|Bibliography||Dibak, Christoph; Dürr, Frank; Rothermel, Kurt: Numerical Analysis of Complex Physical Systems on Networked Mobile Devices. |
In: Proceedings of the 12th IEEE International Conference on Mobile Ad hoc and Sensor Systems (MASS 2015); Dallas, USA, October 19-22 2015.
University of Stuttgart, Faculty of Computer Science, Electrical Engineering, and Information Technology.
pp. 1-9, english.
Dallas: IEEE, October 2015.
Article in Proceedings (Conference Paper).
|CR-Schema||C.2.4 (Distributed Systems)|
C.4 (Performance of Systems)
G.1.0 (Numerical Analysis General)
|Keywords||mobile cloud computing; numerical applications; mobile cyber-physical systems; augmented reality|
Recently, a new class of mobile applications has appeared that takes into account the behavior of physical phenomenon. Prominent examples of such applications include augmented reality applications visualizing physical processes on a mobile device or mobile cyber-physical systems like autonomous vehicles or robots. Typically, these applications need to solve partial differential equations (PDE) to simulate the behavior of a physical system. There are two basic strategies to numerically solve these PDEs: (1) offload all computations to a remote server; (2) solve the PDE on the resource-constrained mobile device. However, both strategies have severe drawbacks. Offloading will fail if the mobile device is disconnected, and resource constraints require to reduce the quality of the solution.
Therefore, we propose a new approach for mobile simulations using a hybrid strategy that is robust to communication failures and can still benefit from powerful server resources. The basic idea of this approach is to dynamically decide on the placement of the PDE solver based on a prediction of the wireless link availability using Markov Chains. Our tests based on measurement in real cellular networks and real mobile devices show that this approach is able to keep deadline constraints in more than 61 % of the cases compared to a pure offloading approach, while saving up to 74 % of energy compared to a simplified approach.
|Full text and|
|PDF (883408 Bytes)|
|Copyright||© 2015 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. |
|Contact||Christoph Dibak email@example.com |
|Department(s)||University of Stuttgart, Institute of Parallel and Distributed Systems, Distributed Systems|
|Entry date||August 7, 2015|