The article presents the results of the analysis of the need for unification of tethered telecommunication high-altitude platforms (HAP). Possible ways of unification and standardization of HAP, as well as criteria and methods of their structural optimization are considered. It is shown that one of the methods for increasing the efficiency of telecommunication networks is the unification of requirements, component parts and their composite systems. The requirements that should be laid at the stage of setting a technical task for product development are given and it is shown that such parameters as the repeatability factor, the applicability factor, the inter-project unification coefficient are used to assess the level of unification. It is shown that to solve the problems of hardware-software unification and ensure information compatibility, it is necessary to develop appropriate models that take into account the specifics of modern information transmission systems in HAP. The rationale for using the apparatus of logical-dynamic models for solving unification problems is proved, and their joint use with network models allows to formalize the information necessary for solving the problems of hardware-software unification of HAP and ensuring their information compatibility.

We propose the new EI-clustering method for random networks. Regarding the underlying graph of a random network, EI-clustering is an advanced statistical tool for community detection and based on the estimation of the extremal index (EI) associated with each node. The EI metric is estimated by samples of indices of the node in uences. The latter quantities are determined by the PageRank and a Max-Linear Model. The EI values of both models are estimated by a blocks estimator for each node which is considered as the root of a Thorny Branching Tree. Generations of descendant nodes related to the root node of the tree are used as blocks. The reciprocal of the EI value indicates the average number of in uential nodes per generation containing at least one in uential node. In the context of random graphs the EI metric indicates the ability of a randomly selected node to attract highly ranked nodes in its orbit. Looking at the changing shape of a plot of the EI metric versus the node number, the node communities are detected. The EI-clustering method is compared with the conductance measure regarding the data set of a real Web graph.

Modern tools to measure Internet traffic such as Wireshark or Atheris offer complex opportunities to collect packet data from high speed networks. Advanced statistical methods are required to support an adequate teletraffic analysis of these traces and the evaluation of relevant performance indices, for instance, of captured packet flows stemming from new multimedia services in Internet. They allow us to cope with immanent dependencies and underlying heavy-tailed distributions of interesting features of the traffic such as the bitrates, volumes or lengths of sessions, the inter-arrival times, loss rates and delay distributions of the packet streams or their equivalent bandwidth.  In the tutorial we shall discuss useful statistical techniques to handle the arising strongly correlated or long-range dependent time series and heavy-tailed marginal distributions. The latter features characterize the underlying random variables of the observed data. Advanced procedures to compute the demanded bandwidth of observed streams or the delay-loss profiles of packet flows during a session will be stated. The analysis concepts will be illustrated by real traces arising from some popular Internet applications.  The tutorial shall stimulate the participants to incorporate adaptations of the sketched statistical procedures into open source tools or their own codes according to their personal needs.

The paper deals with a multi-server controllable queueing system M(t)/M/K with time-dependent and, in particular, with periodic arrival rates. The models with homogeneous and heterogeneous servers are of interest. In latter case the fastest free server allocation mechanism is assumed and the preemption is allowed. The control problem consists in evaluation of the optimal number of servers during some specified stages and is solved by finite horizon dynamic programming approach. To calculate the transient solutions we use a forth-order Runge-Kutta method for the system with a truncated queue length. The results are compared with corresponding queues operating in a stationary regime. It is shown that the optimal control policies are also time dependent and periodic as arrival rates and heterogeneous systems are superior in performance comparing to the homogeneous ones.