DocumentCode :
3307295
Title :
Predict and spread: An efficient routing algorithm for opportunistic networking
Author :
Niu, Jianwei ; Guo, Jinkai ; Cai, Qingsong ; Sadeh, Norman ; Guo, Shaohui
Author_Institution :
Sch. of Comput. Sci. & Eng., Beihang Univ., Beijing, China
fYear :
2011
fDate :
28-31 March 2011
Firstpage :
498
Lastpage :
503
Abstract :
With their proliferation and increasing capabilities, mobile devices with local wireless interfaces can be organized into opportunistic networks that exploit communication opportunities arising out of the movement of their users. Because the nodes are carried by people, these opportunistic networks can also be viewed as social networks. Unfortunately, existing routing algorithms for opportunistic networks rely on relatively simple mobility models that rarely consider these social network characteristics. In this paper, we propose PreS (Predict and Spread), an efficient routing algorithm for opportunistic networking that employs an adapted Markov chain to model a node´s mobility pattern, and capture its social characteristics. A comparison with state-of-the-art algorithms suggests that PreS can yield better performance in terms of delivery ratio and delivery latency, and approaches the performance of the Epidemic algorithm with lower resource consumption.
Keywords :
Markov processes; mobility management (mobile radio); telecommunication network routing; adapted Markov chain; delivery latency; delivery ratio; epidemic algorithm; local wireless interface; mobile device; mobility pattern; opportunistic networking; predict and spread algorithm; routing algorithm; social network; Adaptation model; Algorithm design and analysis; Markov processes; Prediction algorithms; Probability; Relays; Routing; Markov chain; delay tolerant networks; message forwarding; mobility model; opportunistic networks;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Wireless Communications and Networking Conference (WCNC), 2011 IEEE
Conference_Location :
Cancun, Quintana Roo
ISSN :
1525-3511
Print_ISBN :
978-1-61284-255-4
Type :
conf
DOI :
10.1109/WCNC.2011.5779183
Filename :
5779183
Link To Document :
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