Call blocking probabilities for Poisson traffic under the Multiple Fractional Channel Reservation policy

In this paper, we study the performance of the Multiple Fractional Channel Reservation (MFCR) policy, which is a bandwidth reservation policy that allows the reservation of real (not integer) number of channels in order to favor calls of high channel (bandwidth) requirements. We consider a link of fixed capacity that accommodates Poisson arriving calls of different service-classes with different bandwidth-per-call requirements. Calls compete for the available bandwidth under the MFCR policy. To determine call blocking probabilities, we propose approximate but recursive formulas based on the notion of reserve transition rates. The accuracy of the proposed method is verified through simulation

Simulation and analysis of adaptive routing and flow control in wide area communication networks

This thesis presents the development of new simulation and analytic models for the performance analysis of wide area communication networks. The models are used to analyse adaptive routing and flow control in fully connected circuit switched and sparsely connected packet switched networks. In particular the performance of routing algorithms derived from the L(_R-I) linear learning automata model are assessed for both types of network. A novel architecture using the INMOS Transputer is constructed for simulation of both circuit and packet switched networks in a loosely coupled multi- microprocessor environment. The network topology is mapped onto an identically configured array of processing centres to overcome the processing bottleneck of conventional Von Neumann architecture machines. Previous analytic work in circuit switched work is extended to include both asymmetrical networks and adaptive routing policies. In the analysis of packet switched networks analytic models of adaptive routing and flow control are integrated to produce a powerful, integrated environment for performance analysis The work concludes that routing algorithms based on linear learning automata have significant potential in both fully connected circuit switched networks and sparsely connected packet switched networks

STOCHASTIC MODELING AND TIME-TO-EVENT ANALYSIS OF VOIP TRAFFIC

Voice over IP (VoIP) systems are gaining increased popularity due to the cost effectiveness, ease of management, and enhanced features and capabilities. Both enterprises and carriers are deploying VoIP systems to replace their TDM-based legacy voice networks. However, the lack of engineering models for VoIP systems has been realized by many researchers, especially for large-scale networks. The purpose of traffic engineering is to minimize call blocking probability and maximize resource utilization. The current traffic engineering models are inherited from the legacy PSTN world, and these models fall short from capturing the characteristics of new traffic patterns. The objective of this research is to develop a traffic engineering model for modern VoIP networks. We studied the traffic on a large-scale VoIP network and collected several billions of call information. Our analysis shows that the traditional traffic engineering approach based on the Poisson call arrival process and exponential holding time fails to capture the modern telecommunication systems accurately. We developed a new framework for modeling call arrivals as a non-homogeneous Poisson process, and we further enhanced the model by providing a Gaussian approximation for the cases of heavy traffic condition on large-scale networks. In the second phase of the research, we followed a new time-to-event survival analysis approach to model call holding time as a generalized gamma distribution and we introduced a Call Cease Rate function to model the call durations. The modeling and statistical work of the Call Arrival model and the Call Holding Time model is constructed, verified and validated using hundreds of millions of real call information collected from an operational VoIP carrier network. The traffic data is a mixture of residential, business, and wireless traffic. Therefore, our proposed models can be applied to any modern telecommunication system. We also conducted sensitivity analysis of model parameters and performed statistical tests on the robustness of the models’ assumptions. We implemented the models in a new simulation-based traffic engineering system called VoIP Traffic Engineering Simulator (VSIM). Advanced statistical and stochastic techniques were used in building VSIM system. The core of VSIM is a simulation system that consists of two different simulation engines: the NHPP parametric simulation engine and the non-parametric simulation engine. In addition, VSIM provides several subsystems for traffic data collection, processing, statistical modeling, model parameter estimation, graph generation, and traffic prediction. VSIM is capable of extracting traffic data from a live VoIP network, processing and storing the extracted information, and then feeding it into one of the simulation engines which in turn provides resource optimization and quality of service reports

Learning algorithms for the control of routing in integrated service communication networks

There is a high degree of uncertainty regarding the nature of traffic on future integrated service networks. This uncertainty motivates the use of adaptive resource allocation policies that can take advantage of the statistical fluctuations in the traffic demands. The adaptive control mechanisms must be 'lightweight', in terms of their overheads, and scale to potentially large networks with many traffic flows. Adaptive routing is one form of adaptive resource allocation, and this thesis considers the application of Stochastic Learning Automata (SLA) for distributed, lightweight adaptive routing in future integrated service communication networks. The thesis begins with a broad critical review of the use of Artificial Intelligence (AI) techniques applied to the control of communication networks. Detailed simulation models of integrated service networks are then constructed, and learning automata based routing is compared with traditional techniques on large scale networks. Learning automata are examined for the 'Quality-of-Service' (QoS) routing problem in realistic network topologies, where flows may be routed in the network subject to multiple QoS metrics, such as bandwidth and delay. It is found that learning automata based routing gives considerable blocking probability improvements over shortest path routing, despite only using local connectivity information and a simple probabilistic updating strategy. Furthermore, automata are considered for routing in more complex environments spanning issues such as multi-rate traffic, trunk reservation, routing over multiple domains, routing in high bandwidth-delay product networks and the use of learning automata as a background learning process. Automata are also examined for routing of both 'real-time' and 'non-real-time' traffics in an integrated traffic environment, where the non-real-time traffic has access to the bandwidth 'left over' by the real-time traffic. It is found that adopting learning automata for the routing of the real-time traffic may improve the performance to both real and non-real-time traffics under certain conditions. In addition, it is found that one set of learning automata may route both traffic types satisfactorily. Automata are considered for the routing of multicast connections in receiver-oriented, dynamic environments, where receivers may join and leave the multicast sessions dynamically. Automata are shown to be able to minimise the average delay or the total cost of the resulting trees using the appropriate feedback from the environment. Automata provide a distributed solution to the dynamic multicast problem, requiring purely local connectivity information and a simple updating strategy. Finally, automata are considered for the routing of multicast connections that require QoS guarantees, again in receiver-oriented dynamic environments. It is found that the distributed application of learning automata leads to considerably lower blocking probabilities than a shortest path tree approach, due to a combination of load balancing and minimum cost behaviour

Application of advanced on-board processing concepts to future satellite communications systems

An initial definition of on-board processing requirements for an advanced satellite communications system to service domestic markets in the 1990's is presented. An exemplar system architecture with both RF on-board switching and demodulation/remodulation baseband processing was used to identify important issues related to system implementation, cost, and technology development

An Adaptive Scheme for Admission Control in ATM Networks

This paper presents a real time front-end admission control scheme for ATM networks. A call management scheme which uses the burstiness associated with traffic sources in a heterogeneous ATM environment to effect dynamic assignment of bandwidth is presented. In the proposed scheme, call acceptance is based on an on-line evaluation of the upper bound on cell loss probability which is derived from the estimated distribution of the number of calls arriving. Using this scheme, the negotiated quality of service will be assured when there is no estimation error. The control mechanism is effective when the number of calls is large, and tolerates loose bandwidth enforcement and loose policing control. The proposed approach is very effective in the connection oriented transport of ATM networks where the decision to admit new traffic is based on thea priori knowledge of the state of the route taken by the traffic

On IP over WDM burst-switched long haul and metropolitan area networks

The IP over Wavelength Division Multiplexing (WDM) network is a natural evolution ushered in by the phenomenal advances in networking technologies and technical breakthroughs in optical communications, fueled by the increasing demand in the reduction of operation costs and the network management complexity. The unprecedented bandwidth provisioning capability and the multi-service supportability of the WDM technology, in synergy with the data-oriented internetworking mechanisms, facilitates a common shared infrastructure for the Next Generation Internet (NGJ). While NGI targets to perform packet processing directly on the optical transport layer, a smooth evolution is critical to success. Intense research has been conducted to design the new generation optical networks that retain the advantages of packet-oriented transport prototypes while rendering elastic network resource utilization and graded levels of service. This dissertation is focused on the control architecture, enabling technologies, and performance analysis of the WDM burst-switched long haul and Metropolitan Area Networks (MANs). Theoretical analysis and simulation results are reported to demonstrate the system performance and efficiency of proposed algorithms. A novel transmission mechanism, namely, the Forward Resource Reservation (ERR) mechanism, is proposed to reduce the end-to-end delay for an Optical Burst Switching (OBS)-based IP over WDM system. The ERR scheme adopts a Linear Predictive Filter and an aggressive reservation strategy for data burst length prediction and resource reservation, respectively, and is extended to facilitate Quality of Service (QoS) differentiation at network edges. The ERR scheme improves the real-time communication services for applications with time constraints without deleterious system costs. The aggressive strategy for channel holding time reservations is proposed. Specifically, two algorithms, the success probability-driven (SPD) and the bandwidth usage-driven (BUD) ones, are proposed for resource reservations in the FRRenabled scheme. These algorithms render explicit control on the latency reduction improvement and bandwidth usage efficiency, respectively, both of which are important figures of performance metrics. The optimization issue for the FRR-enabled system is studied based on two disciplines - addressing the static and dynamic models targeting different desired objectives (in terms of algorithm efficiency and system performance), and developing a \u27\u27crank back\u27\u27 based signaling mechanism to provide bandwidth usage efficiency. The proposed mechanisms enable the network nodes to make intelligent usage of the bandwidth resources. In addition, a new control architecture with enhanced address resolution protocol (E-ARP), burst-based transmission, and hop-based wavelength allocation is proposed for Ethernet-supported IP over WDM MANs. It is verified, via theoretical analysis and simulation results, that the E-ARP significantly reduces the call setup latency and the transmission requirements associated with the address probing procedures; the burst-based transport mechanism improves the network throughput and resource utilization; and the hop-based wavelength allocation algorithm provides bandwidth multiplexing with fairness and high scalability. The enhancement of the Ethernet services, in tandem with the innovative mechanisms in the WDM domain, facilitates a flexible and efficient integration, thus making the new generation optical MAN optimized for the scalable, survivable, and IP-dominated network at gigabit speed possible