Analysis of Radio Spectrum Market Evolution Possibilities

A tremendous growth in wireless traffic volumes and a shortage of feasible radio spectrum has led to a situation where the old and rigid spectrum regime is not a viable option for spectrum management and a shift towards a more market driven approach has begun. Great uncertainty still exists over how such a radio spectrum market will come about and what kind of shape it would take. This paper studies some long term macro level evolution possibilities for how this radio spectrum market could emerge and what would be the corresponding value chain configurations. The scenario planning and system dynamics methods are utilized to build four alternative future spectrum market scenarios.Spectrum Markets, Spectrum Policy, Flexible Spectrum Usage, Cognitive Radio, Value Networks, Scenario Planning, System Dynamics.

Enhancing QoS provisioning and granularity in next generation internet

Next Generation IP technology has the potential to prevail, both in the access and in the core networks, as we are moving towards a multi-service, multimedia and high-speed networking environment. Many new applications, including the multimedia applications, have been developed and deployed, and demand Quality of Service (QoS) support from the Internet, in addition to the current best effort service. Therefore, QoS provisioning techniques in the Internet to guarantee some specific QoS parameters are more a requirement than a desire. Due to the large amount of data flows and bandwidth demand, as well as the various QoS requirements, scalability and fine granularity in QoS provisioning are required. In this dissertation, the end-to-end QoS provisioning mechanisms are mainly studied, in order to provide scalable services with fine granularity to the users, so that both users and network service providers can achieve more benefits from the QoS provisioned in the network. To provide the end-to-end QoS guarantee, single-node QoS provisioning schemes have to be deployed at each router, and therefore, in this dissertation, such schemes are studied prior to the study of the end-to-end QoS provisioning mechanisms. Specifically, the effective sharing of the output bandwidth among the large amount of data flows is studied, so that fairness in the bandwidth allocation among the flows can be achieved in a scalable fashion. A dual-rate grouping architecture is proposed in this dissertation, in which the granularity in rate allocation can be enhanced, while the scalability of the one-rate grouping architecture is still maintained. It is demonstrated that the dual-rate grouping architecture approximates the ideal per-flow based PFQ architecture better than the one-rate grouping architecture, and provides better immunity capability. On the end-to-end QoS provisioning, a new Endpoint Admission Control scheme for Diffserv networks, referred to as Explicit Endpoint Admission Control (EEAC), is proposed, in which the admission control decision is made by the end hosts based on the end-to-end performance of the network. A novel concept, namely the service vector, is introduced, by which an end host can choose different services at different routers along its data path. Thus, the proposed service provisioning paradigm decouples the end-to-end QoS provisioning from the service provisioning at each router, and the end-to-end QoS granularity in the Diffserv networks can be enhanced, while the implementation complexity of the Diffserv model is maintained. Furthermore, several aspects of the implementation of the EEAC and service vector paradigm, referred to as EEAC-SV, in the Diffserv architecture are also investigated. The performance analysis and simulation results demonstrate that the proposed EEAC-SV scheme, not only increases the benefit to the service users, but also enhances the benefit to the network service provider in terms of network resource utilization. The study also indicates that the proposed EEAC-SV scheme can provide a compatible and friendly networking environment to the conventional TCP flows, and the scheme can be deployed in the current Internet in an incremental and gradual fashion

An Intelligent Model To Control Preemption Rate Of Instantaneous Request Calls In Networks With Book-Ahead Reservation

Resource sharing between book-ahead (BA) and instantaneous request (IR) reservation often results in high preemption rate of on-going IR calls. High IR call preemption rate causes interruption to service continuity which is considered as detrimental in a QoS-enabled network. A number of call admission control models have been proposed in literature to reduce the preemption rate of on-going IR calls. Many of these models use a tuning parameter to achieve certain level of preemption rate. This paper presents an artificial neural network (ANN) model to dynamically control the preemption rate of on-going calls in a QoS-enabled network. The model maps network traffic parameters and desired level of preemption rate into appropriate tuning parameter. Once trained, this model can be used to automatically estimate the tuning parameter value necessary to achieve the desired level of preemption rate. Simulation results show that the preemption rate attained by the model closely matches with the target rate

Economy-based data replication broker

Data replication is one of the key components in data grid architecture as it enhances data access and reliability and minimises the cost of data transmission. In this paper, we address the problem of reducing the overheads of the replication mechanisms that drive the data management components of a data grid. We propose an approach that extends the resource broker with policies that factor in user quality of service as well as service costs when replicating and transferring data. A realistic model of the data grid was created to simulate and explore the performance of the proposed policy. The policy displayed an effective means of improving the performance of the grid network traffic and is indicated by the improvement of speed and cost of transfers by brokers.<br /