The increasing availability of mobile devices with wireless communication capabilities stimulates considering new service provisioning environments where accessibility to the traditional Internet is provided via Access Points (APs) working as bridges between fixed hosts and wireless devices. The most notable example is the case of IEEE 802.11 APs that support connectivity of Wi-Fi terminals to a wired local area network. In the following, we will indicate these integrated networks with fixed Internet hosts, wireless terminals, and wireless APs in between, as the Wireless Internet (WI).
WI opens new challenging scenarios for mobile service provisioning. On the one hand, time-continuous services, such as audio/video streaming, relevantly suffer from the temporary disconnections that mobile clients experience at their handovers from old Wi-Fi access localities to new ones; in addition, they often require moving reached session states in newly visited localities. On the other hand, WI pushes towards the possibility to provide novel services whose contents depend on client location; location dependency complicates application design and implementation, and requires innovative support functions.
We claim that both mobile services with session continuity requirements and location-dependent ones can relevantly benefit from the adoption of lightweight and decentralized mechanisms capable of predicting wireless client handover between WI access localities. In particular, the idea is to provide support functions for
Our work on handover and mobility prediction is part of our original middleware for the support of WI service provisioning, which transparently mediates wireless client access to distributed applications via mobile proxies that dynamically adapt service results to client terminal properties, location, and runtime resource availability.
Let us stress that our prediction solution is completely local and decentralized: each wireless client hosts its own predictor, whose results only depend on either actual or filtered RSSI values for all APs in visibility, with no need of interacting with either other clients in its WI access localities or support components running in the wired infrastructure. Our middleware simply exploits the local RSSI monitoring data that IEEE 802.11 client cards have to collect anyway to be compliant with the standard; the middleware-level awareness of RSSI data is achieved in a completely portable way over heterogeneous platforms, as detailed in.
Last update: 4-may-10