Seferin Mirtchev

Data and Traffic Models in 5G Network

This chapter presents data and traffic analyses in 5G networks. We setup experiments with Zigbee sensors and measure different traffic patterns by changing the environmental conditions and number of channels. Due to the differences in read, write operations, message fragmentations and backoff of the Carrier Sense Multiple Access/Collision Avoidance algorithm we demonstrated that the traffic flows are changing dynamically. This leads to different behaviour of the network domain and requires special attention to network design. Statistical analyses are performed using Easyfit tool. It allows to find best fitting probability density function of traffic flows, approximation toward selected distributions as Pareto and Gamma and random number generation with selected distribution. Our chapter concludes with future plan for distribution parameters mapping to different traffic patterns, network topologies, different protocols and experimental environment.

Traffic sources measurement and analysis in UMTS

In this paper, we show statistical analyses of several types of traffic sources in a UMTS network, namely, voice, video, and data sources. For each traffic source type measurements were collected in order to, on the one hand, gain better understanding of the statistical characteristics of the sources and, on the other hand, enable forecasting traffic behavior in the network. The latter can be used to estimate service times and Quality of Service. Based on evaluation of packet inter-arrival times, we propose the Polya distribution to be used in network simulations or in estimations of available capacity in opportunistic sessions. Our results can be applied for dynamic network configuration in order to avoid potential network congestions or overflows.

Generic IP Network Traffic Management from Measurement through Analyses to Simulation

The aim of this chapter is to present different approaches to network traffic management applicable to the IP, transport and application layers in IP, 3G, WiMAX and 4G technologies. The proposed technology for analysis is flexible enough to different types of traffic in opportunistic networks. We start with traffic measurements and obtain accurate data for detail network simulations and precise analysis. Then, we highlight the self-similar nature of the incoming traffic at network nodes. In our next analysis, we look at mapping the measured data with the Polya arrival process by Pareto and gamma distributed inter-arrival times. Polya, Pareto and gamma distributions have the capability to change shape and scale in a way to simulate different types of observed traffic. A proper analytical description of the end-recipient traffic flows and point process of self-similarity inputs are applied for a better user behavior specification. During an end-to-end simulation, more complex queuing models with priorities are proposed. The behavior of the system at its bounds is shown. We map the data from measurements and simulations with the application layer requirements, cross-layer Quality of Service (QoS) and Quality of Experience (QoE) parameters. This is done by traffic fractality analyses, codec-dependent resource reallocation and Fibonacci backward difference traffic moments analyses. All of them demonstrate special moments in the breakdown of the shaping effect. Finally, we express views on openresearch issues for offering optimization in the Internet traffic analyses.

New constant service time Polya/D/n traffic model with peaked input stream

Abstract In this paper, we study the buffer queueing behaviour in high-speed networks. Some limited analytical derivations of queue models have been proposed in literature but their solutions are often a great mathematical challenge. We propose to use the Polya distribution to overcome such limitations. The specific behaviour of an IP interface with bursty traffic and long-range dependence is investigated by a version of the “classical” M/D/ n queueing model called Polya/D/ n . This is queueing system with a Polya input stream (a negative binomial distributed number of arrivals in a fixed time interval), a constant service time, multiple servers, and infinite waiting rooms. The model is considered a renewal process because of its quasi-random input stream and constant service time. We develop balance equations for the state of the system and obtain results for the packet loss and delay. The finding that the Polya distribution is adequate to model bursty input streams in IP network interfaces has motivated the proposal to evaluate the Polya/D/ n system. It is shown that the variance in the input stream significantly changes the characteristics of the waiting system. The suggested model is new and allows defining different bursty traffic and evaluating losses and delays relatively easily.

AALaaS intelligent backhauls for P2P communication in 5G mobile networks

Ambient Assisted Living as a Service (AALaaS) implementation is an emerging area of research and many different solutions could be found worldwide. In this paper, a decentralized foggy solution that well be context-aware and data-oriented is proposed. The new intelligent Peer-to-Peer framework supporting the Radio Access Network (RAN) management, which analyzes dynamically the traffic from the mobile device to different backhaul networks, and suggests most effective routing is fully decentralized and allows data residing. Many access networks will be based on zigbee or similar technology and will allow distributed data collection and dynamic network topologies. Simulation and laboratory experiments of zigbee access network demonstrates type of data to be stored and transmitted in the fog.

Traffic shaping measurements and analyses in 3G network

Traffic shaping effect may have significant impact on end-to-end Quality of Service (QoS) provisioning. Therefore, it should be carefully studied in order to allow the creation of appropriate traffic models to be used for simulations. First, to demonstrate the traffic shaping effect, we present statistical analyses on real-time measurements of diverse traffic sources (voice and video over IP) in a 3G network. By comparing the statistical distributions of the packet inter-arrival times for both the forward and backward direction, we can demonstrate directly the end-to-end traffic shaping effect introduced by the IP core network. Hence, we argue that distributed QoS management approach is needed. Additionally, we give the mean, variance, mean standard deviation, skewness, and kurtosis of the inter-arrival times, which can be used as input for simulation models. The accurate validation of the probability distributions is ensured by the Wolfram Mathematica and Crystal Ball statistical tools. Second, for the same set of measurements, we propose and defend with evaluations the use of the gamma distribution as best fitting function to traffic dynamics. Our proposal is applicable for traffic environments found in delay-tolerant networks, opportunistic networks, Internet of Things, sensor networks etc.

A Generalized Erlang-C Model for the Enhanced Living Environment as a Service ELEaaS

Abstract In this article, a full-access waiting multi-server queue with a statedependent arrival and departure processes is investigated and suggested for use as a generic traffic model of the novel concept of the Enhanced Living Environment as a Service (ELEaaS). The generalized arrival and service flows with nonlinear state dependence intensities are used. The idea is based on the analytical continuation of the Poisson arrival process and Bernoulli service process, and the classic M/M/n queuing system. Birth and death processes and state-dependent rates are applied. The suggested new queuing system is of a M(g)/M(g)/n/k type (in Kendal notation) with a generalized arrival and departure processes M(g). The input and output intensities depend nonlinearly on the system state with defined parameters - the socalled “peaked factors”. The state probabilities of the system are obtained using the general solution of the birth and death processes. The influence of the peaked factors on the queuing behavior is evaluated showing that state-dependent arrival and service rates may change significantly the characteristics of the queuing system. The simplicity and uniformity in representing both peaked and smooth behavior make this queuing model also attractive for future networks’ analysis and synthesis.

3G network traffic sources measurement and analysis

In this paper, we show statistical analyses of several types of traffic sources in a 3G network, namely voice, video and data sources. For each traffic source type, measurements were collected in order to, on the one hand, gain better understanding of the statistical characteristics of the sources and, on the other hand, enable forecasting traffic behaviour in the network. The latter can be used to estimate service times and quality of service parameters. The probability density function, mean, variance, mean square deviation, skewness and kurtosis of the interarrival times are estimated by Wolfram Mathematica and Crystal Ball statistical tools. Based on evaluation of packet interarrival times, we show how the gamma distribution can be used in network simulations and in evaluation of available capacity in opportunistic systems. As a result, from our analyses, shape and scale parameters of gamma distribution are generated. Data can be applied also in dynamic network configuration in order to avoid potential network congestions or overflows. Copyright

Investigation of priority queue with peaked traffic flows

In this paper1, a new single-server priority queueing system with a peaked arrival process and generally distributed service time is analysed by using the Polya distribution to describe the peaked traffic flows. The mean waiting time in the case of infinite number of waiting places is obtained using a generalized Pollaczek-Khinchin formula. It is shown that the performance of such delay systems varies vastly depending on the peakedness of the input flow. To the best of our knowledge, such a priority queueing system with a peaked arrival process is analysed for the first time.

Packet-Level Link Capacity Evaluation for IP Networks

Abstract In recent times, with many applications, the IP networks have become the most powerful tool for sharing information. Best-effort IP interconnected networks deliver data according to the available resources, without any assurance of throughput, delay bounds, or reliability requirements. As a result, their performance is highly variable and cannot be guaranteed. In IP networks, ensuring proper link capacity at the packet level is a challenging problem. In this article, a method to evaluate the link capacity of IP networks at the packet level based on a single server delay system with state-dependent arrival and departure processes is suggested. The dependence of the traffic being carried on the queue length and on the defined waiting time is shown. Presented graphic dependencies allow for defined quality of service, namely the probability of packet loss and admissible delays, to determine the carried traffic of the links.