Results 1  10
of
14
Perspectives on Network Calculus  No Free Lunch, but Still Good Value
, 2012
"... ACM Sigcomm 2006 published a paper [26] which was perceived to unify the deterministic and stochastic branches of the network calculus (abbreviated throughout as DNC and SNC) [39]. Unfortunately, this seemingly fundamental unification—which has raised the hope of a straightforward transfer of all re ..."
Abstract

Cited by 20 (11 self)
 Add to MetaCart
ACM Sigcomm 2006 published a paper [26] which was perceived to unify the deterministic and stochastic branches of the network calculus (abbreviated throughout as DNC and SNC) [39]. Unfortunately, this seemingly fundamental unification—which has raised the hope of a straightforward transfer of all results from DNC to SNC—is invalid. To substantiate this claim, we demonstrate that for the class of stationary andergodic processes, whichis prevalentin traffic modelling, the probabilistic arrival model from [26] is quasideterministic, i.e., the underlying probabilities are either zero or one. Thus, the probabilistic framework from [26] is unable to account for statistical multiplexing gain, which is in fact the raison d’être of packetswitched networks. Other previous formulations of SNC can capture statistical multiplexing
Delay bounds in communication networks with heavytailed and selfsimilar traffic
 IEEE Transactions on Information Theory
, 2012
"... Traffic with selfsimilar and heavytailed characteristics has been widely reported in communication networks, yet, the stateoftheart of analytically predicting the delay performance of such networks is lacking. We address a particularly difficult type of heavytailed traffic where only the first ..."
Abstract

Cited by 12 (3 self)
 Add to MetaCart
(Show Context)
Traffic with selfsimilar and heavytailed characteristics has been widely reported in communication networks, yet, the stateoftheart of analytically predicting the delay performance of such networks is lacking. We address a particularly difficult type of heavytailed traffic where only the first moment can be computed, and present nonasymptotic endtoend delay bounds for such traffic. The derived performance bounds are nonasymptotic in that they do not assume a steady state, large buffer, or many sources regime. The analysis follows a network calculus approach where traffic is characterized by envelope functions and service is described by service curves. Our analysis considers a multihop path of fixedcapacity links with heavytailed selfsimilar cross traffic at each node. A key contribution of the analysis is a novel probabilistic samplepath bound for heavytailed arrival and service processes, which is based on a scalefree sampling method. We explore how delays scale as a function of the length of the path, and compare them with lower bounds. A comparison with simulations illustrates pitfalls when simulating selfsimilar heavytailed traffic, providing further evidence for the need of analytical bounds. I.
Nonasymptotic Delay Bounds for Networks with HeavyTailed Traffic
, 2010
"... Traffic with selfsimilar and heavytailed characteristics has been widely reported in networks, yet, only few analytical results are available for predicting the delay performance of such networks. We address a particularly difficult type of heavytailed traffic where only the first moment can be ..."
Abstract

Cited by 6 (5 self)
 Add to MetaCart
(Show Context)
Traffic with selfsimilar and heavytailed characteristics has been widely reported in networks, yet, only few analytical results are available for predicting the delay performance of such networks. We address a particularly difficult type of heavytailed traffic where only the first moment can be computed, and present the first nonasymptotic endtoend delay bounds for such traffic. The derived performance bounds are nonasymptotic in that they do not assume a steady state, large buffer, or many sources regime. Our analysis considers a multihop path of fixedcapacity links with heavytailed selfsimilar cross traffic at each node. A key contribution of the analysis is a probabilistic samplepath bound for heavytailed arrival and service processes, which is based on a scalefree sampling method. We explore how delays scale as a function of the length of the path, and compare them with lower bounds. A comparison with simulations illustrates pitfalls when simulating selfsimilar heavytailed traffic, providing further evidence for the need of analytical bounds.
Delay Bounds for Networks with HeavyTailed and SelfSimilar Traffic
, 2009
"... We provide upper bounds on the endtoend backlog and delay in a network with heavytailed and selfsimilar traffic. The analysis follows a network calculus approach where traffic is characterized by envelope functions and service is described by service curves. A key contribution of this paper is t ..."
Abstract

Cited by 6 (3 self)
 Add to MetaCart
We provide upper bounds on the endtoend backlog and delay in a network with heavytailed and selfsimilar traffic. The analysis follows a network calculus approach where traffic is characterized by envelope functions and service is described by service curves. A key contribution of this paper is the derivation of a probabilistic sample path bound for heavytailed selfsimilar arrival processes, which is enabled by a suitable envelope characterization, referred to as htss envelope. We derive a heavytailed service curve for an entire network path when the service at each node on the path is characterized by heavytailed service curves. We obtain backlog and delay bounds for traffic that is characterized by an htss envelope and receives service given by a heavytailed service curve. The derived performance bounds are nonasymptotic in that they do not assume a steadystate, large buffer, or many sources regime. We also explore the scale of growth of delays as a function of the length of the path. The appendix contains an analysis for selfsimilar traffic with a Gaussian tail distribution.
Does Link Scheduling Matter on Long Paths?
 INTERNATIONAL CONFERENCE ON DISTRIBUTED COMPUTING SYSTEMS
, 2010
"... We seek to provide an analytical answer whether the impact of the selection of link scheduling algorithms diminishes on long network paths. The answer is provided through a detailed multinode delay analysis, which is applicable to a broad class of scheduling algorithms, and which can account for st ..."
Abstract

Cited by 3 (3 self)
 Add to MetaCart
(Show Context)
We seek to provide an analytical answer whether the impact of the selection of link scheduling algorithms diminishes on long network paths. The answer is provided through a detailed multinode delay analysis, which is applicable to a broad class of scheduling algorithms, and which can account for statistical multiplexing. The analysis is enabled by two contributions: (1) We derive a function that can characterize the available bandwidth at a node for various scheduling algorithms. The function has an accuracy that recovers necessary and sufficient conditions for satisfying worstcase delay bounds at a single node; (2) We obtain endtoend delay bounds by providing an explicit solution to an optimization problem, in which the service received at multiple nodes is subsumed into a single function. By presenting a unified analysis that captures the properties of a broad group of schedulers in a single parameter, we can provide insight how the choice of scheduling algorithms impacts endtoend delay bounds. An important finding of this paper is that some schedulers show noticeable performance differences which persist in a network setting with long paths.
A Guide to the Stochastic Network Calculus
"... Abstract—The aim of the stochastic network calculus is to comprehend statistical multiplexing and scheduling of nontrivial traffic sources in a framework for endtoend analysis of multinode networks. To date, several models, some of them with subtle yet important differences, have been explored t ..."
Abstract

Cited by 3 (2 self)
 Add to MetaCart
Abstract—The aim of the stochastic network calculus is to comprehend statistical multiplexing and scheduling of nontrivial traffic sources in a framework for endtoend analysis of multinode networks. To date, several models, some of them with subtle yet important differences, have been explored to achieve these objectives. Capitalizing on previous works, this paper contributes an intuitive approach to the stochastic network calculus, where we seek to obtain its fundamental results in the possibly easiest way. For this purpose, we will now and then trade generality or precision for simplicity. In detail, the method that is assembled in this work uses moment generating functions, known from the theory of effective bandwidths, to characterize traffic arrivals and network service. Thereof, affine envelope functions with exponentially decaying overflow profile are derived to compute statistical endtoend backlog and delay bounds for networks. I.
Stochastic service curve and delay bound analysis: a single node case
 Computer Science from University of Kaiserslautern
, 2013
"... ar ..."
(Show Context)
A Temporal Network Calculus Approach to Service Guarantee Analysis of Stochastic Networks
"... Many computer networks such as wireless networks are stochastic in nature. In order to perform performance guarantee analysis of such networks, a theory, called stochastic network calculus, has evolved. In the stochastic network calculus literature, most results are based on spacedomain traffic and ..."
Abstract

Cited by 1 (0 self)
 Add to MetaCart
(Show Context)
Many computer networks such as wireless networks are stochastic in nature. In order to perform performance guarantee analysis of such networks, a theory, called stochastic network calculus, has evolved. In the stochastic network calculus literature, most results are based on spacedomain traffic and service models where the arrival process and the service process are respectively characterized by the cumulative amount of arrival and the cumulative amount of service. Recently, a novel approach called timedomain approach to stochastic network calculus (SNC) has been proposed, where the traffic and service models are defined based on the cumulative interarrival times and the cumulative service times respectively. In this paper, we concretize the timedomain SNC traffic and service models by linking some wellknown stochastic processes to them. In addition, we exemplify the temporal analysis approach by investigating the delay performance of a GilbertElliott channel. The results show that the delay bound can be improved under the independence condition. Furthermore, a comparison between the temporal and the spatial analysis results reveals that the two analytical approaches essentially yield close results. 1.
On Using Storage and Genset for Mitigating Power Grid Failures
"... I hereby declare that I am the sole author of this thesis. This is a true copy of the thesis, including any required final revisions, as accepted by my examiners. I understand that my thesis may be made electronically available to the public. ii Although modern society is critically reliant on power ..."
Abstract
 Add to MetaCart
(Show Context)
I hereby declare that I am the sole author of this thesis. This is a true copy of the thesis, including any required final revisions, as accepted by my examiners. I understand that my thesis may be made electronically available to the public. ii Although modern society is critically reliant on power grids, even modern power grids are subject to unavoidable outages due to storms, lightning strikes, and equipment failures. The situation in developing countries is even worse, with frequent load shedding lasting several hours a day due to unreliable generation. We study the use of battery storage to allow a set of homes in a single residential neighbourhood to avoid power outages. Due to the high cost of storage, our goal is to choose the smallest battery size such that, with high target probability, there is no loss of power despite a grid outage. Recognizing that the most common approach today for mitigating outages is to use a diesel generator (genset), we study the related problem of minimizing the carbon footprint of genset operation. Drawing on recent results, we model both problems as buffer sizing problems that can be addressed using stochastic network calculus. We show that this approach greatly improves battery sizing in contrast to prior approaches. Specifically, a numerical study shows that, for a neighbourhood of 100 homes, our approach computes a battery size, which is less than 10 % more than the minimum possible size necessary to satisfy a one day in ten years loss probability (2.7∗104). Moreover, we are able to estimate the carbon footprint reduction, compared to an exact numerical analysis, within a factor of 1.7. We also study the genset scheduling problem when the rate of genset fuel consumption is given by an affine function instead of a linear function of the current power. We give alternate scheduling, an online scheduling strategy that has a competitive ratio of k1