ISP’s Internet Backbone Augmentation using Virtual Link Configuration in Link-state Routing

2001 ◽  
pp. 123-133
Author(s):  
Do-Hoon Kim ◽  
Soon-Ho Lee ◽  
Dong-Wang Tcha
Keyword(s):  
Virtual Link ◽  
Internet Backbone ◽  
Link State

ENHANCING INTERNET NETWORK RELIABILITY WITH INTEGRATED FRAMEWORK OF MULTI-OBJECTIVE GENETIC ALGORITHM AND MONTE CARLO SIMULATION

2008 ◽  
Vol 25 (06) ◽  
pp. 837-846 ◽  
Author(s):  
JONG-RYUL KIM ◽  
DOHOON KIM
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Decision Model ◽  
Network Reliability ◽  
Virtual Link ◽  
Multi Objective ◽  
Link State ◽  
Operational Costs ◽  
Multi Objective Genetic Algorithm ◽  
Routing Performance

This paper presents a combined framework of Multi-Objective Generic Algorithm (MOGA) and Monte Carlo Simulation (MCS) in order to improve backbone topology by leveraging the Virtual Link (VL) system in an hierarchical Link-State (LS) routing domain. Given that the sound backbone topology structure has a great impact on the overall routing performance in a hierarchical LS domain, the importance of this research is evident. The proposed decision model is to find an optimal configuration of VLs that properly meets two-pronged engineering goals in installing and maintaining VLs: i.e., operational costs and network reliability. The experiment results clearly indicates that it is essential to the effective operations of hierarchical LS routing domain to consider not only engineering aspects but also specific benefits from systematical layout of VLs, thereby presenting the validity of the decision model and MOGA with MCS.

Multipoint Relay Selections with QoS Support in Link State Routing Protocol for Multi-Hop Wireless Networks

2009 ◽  
Vol E92-A (9) ◽  
pp. 2218-2226
Author(s):  
Takeaki KOGA ◽  
Shigeaki TAGASHIRA ◽  
Teruaki KITASUKA ◽  
Tsuneo NAKANISHI ◽  
Akira FUKUDA
Keyword(s):  
Wireless Networks ◽  
Routing Protocol ◽  
Link State

scholarly journals GAMPAL: an anomaly detection mechanism for Internet backbone traffic by flow size prediction with LSTM-RNN

2021 ◽  
Author(s):  
Taku Wakui ◽  
Takao Kondo ◽  
Fumio Teraoka
Keyword(s):  
Anomaly Detection ◽  
Short Term Memory ◽  
Denial Of Service ◽  
General Purpose ◽  
Traffic Information ◽  
Traffic Patterns ◽  
Detection Mechanism ◽  
Internet Service ◽  
Internet Backbone ◽  
Backbone Network

AbstractThis paper proposes a general-purpose anomaly detection mechanism for Internet backbone traffic named GAMPAL (General-purpose Anomaly detection Mechanism using Prefix Aggregate without Labeled data). GAMPAL does not require labeled data to achieve general-purpose anomaly detection. For scalability to the number of entries in the BGP RIB (Border Gateway Protocol Routing Information Base), GAMPAL introduces prefix aggregate. The BGP RIB entries are classified into prefix aggregates, each of which is identified with the first three AS (Autonomous System) numbers in the AS_PATH attribute. GAMPAL establishes a prediction model for traffic sizes based on past traffic sizes. It adopts a LSTM-RNN (Long Short-Term Memory Recurrent Neural Network) model that focuses on the periodicity of the Internet traffic patterns at a weekly scale. The validity of GAMPAL is evaluated using real traffic information, BGP RIBs exported from the WIDE backbone network (AS2500), a nationwide backbone network for research and educational organizations in Japan, and the dataset of an ISP (Internet Service Provider) in Spain. As a result, GAMPAL successfully detects anomalies such as increased traffic due to an event, DDoS (Distributed Denial of Service) attacks targeted at a stub organization, a connection failure, an SSH (Secure Shell) scan attack, and anomaly spam.

Performance Evaluation of Optimized Link State Routing-based Localization

2007 ◽  
Author(s):  
Tomoya Takenaka ◽  
Hiroshi Mineno ◽  
Yuichi Tokunaga ◽  
Naoto Miyauchi ◽  
Tadanori Mizuno
Keyword(s):  
Performance Evaluation ◽  
Link State ◽  
Optimized Link State Routing
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