Title
Evaluating network information models on resource efficiency and application performance in lambda-grids
Abstract
A critical challenge for wide-area configurable networks is definition and widespread acceptance of Network Information Model (NIM). When a network comprises multiple domains, intelligent information sharing is required for a provider to maintain a competitive advantage and for customers to use a provider's network and make good resource selection decisions. We characterize the information that can be shared between domains and propose a spectrum of network information models. To evaluate the impact of the proposed models, we use a trace-driven simulation under a range of real providers' networks and assess how the available information affects applications' and providers' ability to utilize network resources. We find that domain topology information is crucial for achieving good resource efficiency, low application latency and network configuration cost, while domain link state information contributes to better resource utilization and system throughput. These results suggest that collaboration between service providers can provide better overall network productivity.
Year
DOI
Venue
2007
10.1145/1362622.1362632
SC
Keywords
Field
DocType
intelligent information sharing,domain topology information,available information,overall network productivity,application performance,network resource,domain link state information,network configuration cost,wide-area configurable network,better resource utilization,network information model,resource efficiency,throughput,topology,competitive advantage,productivity,wavelength division multiplexing,motion pictures,network topology,servers,computer science,resource utilization,application software,collaboration,spectrum,information model,computer networks,service provider
Organizational network analysis,Computer science,Parallel computing,Computer network,Network simulation,Network topology,Service provider,Information model,Information sharing,Network management station,Intelligent computer network,Distributed computing
Conference
Citations 
PageRank 
References 
4
0.53
23
Authors
2
Name
Order
Citations
PageRank
Nut Taesombut1433.60
Andrew A. Chien23696405.97