Multilevel Hierarchical Mobility Management in Densely Meshed Networks

Kawano, Keiichi; Kinoshita, Kazuhiko; Murakami, Koso

doi:10.1093/ietcom/e89-b.7.2002

Cited by 5 publications

(2 citation statements)

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“…Faster MNs select more distant MAPs, as it is believed that faster movement leads to a larger moving area. In [7] the use of a speed-based algorithm in synthetic meshed networks was studied.…”

Section: Overview Of Related Algorithmsmentioning

confidence: 99%

“…For the purpose of performance evaluation we used a simulation model, implemented in C#. Unlike the majority of proposed solutions, we used a non-tree-like synthetic topology, similar to that in [7], achieving better simulation of random MAP coverage area overlaps. We simulated 100 MAPs, distributed over 233 ARs, each AR covering a single radio cell.…”

Section: A Simulation Modelmentioning

confidence: 99%

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MAP Selection Algorithms Based on Future Movement Prediction Capability in Synthetic and Realistic Environment

Vilhar

Novak

Kandus

2008

JCOMSS

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Efficient mobility management involves micromobilityprinciples. The performance of the Hierarchical MobileIPv6 (HMIPv6) protocol, a representative micro-mobilityapproach, is affected by the Mobility Anchor Point (MAP)selection. In this paper, we propose a new selection method based on a prediction of the future movements of Mobile Nodes (MNs). The proposed algorithms exploit the information about the future availability of MAPs and choose those MAPs that assure a better service. An improvement to the evaluation methodology is also proposed. The algorithms are compared to each other notonly in synthetic but also in realistic internet topologies, which has not been a practice in the past. The simulation results show promising improvements in terms of distance from chosen MAPs and frequency of MAP changes. Moreover, we showed that, for perceivable improvement of MAP selection, absolute accuracy of movement prediction is not required. As pioneers in the mobility management analysis in realistic environment, we ascertain that offering MAP services over more than one Autonomous System (AS) proves beneficial.

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Section: Overview Of Related Algorithmsmentioning

confidence: 99%

Section: A Simulation Modelmentioning

confidence: 99%