Parallel Algorithm For Network Traffic Scheduling In Application-Specific Architectures

1988 ◽  
Author(s):  
Ronald P. Bianchini, Jr. ◽  
John P. Shen
Keyword(s):  
Parallel Algorithm ◽  
Network Traffic ◽  
Traffic Scheduling ◽  
Application Specific

Using Indirect Routing to Recover from Network Traffic Scheduling Estimation Error

2017 ◽  
Author(s):  
Conglong Li ◽  
Matthew K. Mukerjee ◽  
David G. Andersen ◽  
Srinivasan Seshan ◽  
Michael Kaminsky ◽  
...  
Keyword(s):  
Network Traffic ◽  
Estimation Error ◽  
Traffic Scheduling

scholarly journals A parallel algorithm for network traffic anomaly detection based on Isolation Forest

2018 ◽  
Vol 14 (11) ◽  
pp. 155014771881447 ◽  
Author(s):  
Xiaoling Tao ◽  
Yang Peng ◽  
Feng Zhao ◽  
Peichao Zhao ◽  
Yong Wang
Keyword(s):  
Anomaly Detection ◽  
Parallel Algorithm ◽  
Single Machine ◽  
Network Traffic ◽  
Large Network ◽  
Traffic Data ◽  
Network Applications ◽  
Traffic Anomaly ◽  
Isolation Forest ◽  
Traffic Anomaly Detection

With the rapid development of large-scale complex networks and proliferation of various social network applications, the amount of network traffic data generated is increasing tremendously, and efficient anomaly detection on those massive network traffic data is crucial to many network applications, such as malware detection, load balancing, network intrusion detection. Although there are many methods around for network traffic anomaly detection, they are all designed for single machine, failing to deal with the case that the network traffic data are so large that it is prohibitive for a single computer to store and process the data. To solve these problems, we propose a parallel algorithm based on Isolation Forest and Spark for network traffic anomaly detection. We combine the advantages of Isolation Forest algorithm in network traffic anomaly detection and big data processing capability of Spark technology. Meanwhile, we apply the idea of parallelization to the process of modeling and evaluation. In the calculation process, by assigning tasks to multiple compute nodes, Isolation Forest and Spark can efficiently perform anomaly detection and evaluation process. By this way, we can also solve the problem of computation bottleneck on single machine. Extensive experiments on real world datasets show that our Isolation Forest and Spark is efficient and scales well for anomaly detection on large network traffic data.

scholarly journals Termite inspired algorithm for traffic engineering in hybrid software defined networks

2020 ◽  
Vol 6 ◽  
pp. e283
Author(s):  
R Ananthalakshmi Ammal ◽  
Sajimon PC ◽  
Vinodchandra SS
Keyword(s):  
Network Traffic ◽  
Traffic Engineering ◽  
Test Bed ◽  
Network Resources ◽  
Traffic Scheduling ◽  
Physical Test ◽  
Multi Protocol Label Switching ◽  
Link Availability ◽  
Sdn Controller

In the era of Internet of Things and 5G networks, handling real time network traffic with the required Quality of Services and optimal utilization of network resources is a challenging task. Traffic Engineering provides mechanisms to guide network traffic to improve utilization of network resources and meet requirements of the network Quality of Service (QoS). Traditional networks use IP based and Multi-Protocol Label Switching (MPLS) based Traffic Engineering mechanisms. Software Defined Networking (SDN) have characteristics useful for solving traffic scheduling and management. Currently the traditional networks are not going to be replaced fully by SDN enabled resources and hence traffic engineering solutions for Hybrid IP/SDN setups have to be explored. In this paper we propose a new Termite Inspired Optimization algorithm for dynamic path allocation and better utilization of network links using hybrid SDN setup. The proposed bioinspired algorithm based on Termite behaviour implemented in the SDN Controller supports elastic bandwidth demands from applications, by avoiding congestion, handling traffic priority and link availability. Testing in both simulated and physical test bed demonstrate the performance of the algorithm with the support of SDN. In cases of link failures, the algorithm in the SDN Controller performs failure recovery gracefully. The algorithm also performs very well in congestion avoidance. The SDN based algorithm can be implemented in the existing traditional WAN as a hybrid setup and is a less complex, better alternative to the traditional MPLS Traffic Engineering setup.

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