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 환경에서 모바일 노드 이동 또는 신호 페이딩으로 인한 빠른 토폴로지 변경으로 인해 기존 라우팅 복원 프로세스는 구현하는 데 비용이 많이 들고 네트워크 트래픽 오버헤드가 많이 발생하고 라우팅 경로 대기 시간이 길어질 수 있습니다. 인터넷 라우팅 프로토콜에 사용되는 전통적인 SPT(최단 경로 트리) 재계산 및 복원 방식을 채택하는 것은 MANET에 효과적으로 작동하지 않습니다. 차세대 SPT 복원 시스템의 목적은 SPT 복원 엔진이 과도한 SPT 계산을 건너뛸 수 있는 적응형 학습 제어 시스템을 사용하여 비용 효율적인 솔루션을 제공하는 것입니다. 우리는 CSPTR(Cognitive Shortest Path Tree Restoration)이라는 새로운 SPT 복원 방식을 제안했습니다. CSPTR은 NSM(Network Simplex Method) 및 SA(Sensitivity Analysis) 기술을 기반으로 설계되어 포괄적이고 저렴한 링크 오류 복구 프로세스를 제공합니다. NSM은 각 노드에 대한 최단 경로를 도출하는 데 사용되는 반면, SA를 사용하면 네트워크 토폴로지가 변경될 때 SPT를 불필요하게 다시 계산하는 노력을 크게 줄일 수 있습니다. 실제로 CSPTR의 학습 기능을 활성화하기 위해 SA 범위 테이블이 사용됩니다. 컴퓨팅 및 통신 오버헤드의 성능을 Dijstra의 알고리즘 및 증분 OSPF와 같은 잘 알려진 다른 두 가지 방식과 비교합니다. 결과는 CSPTR이 불필요한 SPT 재계산을 크게 제거하고 대량의 플러딩 오버헤드를 줄일 수 있음을 보여줍니다.
The copyright of the original papers published on this site belongs to IEICE. Unauthorized use of the original or translated papers is prohibited. See IEICE Provisions on Copyright for details.
부
Huan CHEN, Bo-Chao CHENG, Po-Kai TSENG, "Cognitive Shortest Path Tree Restoration (CSPTR) for MANET Using Cost-Sensitivity Analysis" in IEICE TRANSACTIONS on Communications,
vol. E92-B, no. 3, pp. 717-727, March 2009, doi: 10.1587/transcom.E92.B.717.
Abstract: With quick topology changes due to mobile node movement or signal fading in MANET environments, conventional routing restoration processes are costly to implement and may incur high flooding of network traffic overhead and long routing path latency. Adopting the traditional shortest path tree (SPT) recomputation and restoration schemes used in Internet routing protocols will not work effectively for MANET. An object of the next generation SPT restoration system is to provide a cost-effective solution using an adaptive learning control system, wherein the SPT restoration engine is able to skip over the heavy SPT computation. We proposed a novel SPT restoration scheme, called Cognitive Shortest Path Tree Restoration (CSPTR). CSPTR is designed based on the Network Simplex Method (NSM) and Sensitivity Analysis (SA) techniques to provide a comprehensive and low-cost link failure healing process. NSM is used to derive the shortest paths for each node, while the use of SA can greatly reduce the effort of unnecessary recomputation of the SPT when network topology changes. In practice, a SA range table is used to enable the learning capability of CSPTR. The performance of computing and communication overheads are compared with other two well-known schemes, such as Dijstra's algorithm and incremental OSPF. Results show that CSPTR can greatly eliminate unnecessary SPT recomputation and reduce large amounts of the flooding overheads.
URL: https://global.ieice.org/en_transactions/communications/10.1587/transcom.E92.B.717/_p
부
@ARTICLE{e92-b_3_717,
author={Huan CHEN, Bo-Chao CHENG, Po-Kai TSENG, },
journal={IEICE TRANSACTIONS on Communications},
title={Cognitive Shortest Path Tree Restoration (CSPTR) for MANET Using Cost-Sensitivity Analysis},
year={2009},
volume={E92-B},
number={3},
pages={717-727},
abstract={With quick topology changes due to mobile node movement or signal fading in MANET environments, conventional routing restoration processes are costly to implement and may incur high flooding of network traffic overhead and long routing path latency. Adopting the traditional shortest path tree (SPT) recomputation and restoration schemes used in Internet routing protocols will not work effectively for MANET. An object of the next generation SPT restoration system is to provide a cost-effective solution using an adaptive learning control system, wherein the SPT restoration engine is able to skip over the heavy SPT computation. We proposed a novel SPT restoration scheme, called Cognitive Shortest Path Tree Restoration (CSPTR). CSPTR is designed based on the Network Simplex Method (NSM) and Sensitivity Analysis (SA) techniques to provide a comprehensive and low-cost link failure healing process. NSM is used to derive the shortest paths for each node, while the use of SA can greatly reduce the effort of unnecessary recomputation of the SPT when network topology changes. In practice, a SA range table is used to enable the learning capability of CSPTR. The performance of computing and communication overheads are compared with other two well-known schemes, such as Dijstra's algorithm and incremental OSPF. Results show that CSPTR can greatly eliminate unnecessary SPT recomputation and reduce large amounts of the flooding overheads.},
keywords={},
doi={10.1587/transcom.E92.B.717},
ISSN={1745-1345},
month={March},}
부
TY - JOUR
TI - Cognitive Shortest Path Tree Restoration (CSPTR) for MANET Using Cost-Sensitivity Analysis
T2 - IEICE TRANSACTIONS on Communications
SP - 717
EP - 727
AU - Huan CHEN
AU - Bo-Chao CHENG
AU - Po-Kai TSENG
PY - 2009
DO - 10.1587/transcom.E92.B.717
JO - IEICE TRANSACTIONS on Communications
SN - 1745-1345
VL - E92-B
IS - 3
JA - IEICE TRANSACTIONS on Communications
Y1 - March 2009
AB - With quick topology changes due to mobile node movement or signal fading in MANET environments, conventional routing restoration processes are costly to implement and may incur high flooding of network traffic overhead and long routing path latency. Adopting the traditional shortest path tree (SPT) recomputation and restoration schemes used in Internet routing protocols will not work effectively for MANET. An object of the next generation SPT restoration system is to provide a cost-effective solution using an adaptive learning control system, wherein the SPT restoration engine is able to skip over the heavy SPT computation. We proposed a novel SPT restoration scheme, called Cognitive Shortest Path Tree Restoration (CSPTR). CSPTR is designed based on the Network Simplex Method (NSM) and Sensitivity Analysis (SA) techniques to provide a comprehensive and low-cost link failure healing process. NSM is used to derive the shortest paths for each node, while the use of SA can greatly reduce the effort of unnecessary recomputation of the SPT when network topology changes. In practice, a SA range table is used to enable the learning capability of CSPTR. The performance of computing and communication overheads are compared with other two well-known schemes, such as Dijstra's algorithm and incremental OSPF. Results show that CSPTR can greatly eliminate unnecessary SPT recomputation and reduce large amounts of the flooding overheads.
ER -