A traffic anomaly detection approach in communication networks for applications of multimedia medical devices

Jiang, Dingde; Zhen, Yuan; Zhang, Peng; Miao, Lei; Zhu, Ting

doi:10.1007/s11042-016-3402-6

Cited by 39 publications

(17 citation statements)

References 57 publications

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“…In [29], instead of supposing per-defined popularity for video contents, the authors find the important points in a video and proposed algorithm to give priority to cached these important points. Network traffic and energy efficiency have an important impact on the video, which is considered in [9,10] and [11].…”

Section: Related Workmentioning

confidence: 99%

Management of scalable video streaming in information centric networking

Ullah

Thar

Hong

2016

Multimed Tools Appl

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Ability of caching the contents is one of the most important feature of an Information Centric Networking (ICN) node. By managing the cache space intelligently we can improve network's performance and increase users' Quality of Experience (QoE). Moreover, scalable video streaming in ICN is envisioned to be very beneficial as well as a challenging issue. In this paper, we are proposing a mechanism for cache management and request forwarding policies for scalable video streaming in ICN. Our proposed cache decision policy ensures to cache the base layer of a scalable video near to the users, which is mandatory layer for decoding any SVC encoded video and is needed by all the users with any data-rate budget, and consequently cache the higher layers in the upper nodes in the CCN/ICN within a specific RTT range. Furthermore, our intelligent cache decision cover fairness by considering router's cache capacity (inside the RTT range) and at the same time giving more priority to the nodes that are nearer to the users. A limited cooperative request forwarding mechanism, which is the part of our proposal, plays a role to improve users' QoE by providing the popular requested contents quickly. We have intensively simulated our proposed cache management and request forwarding scheme. The simulation results show that our proposed solution outperforms the current cache management schemes and improve the cache utilization. Also our proposed scheme decrease the traffic flowing inside the network by eliminating the request flooding and providing the requested contents from the nearby location to the users. The proposed scheme provides video faster to the users, specially the mandatory base layer is provided very quickly to the users.

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Section: Related Workmentioning

confidence: 99%

Management of scalable video streaming in information centric networking

Ullah

Thar

Hong

2016

Multimed Tools Appl

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“…Accordingly, a period signal model could accurately to detection and diagnose abnormal network traffic. Additionally, the detection method for multimedia traffic was also presented to guarantee network performance [8]. A new detection approach was proposed to find out abnormal network events [12][13][14][15].…”

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confidence: 99%

A Bayes Learning-based Anomaly Detection Approach in Large-scale Networks

He¹

2017

dtcse

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Abstract. With quick developments of new application patterns and network technologies, network anomalies have an important impact on network operations. How to accurately detect network anomalies has become the hot topic in current communication networks. This paper proposes a new detection approach to diagnose the anomaly in network traffic. Firstly, we use the Bayes learning theory to describe network traffic properties. By the learning process, normal network traffic can correctly be modeled. Secondly, the feature extraction is used to differentiate abnormal network traffic from normal huge traffic. Thirdly, the detail detection algorithm is presented to find the anomalous component in network traffic. Finally, we carry out the detailed simulation experiments. Simulation results indicate that our approach is effective.

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“…Generally, we wish Equation (8) to be equal to zero. Because of the time-varying and correlated nature, there always exists some bias in Equation (8).…”

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confidence: 99%

“…Because of the time-varying and correlated nature, there always exists some bias in Equation (8). Only when the bias is minimum, can we attain the optimal model for the end-to-end network traffic.…”

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confidence: 99%

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A Bayes Theory-Based Modeling Algorithm to End-to-end Network Traffic

et al. 2016

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Abstract.Recently, network traffic has exponentially increasing due to all kind of applications, such as mobile Internet, smart cities, smart transportations, Internet of things, and so on. the end-to-end network traffic becomes more important for traffic engineering. Usually end-to-end traffic estimation is highly difficult. This paper proposes a Bayes theory-based method to model the end-to-end network traffic. Firstly, the end-to-end network traffic is described as a independent identically distributed normal process. Then the Bases theory is used to characterize the end-to-end network traffic. By calculating the parameters, the model is determined correctly. Simulation results show that our approach is feasible and effective.

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A traffic anomaly detection approach in communication networks for applications of multimedia medical devices

Cited by 39 publications

References 57 publications

Management of scalable video streaming in information centric networking

Management of scalable video streaming in information centric networking

A Bayes Learning-based Anomaly Detection Approach in Large-scale Networks

A Bayes Theory-Based Modeling Algorithm to End-to-end Network Traffic

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