This paper looks at a markov chain based model and uses queuing theory to analyse its performance. The system is D-BMAP/D/1 and a closed form solution is found
Research about modelling aspects of networks.
This paper looks at the phenomenon of long-range dependence. It shows that certain long-range dependent models give answers which contain infinities and also that this behaviour will not be detected by a naive modelling approach. The work is an extension of an earlier published PMECT paper.
This paper looks at ways of predicting the TCP throughput of a connection. The assumption is that some information is available about the connection. A comparison is made between “formula based” (FB) prediction, that is using round-trip time and loss versus time series analysis prediction (referred to here as history based (HB)), that is using previous measurements on the same connection. Both approaches require some measurements from the connection already.
This paper deals with reducing costs for cloud computing users. Cloud customers use “Traffic Redundancy Elimination” (TRE) to reduce bandwidth costs. Redundant data chunks are detected and removed – cloud providers will not implement middleboxes for this as they have no incentive. The paper gives a TRE solution which does not require a server to maintain client status. The system is known as PACK “Predictive ACKnowledgements” which is receiver driven.
This paper looks at the issue of reducing variability in performance in data centre networks. Variable network performance can lead to unreliable application performance in networked applications – this can be a particular problem for cloud apps. Virtual networks are proposed as a solution to isolate the “tenant” performance from the physical network infrastructure. The system presented is known as Oktopus. The system provides a tradeoff between guarantees to tenants, costs to tenants and profits to providers by mapping a virtual network to the physical network.
This paper creates a simple mathematical model based on Markov chains which can model (with some simple assumptions) the type of cacheing trees seen in content centric networking. The model is tested with some simulation results.