نتایج جستجو برای: mobility prediction

تعداد نتایج: 345876  

2003
Nianjun Zhou Alhussein A. Abouzeid

In this paper, we define the routing overhead as the amount of information needed to describe the changes in a network topology. We derive a universal lower bound on the routing overhead in a mobile ad-hoc network. We also consider a prediction-based routing protocol that attempts to minimize the routing overhead by predicting the changes in the network topology from the previous mobility patte...

Journal: :CoRR 2010
Biju Issac K. Hamid C. E. Tan

In an IEEE 802.11 Infrastructure network, as the mobile node is moving from one access point to another, the resource allocation and smooth hand off may be a problem. If some reliable prediction is done on mobile node’s next move, then resources can be allocated optimally as the mobile node moves around. This would increase the performance throughput of wireless network. We plan to investigate ...

2006
Andre E. Bergh

Achieving seamless mobility is a major challenge for future wireless networks. Presently, low latency handover protocols such as FMIPv6 depend heavily on link-layer triggers to facilitate proactive handovers. Differences in link-layer technologies and the absence of a standardised trigger model makes it difficult to achieve fast vertical handovers in a multi-access environment. This paper intro...

2002
Wenye Wang Ian F. Akyildiz

AbsfracfThis paper presents a new scheme to estimate the user mobility by incorporating the aggregate history of mobile users and system parameters. With this approach, each user’s position within the location area is differentiated by zone partition for more accurate prediction. In order tn provide the flexibility of tradeoff between quality demand and computation complexity, the estimation is...

Journal: :Journal of Advanced Transportation 2022

Predicting individual mobility of subway passengers in large crowding events is crucial for safety management and crowd control. However, most previous models focused on prediction under ordinary conditions. Here, we develop a passenger model, which also applicable to events. The developed model includes the trip-making part trip attribute part. For prediction, regularized logistic regression t...

Journal: :International Journal of Interactive Mobile Technologies (iJIM) 2020

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