The Role of Responsive Pricing in the Internet

The Internet continues to evolve as it reaches out to a wider user population. The recent introduction of user-friendly navigation and retrieval tools for the World Wide Web has triggered an unprecedented level of interest in the Internet among the media and the general public, as well as in the technical community. It seems inevitable that some changes or additions are needed in the control mechanisms used to allocate usage of Internet resources. In this paper, we argue that a feedback signal in the form of a variable price for network service is a workable tool to aid network operators in controlling Internet traffic. We suggest that these prices should vary dynamically based on the current utilization of network resources. We show how this responsive pricing puts control of network service back where it belongs: with the users.Internet, pricing, feedback, networks

Quality of Service Differentiation in Heterogeneous CDMA Networks : A Mathematical Modelling Approach

Next-generation cellular networks are expected to enable the coexistence of macro and small cells, and to support differentiated quality-of-service (QoS) of mobile applications. Under such conditions in the cell, due to a wide range of supported services and high dependencies on efficient vertical and horizontal handovers, appropriate management of handover traffic is very crucial. Furthermore, new emerging technologies, such as cloud radio access networks (C-RAN) and self-organizing networks (SON), provide good implementation and deployment opportunities for novel functions and services. We design a multi-threshold teletraffic model for heterogeneous code division multiple access (CDMA) networks that enable QoS differentiation of handover traffic when elastic and adaptive services are present. Facilitated by this model, it is possible to calculate important performance metrics for handover and new calls, such as call blocking probabilities, throughput, and radio resource utilization. This can be achieved by modelling the cellular CDMA system as a continuous-time Markov chain. After that, the determination of state probabilities in the cellular system can be performed via a recursive and efficient formula. We present the applicability framework for our proposed approach, that takes into account advances in C-RAN and SON technologies. We also evaluate the accuracy of our model using simulations and find it very satisfactory. Furthermore, experiments on commodity hardware show algorithm running times in the order of few hundreds of milliseconds, which makes it highly applicable for accurate cellular network dimensioning and radio resource management

Congestion probabilities in CDMA-based networks supporting batched Poisson traffic

We propose a new multirate teletraffic loss model for the calculation of time and call congestion probabilities in CDMA-based networks that accommodate calls of different serviceclasses whose arrival follows a batched Poisson process. The latter is more "peaked" and "bursty" than the ordinary Poisson process. The acceptance of calls in the system is based on the partial batch blocking discipline. This policy accepts a part of the batch (one or more calls) and discards the rest if the available resources are not enough to accept the whole batch. The proposed model takes into account the multiple access interference, the notion of local (soft) blocking, user’s activity and the interference cancellation. Although the analysis of the model does not lead to a product form solution of the steady state probabilities, we show that the calculation of the call-level performance metrics, time and call congestion probabilities, can be based on approximate but recursive formulas. The accuracy of the proposed formulas are verified through simulation and found to be quite satisfactory

Dynamic bandwidth allocation in multi-class IP networks using utility functions.

PhDAbstact not availableFujitsu Telecommunications Europe Lt

Methods of Congestion Control for Adaptive Continuous Media

Since the first exchange of data between machines in different locations in early 1960s, computer networks have grown exponentially with millions of people now using the Internet. With this, there has also been a rapid increase in different kinds of services offered over the World Wide Web from simple e-mails to streaming video. It is generally accepted that the commonly used protocol suite TCP/IP alone is not adequate for a number of modern applications with high bandwidth and minimal delay requirements. Many technologies are emerging such as IPv6, Diffserv, Intserv etc, which aim to replace the onesize-fits-all approach of the current lPv4. There is a consensus that the networks will have to be capable of multi-service and will have to isolate different classes of traffic through bandwidth partitioning such that, for example, low priority best-effort traffic does not cause delay for high priority video traffic. However, this research identifies that even within a class there may be delays or losses due to congestion and the problem will require different solutions in different classes. The focus of this research is on the requirements of the adaptive continuous media class. These are traffic flows that require a good Quality of Service but are also able to adapt to the network conditions by accepting some degradation in quality. It is potentially the most flexible traffic class and therefore, one of the most useful types for an increasing number of applications. This thesis discusses the QoS requirements of adaptive continuous media and identifies an ideal feedback based control system that would be suitable for this class. A number of current methods of congestion control have been investigated and two methods that have been shown to be successful with data traffic have been evaluated to ascertain if they could be adapted for adaptive continuous media. A novel method of control based on percentile monitoring of the queue occupancy is then proposed and developed. Simulation results demonstrate that the percentile monitoring based method is more appropriate to this type of flow. The problem of congestion control at aggregating nodes of the network hierarchy, where thousands of adaptive flows may be aggregated to a single flow, is then considered. A unique method of pricing mean and variance is developed such that each individual flow is charged fairly for its contribution to the congestion

An Overview on Application of Machine Learning Techniques in Optical Networks

Today's telecommunication networks have become sources of enormous amounts of widely heterogeneous data. This information can be retrieved from network traffic traces, network alarms, signal quality indicators, users' behavioral data, etc. Advanced mathematical tools are required to extract meaningful information from these data and take decisions pertaining to the proper functioning of the networks from the network-generated data. Among these mathematical tools, Machine Learning (ML) is regarded as one of the most promising methodological approaches to perform network-data analysis and enable automated network self-configuration and fault management. The adoption of ML techniques in the field of optical communication networks is motivated by the unprecedented growth of network complexity faced by optical networks in the last few years. Such complexity increase is due to the introduction of a huge number of adjustable and interdependent system parameters (e.g., routing configurations, modulation format, symbol rate, coding schemes, etc.) that are enabled by the usage of coherent transmission/reception technologies, advanced digital signal processing and compensation of nonlinear effects in optical fiber propagation. In this paper we provide an overview of the application of ML to optical communications and networking. We classify and survey relevant literature dealing with the topic, and we also provide an introductory tutorial on ML for researchers and practitioners interested in this field. Although a good number of research papers have recently appeared, the application of ML to optical networks is still in its infancy: to stimulate further work in this area, we conclude the paper proposing new possible research directions

Performance analysis of CDMA-based networks with interference cancellation, for batched poisson traffic under the Bandwidth Reservation policy

CDMA-based technologies deserve assiduous analysis and evaluation. We study the performance, at call-level, of a CDMA cell with interference cancellation capabilities, while assuming that the cell accommodates different service-classes of batched Poisson arriving calls. The partial batch blocking discipline is applied for Call Admission Control (CAC). To guarantee certain Quality of Service (QoS) for each service-class, the Bandwidth Reservation (BR) policy is incorporated in the CAC; i.e., a fraction of system resources is reserved for high-speed service-classes. We propose a new multirate loss model for the calculation of time and call congestion probabilities. The notion of local (soft) and hard blocking, users activity, interference cancellation, as well as the BR policy, are incorporated in the model. Although the steady state probabilities of the system do not have a product form solution, time and call congestion probabilities can be efficiently determined via approximate but recursive formulas. Simulation verified the high accuracy of the new formulas. We also show the consistency of the proposed model in respect of its parameters, while comparison of the proposed model with that of Poisson input shows its necessity

An Approach to Model Resources Rationalisation in Hybrid Clouds through Users Activity Characterisation

In recent years, some strategies (e.g., server consolidation by means of virtualisation techniques) helped the managers of large Information Technology (IT) infrastructures to limit, when possible, the use of hardware resources in order to provide reliable services and to reduce the Total Cost of Ownership (TCO) of such infrastructures. Moreover, with the advent of Cloud computing, a resource usage rationalisation can be pursued also for the users applications, if this is compatible with the Quality of Service (QoS) which must be guaranteed. In this perspective, modern datacenters are “elastic”, i.e., able to shrink or enlarge the number of local physical or virtual resources from private/public Clouds. Moreover, many of large computing environments are integrated in distributed computing environment as the grid and cloud infrastructures. In this document, we report some advances in the realisation of a utility, we named Adaptive Scheduling Controller (ASC) which, interacting with the datacenter resource manager, allows an effective and efficient usage of resources, also by means of users jobs classification. Here, we focus both on some data mining algorithms which allows to classify the users activity and on the mathematical formalisation of the functional used by ASC to find the most suitable configuration for the datacenter’s resource manager. The presented case study concerns the SCoPE infrastructure, which has a twofold role: local computing resources provider for the University of Naples Federico II and remote resources provider for both the Italian Grid Infrastructure (IGI) and the European Grid Infrastructure (EGI) Federated Cloud

State-Dependent Bandwidth Sharing Policies for Wireless Multirate Loss Networks

We consider a reference cell of fixed capacity in a wireless cellular network while concentrating on next-generation network architectures. The cell accommodates new and handover calls from different service-classes. Arriving calls follow a random or quasi-random process and compete for service in the cell under two bandwidth sharing policies: 1) a probabilistic threshold (PrTH) policy or 2) the multiple fractional channel reservation (MFCR) policy. In the PrTH policy, if the number of in-service calls (new or handover) of a service-class exceeds a threshold (difference between new and handover calls), then an arriving call of the same service-class is accepted in the cell with a predefined state-dependent probability. In the MFCR policy, a real number of channels is reserved to benefit calls of certain service-classes; thus, a service priority is introduced. The cell is modeled as a multirate loss system. Under the PrTH policy, call-level performance measures are determined via accurate convolution algorithms, while under the MFCR policy, via approximate but efficient models. Furthermore, we discuss the applicability of the proposed models in 4G/5G networks. The accuracy of the proposed models is verified through simulation. Comparison against other models reveals the necessity of the new models and policies