Fuzzy sets and fuzzy logic: theory and applications
Fuzzy sets and fuzzy logic: theory and applications
Adaptive Offloading for Pervasive Computing
IEEE Pervasive Computing
MAUI: making smartphones last longer with code offload
Proceedings of the 8th international conference on Mobile systems, applications, and services
CloneCloud: elastic execution between mobile device and cloud
Proceedings of the sixth conference on Computer systems
Odessa: enabling interactive perception applications on mobile devices
MobiSys '11 Proceedings of the 9th international conference on Mobile systems, applications, and services
NGMAST '11 Proceedings of the 2011 Fifth International Conference on Next Generation Mobile Applications, Services and Technologies
A generic middleware framework for handling process intensive hybrid cloud services from mobiles
Proceedings of the 9th International Conference on Advances in Mobile Computing and Multimedia
COMET: code offload by migrating execution transparently
OSDI'12 Proceedings of the 10th USENIX conference on Operating Systems Design and Implementation
Mobile cloud messaging supported by XMPP primitives
Proceeding of the fourth ACM workshop on Mobile cloud computing and services
Mobile code offloading: should it be a local decision or global inference?
Proceeding of the 11th annual international conference on Mobile systems, applications, and services
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Mobile cloud computing is arising as a prominent domain that is seeking to bring the massive advantages of the cloud to the resource constrained smartphones, by following a delegation or offloading criteria. In a delegation model, a mobile device consumes services from multiple clouds by efficiently utilizing solutions like middleware. In the offloading model, a mobile application is partitioned and analyzed so that the most computational expensive operations at code level can be identified and offloaded for remote processing. While code offloading is studied extensively for the development of mobile cloud applications, much of the advantages of cloud computing are still left unexploited and poorly considered in these approaches. Cloud computing may introduce many other dynamic variables like performance metrics, parallelization of tasks, elasticity etc., to current code offloading models that could affect the overall offloading decision process. To address this, we propose a fuzzy decision engine for code offloading, that considers both mobile and cloud variables. The cloud parameters and rules are introduced asynchronously to the mobile, using notification services. The paper also proposes a strategy to enrich the offloading decision process with evidence-based learning methods, by exploiting cloud processing capabilities over code offloading traces.