Title :
A delay/disruption tolerant routing algorithm based on traffic prediction
Author :
Yongtao Wei ; Junwei Wang
Author_Institution :
Sch. of Inf. Sci. & Eng., Northeastern Univ., Shenyang, China
Abstract :
Delay/Disruption tolerant networks (DTNs) are a class of emerging networks that experience frequent and long-duration partitions. These networks have a variety of applications in situations such as crisis environments and deep-space communication. In this paper, the problem of traffic prediction in DTNs is studied. While traffic prediction in the Internet and mobile ad hoc networks has been studied extensively, due to the unique characteristic of frequent partitioning in DTNs, traffic prediction in DTNs is a considerably different and challenging problem. It brings new issues to the design of routing algorithms. In this paper, we propose new semantic models for DTN traffic prediction and develop traffic prediction based routing algorithm. This paper present a framework to evaluate these algorithms in DTNs. The object is to understand how routing performance is affected by the availability of traffic prediction and to guide the design of DTN routing protocols. Simulations show that efficient traffic prediction routing for DTNs can be constructed using only partial knowledge. In addition, routing algorithms that with traffic prediction achieve better delivery ratios, especially when available knowledge is limited.
Keywords :
Internet of Things; delay tolerant networks; telecommunication network routing; telecommunication traffic; DTN routing protocols; DTN traffic prediction; Internet; deep space communication; delay-disruption tolerant routing algorithm; mobile ad hoc networks; traffic prediction; Algorithm design and analysis; Delays; Prediction algorithms; Predictive models; Routing; Time series analysis; Wavelet transforms; delay/disruption tolerant; probability prediction; routing;
Conference_Titel :
Control and Decision Conference (CCDC), 2015 27th Chinese
Conference_Location :
Qingdao
Print_ISBN :
978-1-4799-7016-2
DOI :
10.1109/CCDC.2015.7162481