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Department(s)University of Stuttgart, Institute of Parallel and Distributed Systems, Distributed Systems
Superviser(s)Dipl.-Inf. Stefan Föll
Entry dateJanuary 10, 2012
   Publ. Computer Science