Merlin: A Language for Provisioning Network Resources

This paper presents Merlin, a new framework for managing resources in software-defined networks. With Merlin, administrators express high-level policies using programs in a declarative language. The language includes logical predicates to identify sets of packets, regular expressions to encode forwarding paths, and arithmetic formulas to specify bandwidth constraints. The Merlin compiler uses a combination of advanced techniques to translate these policies into code that can be executed on network elements including a constraint solver that allocates bandwidth using parameterizable heuristics. To facilitate dynamic adaptation, Merlin provides mechanisms for delegating control of sub-policies and for verifying that modifications made to sub-policies do not violate global constraints. Experiments demonstrate the expressiveness and scalability of Merlin on real-world topologies and applications. Overall, Merlin simplifies network administration by providing high-level abstractions for specifying network policies and scalable infrastructure for enforcing them

Optimized usage of network resources based on context information

Today an efficient (cost-effective) design and usage of networks is of particular importance. As more and more computer systems become context-aware the question of how context information can be used to improve computer networks arises. In this poster we describe how context information can be used to optimize the usage of resources in a computer network. By means of a mobile payment system we show how these optimization method can be applied

A critical comparison of approaches to resource name management within the IEC common information model

Copyright @ 2012 IEEEElectricity network resources are frequently identified within different power systems by inhomogeneous names and identities due to the legacy of their administration by different utility business domains. The IEC 61970 Common Information Model (CIM) enables network modeling to reflect the reality of multiple names for unique network resources. However this issue presents a serious challenge to the integrity of a shared CIM repository that has the task of maintaining a resource manifest, linking network resources to master identities, when unique network resources may have multiple names and identities derived from different power system models and other power system applications. The current approach, using CIM 15, is to manage multiple resource names within a singular CIM namespace utilizing the CIM “IdentifiedObject” and “Name” classes. We compare this approach to one using additional namespaces relating to different power systems, similar to the practice used in CIM extensions, in order to more clearly identify the genealogy of a network resource, provide faster model import times and a simpler means of supporting the relationship between multiple resource names and identities and a master resource identity.This study is supported by the UK National Grid and Brunel University

Indigenous Science Network Resources

A set of Australian and global resources to support the teaching of Indigenous perspectives in Science

Pricing Congestible Network Resources

We describe the basic economic theory of pricing a congestible resource such as an ftp server, a router, a Web site, etc. In particular, we examine the implications of "congestion pricing" as a way to encourage efficient use of network resources. We explore the implications of flat pricing and congestion pricing for capacity expansion in centrally planned, competitive, and monopolistic environments.Center for Research on Economic and Social Theory, Department of Economics, University of Michiganhttp://deepblue.lib.umich.edu/bitstream/2027.42/100874/1/ECON327.pd

Network Resources for Astronomers

The amount of data produced by large observational facilities and space missions has led to the archiving and on-line accessibility of much of this data, available to the entire astronomical community. This allows a much wider multi-frequency approach to astronomical research than previously possible. Here we provide an overview of these services, and give a basic description of their contents and possibilities for accessing them. Apart from services providing observational data, many of those providing general information, e.g. on addresses, bibliographies, software etc. are also described. The field is rapidly growing with improved network technology, and our attempt to keep the report as complete and up-to-date as possible will inevitably be outdated shortly. We will endeavor to maintain an updated version of this document on-line.Comment: 53 pages; uuencoded compressed PostScript; includes one table, no figures; Lyon-41 (Aug'94) and ESO-1033 (Sept'94), to appear in PASP, November 1994 issu

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

Online Resource Inference in Network Utility Maximization Problems

The amount of transmitted data in computer networks is expected to grow considerably in the future, putting more and more pressure on the network infrastructures. In order to guarantee a good service, it then becomes fundamental to use the network resources efficiently. Network Utility Maximization (NUM) provides a framework to optimize the rate allocation when network resources are limited. Unfortunately, in the scenario where the amount of available resources is not known a priori, classical NUM solving methods do not offer a viable solution. To overcome this limitation we design an overlay rate allocation scheme that attempts to infer the actual amount of available network resources while coordinating the users rate allocation. Due to the general and complex model assumed for the congestion measurements, a passive learning of the available resources would not lead to satisfying performance. The coordination scheme must then perform active learning in order to speed up the resources estimation and quickly increase the system performance. By adopting an optimal learning formulation we are able to balance the tradeoff between an accurate estimation, and an effective resources exploitation in order to maximize the long term quality of the service delivered to the users