Generative communication in Linda
ACM Transactions on Programming Languages and Systems (TOPLAS)
Coordination languages and their significance
Communications of the ACM
Machine Learning
IEEE Transactions on Knowledge and Data Engineering
Location prediction algorithms for mobile wireless systems
Wireless internet handbook
Mobile dynamic content distribution networks
MSWiM '04 Proceedings of the 7th ACM international symposium on Modeling, analysis and simulation of wireless and mobile systems
Proximity services supporting network virtual memory in mobile devices
Proceedings of the 2nd ACM international workshop on Wireless mobile applications and services on WLAN hotspots
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Mobile devices, like PDAs or smart phones, exhibit limited capabilities in terms of processing power and memory. Supported by advanced WLAN hotspot grid infrastructures, mobile terminals may enhance their computing capabilities significantly by utilizing remote resources in virtually shared spaces. Due to privacy and performance issues, the shared communication objects should be kept in proximity to the roaming owner which requires object migration.We propose a novel self-adaptive decision algorithm for object migration based on a cost-benefit function. This function considers parameters describing the expected latency caused by migration and the expected response time saved by local access. The importance of each parameter is determined by a weight and adapted using Bayesian concept learning. The feasibility of the approach is demonstrated by a prototypical implementation for PDAs based on the space-based middleware CORSO. We further investigate the decision algorithm by means of simulation.