PATHS: analysis of PATH duration statistics and their impact on reactive MANET routing protocols
Proceedings of the 4th ACM international symposium on Mobile ad hoc networking & computing
Strategies for Finding Stable Paths in Mobile Wireless Ad Hoc Networks
LCN '03 Proceedings of the 28th Annual IEEE International Conference on Local Computer Networks
A mobility-based framework for adaptive clustering in wireless ad hoc networks
IEEE Journal on Selected Areas in Communications
MULTIMEDIA '06 Proceedings of the 14th annual ACM international conference on Multimedia
Headlight prefetching for mobile media streaming
MobiDE '07 Proceedings of the 6th ACM international workshop on Data engineering for wireless and mobile access
An analysis framework for mobility metrics in mobile ad hoc networks
EURASIP Journal on Wireless Communications and Networking
Proceedings of the 15th international conference on Multimedia
Link quality estimation in wireless multi-hop networks using Kernel based methods
Computer Networks: The International Journal of Computer and Telecommunications Networking
Privacy preserving continuous multimedia streaming in MANETs
ACM Transactions on Multimedia Computing, Communications, and Applications (TOMCCAP)
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Numerous types of mobile devices are now popular with end users, who increasingly use them to carry multimedia content on the go. As wireless connectivity is integrated with more handhelds, streaming multimedia content among mobile peers is becoming a popular application. One of the main challenges in mobile streaming is the requirement that the link must be continuously available for a period of time to enable uninterrupted data transmission and a smooth media performance. Hence, an accurate prediction of future link availability is very desirable and allows, for example, the selection of the most stable link when a multimedia object is available from multiple peers. In this paper, we present a novel iterative algorithm for predicting continuous link availability between two mobile ad-hoc peers. Our method can function without the support of GPS equipment. By a rough estimation of the distance between two peers, our approach is able to accurately predict link availability over a short period of time. Experimental results show that our algorithm can accurately estimate the future link status with an error margin lower than 7%. To demonstrate the feasibility of our approach we have integrated our link prediction algorithm into MStream: a pioneering mobile audio streaming application. Simulation results show that our link availability model can reduce the number of link breaks and achieve smooth streaming experiences among mobile peers.