Implementation of Internet Protocol Network Architecture for Effective bandwidth Allocation in a Multiparty, Multimedia Conferencing

Advances in multimedia technologies and development of overlay networks foster the opportunity for creating new value-added services over the current Internet. In this paper, a new service network architecture that supports multiparty multimedia conferencing applications, characteristics of which include multi-channel, high bandwidth and low delay tolerance has been proposed. The new service network architecture is built on an array of service nodes called Multiparty Processing Centers (MPCs) which constitute a service overlay network, serving as the infrastructure for multiparty conferencing, and are responsible for conferencing setup, media delivery and the provision of Quality of Service. In this paper, the main focus is on the bandwidth allocation management over the proposed service network. The analysis will determine the bandwidth demand for virtual links among the MPCs. Multimedia traffic is modeled as M/G/∞ input processes and divided into several classes, with the constraint that the aggregate effective bandwidth is within the link capacity times a prescribed utilization threshold

Effective Capacity Analysis for Cognitive Networks under QoS Satisfaction

Spectrum sensing and dynamic spectrum access (DSA) techniques in cognitive radio networks (CRN) have been extensively investigated since last decade. Recently, satisfaction of quality-of-service (QoS) demands for secondary users (SU) has attracted great attention. The SU can not only discover the transmission opportunities, but also cognitively adapts the dynamic spectrum access strategies to its own QoS requirement and the environment variations. In this paper, we study how the delay QoS requirement affects the strategy on network performance. We first treat the delay-QoS in interference constrained cognitive radio network by applying the effective capacity concept, focusing on the two dominant DSA schemes: underlay and overlay. We obtain the effective capacity of the secondary network and determine the power allocation policies that maximize the throughput of the cognitive user. The underlay and overlay approaches may have their respective advantages under diverse propagation environment and system parameters. If the cognitive network can dynamically choose the DSA strategy under different environment, its performance could be further improved. We propose a selection criterion to determine whether to use underlay or overlay scheme under the given QoS constraint and the PUs’ spectrum-occupancy probability. Thus, the throughput of the CRN could be increased. Performance analysis and numerical evaluations are provided to demonstrate the effective capacity of CRN based on the underlay and the overlay schemes, taking into consideration the impact of delay QoS requirement and other related parameters

A note on the data-driven capacity of P2P networks

We consider two capacity problems in P2P networks. In the first one, the nodes have an infinite amount of data to send and the goal is to optimally allocate their uplink bandwidths such that the demands of every peer in terms of receiving data rate are met. We solve this problem through a mapping from a node-weighted graph featuring two labels per node to a max flow problem on an edge-weighted bipartite graph. In the second problem under consideration, the resource allocation is driven by the availability of the data resource that the peers are interested in sharing. That is a node cannot allocate its uplink resources unless it has data to transmit first. The problem of uplink bandwidth allocation is then equivalent to constructing a set of directed trees in the overlay such that the number of nodes receiving the data is maximized while the uplink capacities of the peers are not exceeded. We show that the problem is NP-complete, and provide a linear programming decomposition decoupling it into a master problem and multiple slave subproblems that can be resolved in polynomial time. We also design a heuristic algorithm in order to compute a suboptimal solution in a reasonable time. This algorithm requires only a local knowledge from nodes, so it should support distributed implementations. We analyze both problems through a series of simulation experiments featuring different network sizes and network densities. On large networks, we compare our heuristic and its variants with a genetic algorithm and show that our heuristic computes the better resource allocation. On smaller networks, we contrast these performances to that of the exact algorithm and show that resource allocation fulfilling a large part of the peer can be found, even for hard configuration where no resources are in excess.Comment: 10 pages, technical report assisting a submissio

VINEA: a policy-based virtual network embedding architecture

Network virtualization has enabled new business models by allowing infrastructure providers to lease or share their physical network. To concurrently run multiple customized virtual network services, such infrastructure providers need to run a virtual network embedding protocol. The virtual network embedding is the (NP-hard) problem of matching constrained virtual networks onto the physical network. We present the design and implementation of a policy-based architecture for the virtual network embedding problem. By policy, we mean a variant aspect of any of the (invariant) embedding mechanisms: resource discovery, virtual network mapping, and allocation on the physical infrastructure. Our architecture adapts to different scenarios by instantiating appropriate policies, and has bounds on embedding efficiency and on convergence embedding time, over a single provider, or across multiple federated providers. The performance of representative novel policy configurations are compared over a prototype implementation. We also present an object model as a foundation for a protocol specification, and we release a testbed to enable users to test their own embedding policies, and to run applications within their virtual networks. The testbed uses a Linux system architecture to reserve virtual node and link capacities.National Science Foundation (CNS-0963974

Using Dedicated and Opportunistic Networks in Synergy for a Cost-effective Distributed Stream Processing Platform

This paper presents a case for exploiting the synergy of dedicated and opportunistic network resources in a distributed hosting platform for data stream processing applications. Our previous studies have demonstrated the benefits of combining dedicated reliable resources with opportunistic resources in case of high-throughput computing applications, where timely allocation of the processing units is the primary concern. Since distributed stream processing applications demand large volume of data transmission between the processing sites at a consistent rate, adequate control over the network resources is important here to assure a steady flow of processing. In this paper, we propose a system model for the hybrid hosting platform where stream processing servers installed at distributed sites are interconnected with a combination of dedicated links and public Internet. Decentralized algorithms have been developed for allocation of the two classes of network resources among the competing tasks with an objective towards higher task throughput and better utilization of expensive dedicated resources. Results from extensive simulation study show that with proper management, systems exploiting the synergy of dedicated and opportunistic resources yield considerably higher task throughput and thus, higher return on investment over the systems solely using expensive dedicated resources.Comment: 9 page