Authors:
Philipp Hasper
;
Nils Petersen
and
Didier Stricker
Affiliation:
German Research Center for Artificial Intelligence (DFKI), Germany
Keyword(s):
Remote Execution, Offloading, Mobile Computing, Computer Vision, Mobile Augmented Reality.
Related
Ontology
Subjects/Areas/Topics:
Applications and Services
;
Computer Vision, Visualization and Computer Graphics
;
Enterprise Information Systems
;
Human and Computer Interaction
;
Human-Computer Interaction
;
Mobile Imaging
Abstract:
Mobile implementations of computationally complex algorithms are often prohibitive due to performance constraints. There are two possible solutions for this: (1) adopting a faster but less powerful approach which results in a loss of accuracy or robustness. (2) using remote data processing which suffers from limited bandwidth and communication latencies and is difficult to implement in real-time interactive applications.
Using the example of a mobile Augmented Reality application, we investigate those two approaches and compare them in terms of performance. We examine different workload balances ranging from extensive remote execution to pure onboard processing. The performance behavior is systematically analyzed under different network qualities and device capabilities. We found that even with a fast network connection, optimizing for maximum offload (thin-client configuration) is at a disadvantage compared to splitting the workload between remote system and client. Compared to rem
ote execution, a simplified onboard algorithm is only preferable if the classification data set is below a certain size.
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