280 research outputs found
An Erlang multirate loss model supporting elastic traffic under the threshold policy
In this paper, we propose a multirate teletraffic loss model of a single link with certain bandwidth capacity that accommodates Poisson arriving calls, which can tolerate bandwidth compression (elastic traffic), under the threshold policy. When compression occurs, the service time of new and in-service calls increases. The threshold policy provides different QoS among service-classes by limiting the number of calls of a service-class up to a pre-defined threshold, which can be different for each service-class. Due to the bandwidth compression mechanism, the steady state probabilities in the proposed model do not have a product form solution. However, we approximate the model by a reversible Markov chain, and prove recursive formulas for the calculation of call blocking probabilities and link utilization. The accuracy of the proposed formulas is verified through simulation and found to be very satisfactory
A Taxonomy of Communications Demand
Demand forecasts are an essential tool for planning capacity and
formulating policy. Traffic estimates are becoming increasingly
unreliable, however, as accelerating rates of use and new
communications applications invalidate conventional forecasting
assumptions.
This paper presents an alternative approach to the study of
telecommunications demand: build aggregate estimates for demand
based on the elasticity of demand for bandwidth.
We argue that price elasticity models are necessary to grasp the
interaction between Moore-type technological progress and non-linear
demand functions.
Traditional marketing models are premised on existing or, at best,
foreseeable services. But in a period of sustained price declines,
applications-based forecasts will be unreliable. Dramatically lower
prices can cause fundamental changes in the mix of applications and,
hence, the nature of demand.
We consider the option of posing demand theoretically in terms of
service attributes. Our conclusion is that the positive feedback loop of
technology-driven price decreases and high-elasticity demand will
quickly make it possible to base forecasts on bandwidth elasticity
alone.
Industry analysts and policymakers need models of consumer demand
applicable under dynamic conditions. We conclude by drawing
implications of our demand model for network planning, universal
service policies, and the commoditization of communications carriage
Dynamic bandwidth allocation in multi-class IP networks using utility functions.
PhDAbstact not availableFujitsu Telecommunications Europe Lt
Methods of Congestion Control for Adaptive Continuous Media
Since the first exchange of data between machines in different locations in early 1960s,
computer networks have grown exponentially with millions of people now using the
Internet. With this, there has also been a rapid increase in different kinds of services offered
over the World Wide Web from simple e-mails to streaming video. It is generally accepted
that the commonly used protocol suite TCP/IP alone is not adequate for a number of
modern applications with high bandwidth and minimal delay requirements. Many
technologies are emerging such as IPv6, Diffserv, Intserv etc, which aim to replace the onesize-fits-all approach of the current lPv4. There is a consensus that the networks will have
to be capable of multi-service and will have to isolate different classes of traffic through
bandwidth partitioning such that, for example, low priority best-effort traffic does not cause
delay for high priority video traffic. However, this research identifies that even within a
class there may be delays or losses due to congestion and the problem will require different
solutions in different classes.
The focus of this research is on the requirements of the adaptive continuous media
class. These are traffic flows that require a good Quality of Service but are also able to
adapt to the network conditions by accepting some degradation in quality. It is potentially
the most flexible traffic class and therefore, one of the most useful types for an increasing
number of applications.
This thesis discusses the QoS requirements of adaptive continuous media and
identifies an ideal feedback based control system that would be suitable for this class. A
number of current methods of congestion control have been investigated and two methods
that have been shown to be successful with data traffic have been evaluated to ascertain if
they could be adapted for adaptive continuous media. A novel method of control based on
percentile monitoring of the queue occupancy is then proposed and developed. Simulation
results demonstrate that the percentile monitoring based method is more appropriate to this
type of flow. The problem of congestion control at aggregating nodes of the network
hierarchy, where thousands of adaptive flows may be aggregated to a single flow, is then
considered. A unique method of pricing mean and variance is developed such that each
individual flow is charged fairly for its contribution to the congestion
Traffic engineering in dynamic optical networks
Traffic Engineering (TE) refers to all the techniques a Service Provider employs to improve the efficiency and reliability of network operations. In IP over Optical (IPO) networks, traffic coming from upper layers is carried over the logical topology defined by the set of established lightpaths. Within this framework then, TE techniques allow to optimize the configuration of optical resources with respect to an highly dynamic traffic demand. TE can be performed with two main methods: if the demand is known only in terms of an aggregated traffic matrix, the problem of automatically updating the configuration of an optical network to accommodate traffic changes is called Virtual Topology Reconfiguration (VTR). If instead the traffic demand is known in terms of data-level connection requests with sub-wavelength granularity, arriving dynamically from some source node to any destination node, the problem is called Dynamic Traffic Grooming (DTG). In this dissertation new VTR algorithms for load balancing in optical networks based on Local Search (LS) techniques are presented. The main advantage of using LS is the minimization of network disruption, since the reconfiguration involves only a small part of the network. A comparison between the proposed schemes and the optimal solutions found via an ILP solver shows calculation time savings for comparable results of network congestion. A similar load balancing technique has been applied to alleviate congestion in an MPLS network, based on the efficient rerouting of Label-Switched Paths (LSP) from the most congested links to allow a better usage of network resources. Many algorithms have been developed to deal with DTG in IPO networks, where most of the attention is focused on optimizing the physical resources utilization by considering specific constraints on the optical node architecture, while very few attention has been put so far on the Quality of Service (QoS) guarantees for the carried traffic. In this thesis a novel Traffic Engineering scheme is proposed to guarantee QoS from both the viewpoint of service differentiation and transmission quality. Another contribution in this thesis is a formal framework for the definition of dynamic grooming policies in IPO networks. The framework is then specialized for an overlay architecture, where the control plane of the IP and optical level are separated, and no information is shared between the two. A family of grooming policies based on constraints on the number of hops and on the bandwidth sharing degree at the IP level is defined, and its performance analyzed in both regular and irregular topologies. While most of the literature on DTG problem implicitly considers the grooming of low-speed connections onto optical channels using a TDM approach, the proposed grooming policies are evaluated here by considering a realistic traffic model which consider a Dynamic Statistical Multiplexing (DSM) approach, i.e. a single wavelength channel is shared between multiple IP elastic traffic flows
Stochastic Dynamic Programming and Stochastic Fluid-Flow Models in the Design and Analysis of Web-Server Farms
A Web-server farm is a specialized facility designed specifically for housing Web
servers catering to one or more Internet facing Web sites. In this dissertation, stochastic
dynamic programming technique is used to obtain the optimal admission control
policy with different classes of customers, and stochastic
uid-
ow models
are used to compute the performance measures in the network. The two types of
network traffic considered in this research are streaming (guaranteed bandwidth per
connection) and elastic (shares available bandwidth equally among connections).
We first obtain the optimal admission control policy using stochastic dynamic
programming, in which, based on the number of requests of each type being served,
a decision is made whether to allow or deny service to an incoming request. In
this subproblem, we consider a xed bandwidth capacity server, which allocates the
requested bandwidth to the streaming requests and divides all of the remaining bandwidth
equally among all of the elastic requests. The performance metric of interest in
this case will be the blocking probability of streaming traffic, which will be computed
in order to be able to provide Quality of Service (QoS) guarantees.
Next, we obtain bounds on the expected waiting time in the system for elastic
requests that enter the system. This will be done at the server level in such a way
that the total available bandwidth for the requests is constant. Trace data will be
converted to an ON-OFF source and
fluid-
flow models will be used for this analysis. The results are compared with both the mean waiting time obtained by simulating
real data, and the expected waiting time obtained using traditional queueing models.
Finally, we consider the network of servers and routers within the Web farm where
data from servers
flows and merges before getting transmitted to the requesting users
via the Internet. We compute the waiting time of the elastic requests at intermediate
and edge nodes by obtaining the distribution of the out
ow of the upstream node.
This out
ow distribution is obtained by using a methodology based on minimizing the
deviations from the constituent in
flows. This analysis also helps us to compute waiting
times at different bandwidth capacities, and hence obtain a suitable bandwidth to
promise or satisfy the QoS guarantees.
This research helps in obtaining performance measures for different traffic classes
at a Web-server farm so as to be able to promise or provide QoS guarantees; while at
the same time helping in utilizing the resources of the server farms efficiently, thereby
reducing the operational costs and increasing energy savings
Quality-of-service management in IP networks
Quality of Service (QoS) in Internet Protocol (IF) Networks has been the subject of
active research over the past two decades. Integrated Services (IntServ) and
Differentiated Services (DiffServ) QoS architectures have emerged as proposed
standards for resource allocation in IF Networks. These two QoS architectures
support the need for multiple traffic queuing systems to allow for resource
partitioning for heterogeneous applications making use of the networks. There have
been a number of specifications or proposals for the number of traffic queuing
classes (Class of Service (CoS)) that will support integrated services in IF Networks,
but none has provided verification in the form of analytical or empirical investigation
to prove that its specification or proposal will be optimum.
Despite the existence of the two standard QoS architectures and the large volume of
research work that has been carried out on IF QoS, its deployment still remains
elusive in the Internet. This is not unconnected with the complexities associated with
some aspects of the standard QoS architectures. [Continues.
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