Article Spotlight: Characterization of the Traffic in IP-Based Communication Networks

In this study which delves into network packet characterisation by analysing the approximations for the size of the inbound packets, two identicial networks with distinct IP services have their packet tracked at the work station level. This leads to 2 measurements: Monitoring the work of different protocols and the usabiity of their ports and packet size monitoring and the moments between the entry of the packets into the network. With data capture taking place over 1 second intervals, it can be accurately observed that the change between 0 and 1.2 MB/s that the traffic is uneven and heterogenous, typical for these kinds of networks. As for protocol use, it can be observed that multimedia content is the main driver of traffic volume for this network, mostly from HTTP and SSL packets. As for distribution of the intervals between packets' inbound activity, Dagum approximation can be observed, achieved through the weight coefficients and the Kolmogorov-Simrnov criteria, thus allowing for inferences of the optimal use of the monitored network. As for network B, which consits of the IP-based PBXs (OSV – Open Scape Voice and Asterisk now) and several IP-phones connected to a single switch and a workstation also connected to a mirroring port that momnitors the traffic, there is observably more traffic load due to the active devices making up the bulk of the traffic. The active devices are mainly IP phones and the IP PBX (the Asterisk telephone exchange), which accounts for the distribution of traffic through UDP port 5010. The points in which the network is most loaded are for video content when accounting for the compression used in the SIP sessions, with video information compressed with H.264 and audion information with G711. A connection matrix reveals that the group of devices interconnected by a device with IP 10..21.23.69, an Asterisk telephone exchange, with analysis showing that all traffic pass through this point. On the other hand, the OSV exchange (Open Scape Voice) is only active for the exchange signalling between two devices.

Characterisation of busy-hour traffic of IP networks based on their intrinsic features

Characterisation of busy-hour traffic of IP networks based on their intrinsic features is a scientific paper that discusses the use of statistical techniques to model the behaviour of busy-hour traffic, especially to give network designers and architects grounded data on how to plan for a network based on the critical measure of peak network use. The main experiment conducted for this paper consisted of observational traffic analysis, with the data rate measured during busy hours. The solution explored an architecture that consisted of an initial stage for data cleaning followed by statistical regression. This latter step was modelled to find the relationship between two variables: number of users (predictor variable) vs traffic volume (target variable). These two variables are analysed to check whether there is a real relationship between them regardless of physical location or link capacity. It eventually came to light that the analysed traffic, which stemmed from a number of educational institutions and local networks, follows a White Gaussian Process, meaning that data us uncorrelated, comprising of random and independent fluctuations. What also entails from this observation is that the samples of traffic distribution follow a normal (bell-shaped) curve. Whereas a normal process would reveal that traffic in the real world would be coloured, with clearly defined correlations, a White Gaussian process indicates the presence of noise, meaning that the variables are unrelated due to presence of noise. A White Gaussian Process can also make for a simplified thought process which relies on simple math to predict probabilities of the network being overwhelmed, like predicting the network throughput in conrete numbers e.g.: gbps where the traffic rate becomes throtelled. Lastly, it has been concluded that the relationship between user population and traffic use can be modelled by the ANOVA and ANCOVA analytical techniques. The former stands for analysis of variance, which consists of a test to check whether the means of distinct groups are significantly different. The latter technique handles covariance, which couples ANOVA with regression, detailing how a dependent variable changes according to a determining factor while controlling for another factor. The use of tThese two techniques were arrived at through Goodness-of-fit tests, namely, tools to confirm that the traffic variation was mlinked to the number of users. Ultimately, the authors were able to fit the model to a linear regression analysis, derivating the formula for traffic: (traffic per user) x (number of users) + error term.

Article spotlight: "A Packet-level Characterization of Network Traffic"

"A Packet-level Characterization of Network Traffic" is a scientific paper published by by Alberto Dainotti, Antonio Pescape, and Giorgio Ventre. In this paper, an alternate approach to network characterisation is proposed at the packet level, thus leveraging the overall structure of the network packet, which tends to remain largely the same, thus providing an opportunity to come up with an agnostic framework for network analysis even if there are eventual changes in network protocol technologies. Relying on the packet structure means that this approach moves away from solutions centred around a simple network application such as FTP, SMTP, DNS etc. The network traffic analysis relies only on 2 metrics: packet size and Inter-Packet Time. With information from 2 major educational institutions, over a billion packets and million client server pairs in addition to SMTP and HTTP traffic, the research concerned with spatial and time invariance, that is, whether traffic patterns remained largely the same for different time slices (days, weeks, months etc) and at different locations. With packet-level analyses useful for traffic simulation and congestion analysis, the findings allow for planned network capacity regarding traffic rates, bandwidth, latency and packet loss. The distributional patterns found in the paper allow for traffic simulation to be generated, thus allowing for further future studies in the field of jitter, packet loss and delay. Moreover, this study allowed to discover the use of http port 80 to run p2p traffic, thus revealing the capacity for security diagnosis at the packet level. The architectural pipeline of the proposed solution starts with the reading of packet capture from 2 major network links, which then proceed to be filtered into either SMTP or HTTP traffic, with IP address scrambling taking place for privacy purposes. Unwanted traffic is filtered out, leaving only the data that is useful for the traffic analysis appropriate for the analysis of HTTP and SMTP patterns, thus allowing for the modelling of statistical models using packet size and inter-packet time, demonstrating space and time invariance across different situations and paving the way for model reuse on the strength of packet structure remaining independent of future protocol implementations.

Ein Hinblick in der Zukunft

Mit ihrer Absegnung, ich darf mich einen wenigen Dampf ablassen. Ich werde viel zu viel erledigen, währendessen die derzeitige Umstände mich nicht zurückblicken. Es hat sich nachgewiesen, dass Erfolg und Leistungen sind vorübergehend. Nur Anstrengung. Meine Fähigkeiten gelten allgemeinen nur für die nächste Herausforderung. Und dann kommt es wieder zurück. Meine Bemühung muss sich mit dem nächsten Ziel befassen. Nachgewiesen is dass Erfolgreiche Händlungen gibt es nicht; man geht immer noch zu seiner eigenen Angelegenheiten zurück.