Structural analysis of network traffic flows

Many Massively Multiplayer Online Role-Playing Games (MMORPGs) use TCP flows for communication between the server and the game clients. The utilization of TCP, which was not initially designed for (soft) real-time services, has many implications for the competing traffic flows. In this paper we present a series of studies which explore the competition between MMORPG and other traffic flows. For that aim, we first extend a source-based traffic model, based on player’s activities during the day, to also incorporate the impact of the number of players sharing a server (server population) on network traffic. Based on real traffic traces, we statistically model the influence of the variation of the server’s player population on the network traffic, depending on the action categories (i.e., types of in-game player behaviour). Using the developed traffic model we prove that while server population only modifies specific action categories, this effect is significant enough to be observed on the overall traffic. We find that TCPVegasis a good option for competing flows in order not to throttle the MMORPG flows and that TCP SACK is more respectful with game flows than other TCP variants, namely,Tahoe, Reno,andNew Reno. Other tests show that MMORPG flows do not significantly reduce their sending window size when competing against UDP flows. Additionally, we study the effect of RTT unfairness between MMORPG flows, showing that it is less important than in the case of network-limited TCP flows.

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Structural analysis of network traffic matrix via relaxed principal component pursuit

Computer Networks ◽

10.1016/j.comnet.2012.02.017 ◽

2012 ◽

Vol 56 (7) ◽

pp. 2049-2067 ◽

Cited By ~ 24

Author(s):

Zhe Wang ◽

Kai Hu ◽

Ke Xu ◽

Baolin Yin ◽

Xiaowen Dong

Keyword(s):

Structural Analysis ◽

Network Traffic ◽

Principal Component ◽

Traffic Matrix ◽

Principal Component Pursuit

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Analysis of Stability-To-Chaos in the Dynamic Evolution of Network Traffic Flows under a Dual Updating Mechanism

10.32920/14639076.v1 ◽

2021 ◽

Author(s):

Shixu Liu ◽

Hao Yan ◽

Said M. Easa ◽

Lidan Guo ◽

Yingnuo Tang

Keyword(s):

Traffic Flow ◽

Network Traffic ◽

Numerical Experiments ◽

Dynamic Theory ◽

Evolutionary Model ◽

Dynamic Evolution ◽

Traffic Flows ◽

Route Network ◽

Analysis Of Stability ◽

Route Cost

This paper proposes a traffic-flow evolutionary model under a dual updating mechanism that describes the day-to-day (DTD) dynamics of traffic flow and travel cost. To illustrate the concept, a simple two-route network is considered. Based on the nonlinear dynamic theory, the equilibrium stability condition of the system is derived and the condition for the division between the bifurcation and chaotic states of the system is determined. The characteristics of the DTD dynamic evolution of network traffic flow are investigated using numerical experiments. The results show that the system is absolutely stable when the sensitivity of travelers toward the route cost parameter (θ) is equal to or less than 0.923. The bifurcation appears in the system when θ is larger than 0.923. For values of θ equal to or larger than 4.402, the chaos appears in the evolution of the system. The results also show that with the appearance of chaos, the boundary and interior crises begin to appear in the system when θ is larger than 6.773 and 10.403, respectively. The evolution of network traffic flow is always stable when the proportion of travelers who do not change the route is 84% or greater.

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Visualization of Anomalies using Graph-Based Anomaly Detection

The International FLAIRS Conference Proceedings ◽

10.32473/flairs.v34i1.128554 ◽

2021 ◽

Vol 34 (1) ◽

Author(s):

Ramesh Paudel ◽

Lauren Tharp ◽

Dulce Kaiser ◽

William Eberle ◽

Gerald Gannod

Keyword(s):

Anomaly Detection ◽

Network Traffic ◽

False Positives ◽

Visual Context ◽

Traffic Flows ◽

Security Analysts ◽

Fast Analysis ◽

Detection Systems ◽

Potential Damage ◽

Network Anomaly Detection

Network protocol analyzers such asWireshark are valuable for analyzing network traffic but pose a challenge in that it can be difficult to determine which behaviors are out of the ordinary due to the volume of data that must be analyzed. Network anomaly detection systems can provide vital insights to security analysts to supplement protocol analyzers, but this feedback can be difficult to interpret due to the complexity of the algorithms used and the lack of context to determine the reasoning for which an event was labeled as anomalous. We present an approach for visualizing anomalies using a graph-based anomaly detection methodology that aims to provide visual context to network traffic. We demonstrate the approach using network traffic flows as an approach for aiding in the investigation and triage of anomalous network events. The simplicity of a visual representation supports fast analysis of anomalous traffic to identify true positives from false positives and prevent further potential damage.

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