Context-awareness is a key requirement in many of today's networks, services and applications. Context management systems are used to provide access to distributed, dynamic context information. The reliability of remotely accessed dynamic context information is impacted by network delay, packet drop probability, its information dynamics and the access strategy used. Due to the characteristics of the different access strategies, different levels of reliability of context information can be ensured, but at the same time, these strategies lead to different access traffic which impacts also the network performance, and hence feeds back to the reliability of the information. Furthermore, different levels of QoS may be available and used in order to mitigate the impact of network performance degradation on the reliability of the dynamic context information. In this paper we describe a system and algorithms that are capable of configuring effectively context access strategies in order to maximize reliability of all accessed dynamic context information. The framework utilizes and extends existing information reliability models, and it can utilize different network performance models. Simulation results of scenarios in which the framework uses finite-buffer bottleneck performance models demonstrate the effectiveness of our algorithm to increase reliability. Furthermore, the framework is applied to a scenario with QoS classes that allows to trade off delay and loss via different buffer-size configurations.
['Ahmed Shawky', 'Rasmus Løvenstein Olsen', 'Jens Myrup Pedersen', 'Hans-Peter Schwefel']
Network aware dynamic context subscription management