The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. ex. Some numerals are expressed as "XNUMX".
Copyrights notice
The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. Copyrights notice
MANET(Mobile Ad Hoc Network)은 본질적으로 동적 토폴로지를 가지고 있습니다. 이러한 네트워크의 분산된 다중 홉 특성으로 인해 노드의 무작위 이동성은 특정 노드 쌍 간의 무선 링크 가용성에 영향을 미칠 뿐만 아니라 통신 경로의 신뢰성, 서비스 검색, 심지어 MANET의 서비스 품질까지 위협합니다. 본 논문에서는 MANET의 링크 가용성을 예측하기 위해 새로운 Markov 체인 모델이 제시됩니다. 제안된 접근 방식은 두 노드 사이의 초기 거리에 대한 대략적인 추정을 기반으로 무작위 이동성 환경에서 링크 가용성을 정확하게 추정할 수 있습니다. 또한 제안된 링크 가용성 추정 접근 방식은 Max-Min d-clustering 휴리스틱에 통합됩니다. 강화된 클러스터링 휴리스틱이라고 합니다. M4C는 모바일 노드를 클러스터로 그룹화할 때 노드 이동성을 고려합니다. 클러스터링 알고리즘의 접근 방식과 성능 향상을 검증하기 위해 시뮬레이션 결과를 제공합니다. 또한 적응력을 보여줍니다. M4C, 그리고 다음을 보여줍니다. M4C 토폴로지 집계의 효율성과 클러스터 안정성 간의 균형을 이룰 수 있습니다. 제안된 알고리즘은 MANET의 서비스 가용성과 품질을 향상시키는 데에도 사용될 수 있습니다.
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부
Yuebin BAI, Jun HUANG, Qingmian HAN, Depei QIAN, "Link Availability Based Mobility-Aware Max-Min Multi-Hop Clustering (M4C) for Mobile Ad Hoc Networks" in IEICE TRANSACTIONS on Communications,
vol. E92-B, no. 10, pp. 3132-3142, October 2009, doi: 10.1587/transcom.E92.B.3132.
Abstract: Mobile Ad Hoc Networks (MANETs) have inherently dynamic topologies. Due to the distributed, multi-hop nature of these networks, random mobility of nodes not only affects the availability of radio links between particular node pairs, but also threatens the reliability of communication paths, service discovery, even quality of service of MANETs. In this paper, a novel Markov chain model is presented to predict link availability for MANETs. Based on a rough estimation of the initial distance between two nodes, the proposed approach is able to accurately estimate link availability in a random mobility environment. Furthermore, the proposed link availability estimation approach is integrated into Max-Min d-clustering heuristic. The enhanced clustering heuristic, called M4C, takes node mobility into account when it groups mobile nodes into clusters. Simulation results are given to verify the approach and the performance improvement of clustering algorithm. It also demonstrates the adaptability of M4C, and shows that M4C is able to achieve a tradeoff between the effectiveness of topology aggregation and cluster stabilities. The proposed algorithm can also be used to improve the availability and quality of services for MANETs.
URL: https://global.ieice.org/en_transactions/communications/10.1587/transcom.E92.B.3132/_p
부
@ARTICLE{e92-b_10_3132,
author={Yuebin BAI, Jun HUANG, Qingmian HAN, Depei QIAN, },
journal={IEICE TRANSACTIONS on Communications},
title={Link Availability Based Mobility-Aware Max-Min Multi-Hop Clustering (M4C) for Mobile Ad Hoc Networks},
year={2009},
volume={E92-B},
number={10},
pages={3132-3142},
abstract={Mobile Ad Hoc Networks (MANETs) have inherently dynamic topologies. Due to the distributed, multi-hop nature of these networks, random mobility of nodes not only affects the availability of radio links between particular node pairs, but also threatens the reliability of communication paths, service discovery, even quality of service of MANETs. In this paper, a novel Markov chain model is presented to predict link availability for MANETs. Based on a rough estimation of the initial distance between two nodes, the proposed approach is able to accurately estimate link availability in a random mobility environment. Furthermore, the proposed link availability estimation approach is integrated into Max-Min d-clustering heuristic. The enhanced clustering heuristic, called M4C, takes node mobility into account when it groups mobile nodes into clusters. Simulation results are given to verify the approach and the performance improvement of clustering algorithm. It also demonstrates the adaptability of M4C, and shows that M4C is able to achieve a tradeoff between the effectiveness of topology aggregation and cluster stabilities. The proposed algorithm can also be used to improve the availability and quality of services for MANETs.},
keywords={},
doi={10.1587/transcom.E92.B.3132},
ISSN={1745-1345},
month={October},}
부
TY - JOUR
TI - Link Availability Based Mobility-Aware Max-Min Multi-Hop Clustering (M4C) for Mobile Ad Hoc Networks
T2 - IEICE TRANSACTIONS on Communications
SP - 3132
EP - 3142
AU - Yuebin BAI
AU - Jun HUANG
AU - Qingmian HAN
AU - Depei QIAN
PY - 2009
DO - 10.1587/transcom.E92.B.3132
JO - IEICE TRANSACTIONS on Communications
SN - 1745-1345
VL - E92-B
IS - 10
JA - IEICE TRANSACTIONS on Communications
Y1 - October 2009
AB - Mobile Ad Hoc Networks (MANETs) have inherently dynamic topologies. Due to the distributed, multi-hop nature of these networks, random mobility of nodes not only affects the availability of radio links between particular node pairs, but also threatens the reliability of communication paths, service discovery, even quality of service of MANETs. In this paper, a novel Markov chain model is presented to predict link availability for MANETs. Based on a rough estimation of the initial distance between two nodes, the proposed approach is able to accurately estimate link availability in a random mobility environment. Furthermore, the proposed link availability estimation approach is integrated into Max-Min d-clustering heuristic. The enhanced clustering heuristic, called M4C, takes node mobility into account when it groups mobile nodes into clusters. Simulation results are given to verify the approach and the performance improvement of clustering algorithm. It also demonstrates the adaptability of M4C, and shows that M4C is able to achieve a tradeoff between the effectiveness of topology aggregation and cluster stabilities. The proposed algorithm can also be used to improve the availability and quality of services for MANETs.
ER -