Network delay inference from additive metrics
نویسندگان
چکیده
منابع مشابه
Network Delay Inference from Additive Metrics
We demonstrate the use of computational phylogenetic techniques to solve a central problem in inferential network monitoring. More precisely, we design a novel algorithm for multicast-based delay inference, i.e. the problem of reconstructing the topology and delay characteristics of a network from end-to-end delay measurements on network paths. Our inference algorithm is based on additive metri...
متن کاملUnicast inference of network link delay distributions from edge measurements
Inference of network internal link characteristics has become an increasingly important issue for operating and evaluating large telecommunication networks. Since it is usually impractical to directly monitor each link along a specific path, end-to-end probes are sometimes used to collect link characteristic information at edge nodes of the network. This paper deals with unicast probing methods...
متن کاملUsing Additive Expression Programming for Gene Regulatory Network Inference
Gene regulatory networks depict the interactions among genes in the cell and construction of networks is important in uncovering the underlying biological process of living organisms. In this paper, a non-linear differential equation model is used for gene regulatory network reconstruction and time-series prediction. A new model, called additive expression tree (AET) model is proposed to encode...
متن کاملHybridNN: Supporting Network Location Service on Generalized Delay Metrics
Distributed Nearest Neighbor Search (DNNS) locates service nodes that have shortest interactive delay towards requesting hosts. DNNS provides an important service for largescale latency sensitive networked applications, such as VoIP, online network games, or interactive network services on the cloud. Existing work assumes the delay to be symmetric, which does not generalize to applications that...
متن کاملInference in a Gene Regulatory Network with Transcriptional Time Delay
Background: Ordinary differential equations (ODEs) are an important tool for describing the dynamics of biological systems. However, for ODE models to be useful, their parameters must first be calibrated. Parameter estimation, that is, finding parameter values given experimental data, is an inference problem that can be treated systematically through a Bayesian framework. A Markov chain Monte M...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Random Structures & Algorithms
سال: 2010
ISSN: 1042-9832
DOI: 10.1002/rsa.20305