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Recent and Emerging Topics in Wireless Industrial Communications: A Selection
, 2007
"... In this paper we discuss a selection of promising and interesting research areas in the design of protocols and systemsforwirelessindustrialcommunications.Wehaveselected topicsthathaveeitheremergedashottopicsintheindustrial communicationscommunityinthelastfewyears(likewireless sensornetworks),orwhi ..."
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Cited by 96 (1 self)
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In this paper we discuss a selection of promising and interesting research areas in the design of protocols and systemsforwirelessindustrialcommunications.Wehaveselected topicsthathaveeitheremergedashottopicsintheindustrial communicationscommunityinthelastfewyears(likewireless sensornetworks),orwhichcouldbeworthwhileresearchtopicsin thenextfewyears(forexamplecooperativediversitytechniques for error control, cognitive radio/opportunistic spectrum access for mitigation of external interferences).
Delay Bounds under Arbitrary Multiplexing
, 2007
"... Network calculus has proven as a valuable and versatile methodology for worstcase analysis of communication networks. One issue in which it is still lacking is the treatment of aggregate multiplexing, in particular if the FIFO property cannot be assumed when flows are merged. In this report, we add ..."
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Cited by 28 (8 self)
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Network calculus has proven as a valuable and versatile methodology for worstcase analysis of communication networks. One issue in which it is still lacking is the treatment of aggregate multiplexing, in particular if the FIFO property cannot be assumed when flows are merged. In this report, we address the problem of bounding the delay of individual traffic flows in feedforward networks under arbitrary multiplexing. Somewhat surprisingly, we find that direct application of network calculus results in loose bounds even in seemingly simple scenarios. The reasons for this failure of network calculus are discussed in detail and a method to arrive at tight delay bounds for arbitrary (aggregate) multiplexing is presented. This method is based on the solution of an optimization problem. For the special case of sinktree networks this optimization problem is solved explicitly, thus arriving at a closedform expression for the delay bound. Numerical experiments illustrate that in sinktree networks the improvement over bounds based on direct application of network calculus can be considerable.
Network calculus delay bounds in queueing networks with exact solutions
 In 20th International Teletraffic Congress (ITC
, 2007
"... Abstract. The purpose of this paper is to shed light on the accuracy of probabilistic delay bounds obtained with network calculus. In particular, by comparing calculus bounds with exact results in a series of M/M/1 queues with cross traffic, we show that reasonably accurate bounds are achieved when ..."
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Cited by 22 (11 self)
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Abstract. The purpose of this paper is to shed light on the accuracy of probabilistic delay bounds obtained with network calculus. In particular, by comparing calculus bounds with exact results in a series of M/M/1 queues with cross traffic, we show that reasonably accurate bounds are achieved when the percentage of cross traffic is low. We use recent results in network calculus and, in addition, propose novel bounds based on Doob’s maximal inequality for supermartingales. In the case of single M/M/1 and �when M/D/1 queues, our results improve existing bounds by the utilization factor ρ converges to one. 1 Ω�log(1−ρ) −1
Understanding fairness and its impact on quality of service
 in IEEE 802.11,” in Proceedings of IEEE INFOCOM. IEEE, 2009
"... Abstract — The Distributed Coordination Function (DCF) aims at fair and efficient medium access in IEEE 802.11. In face of its success, it is remarkable that there is little consensus on the actual degree of fairness achieved, particularly bearing its impact on quality of service in mind. In this pa ..."
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Cited by 21 (2 self)
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Abstract — The Distributed Coordination Function (DCF) aims at fair and efficient medium access in IEEE 802.11. In face of its success, it is remarkable that there is little consensus on the actual degree of fairness achieved, particularly bearing its impact on quality of service in mind. In this paper we provide an accurate model for the fairness of the DCF. Given M greedy stations we assume fairness if a tagged station contributes a share of 1/M to the overall number of packets transmitted. We derive the probability distribution of fairness deviations and support our analytical results by an extensive set of measurements. We find a closedform expression for the improvement of longterm over shortterm fairness. Regarding the random countdown values we quantify the significance of their distribution whereas we discover that fairness is largely insensitive to the distribution parameters. Based on our findings we view the DCF as emulating an ideal fair queuing system to quantify the deviations from a fair rate allocation. We deduce a stochastic service curve model for the DCF to predict packet delays in IEEE 802.11. We show how a station can estimate its fair bandwidth share from passive measurements of its traffic arrivals and departures. I.
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 ..."
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Cited by 20 (11 self)
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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
E.: Tight performance bounds in the worstcase analysis of feedforward networks
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On Superlinear Scaling of Network Delays
"... We investigate scaling properties of endtoend delays in packet networks for a flow that traverses a sequence of H nodes and that experiences cross traffic at each node. When the traffic flow and the cross traffic do not satisfy independence assumptions, we find that delay bounds scale faster than ..."
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Cited by 14 (7 self)
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We investigate scaling properties of endtoend delays in packet networks for a flow that traverses a sequence of H nodes and that experiences cross traffic at each node. When the traffic flow and the cross traffic do not satisfy independence assumptions, we find that delay bounds scale faster than linearly. More precisely, for exponentially bounded packetized traffic we show that delays grow with Θ(H log H) in the number of nodes on the network path. This superlinear scaling of delays is qualitatively different from the scaling behavior predicted by a worstcase analysis or by a probabilistic analysis assuming independence of traffic arrivals at network nodes.
On expressing networks with flow transformation in convolutionform
 In Proceedings of IEEE INFOCOM
, 1979
"... Abstract—Convolutionform networks have the property that the endtoend service of network flows can be expressed in terms of a (min;+)convolution of the pernode services. This property is instrumental for deriving endtoend queueing results which fundamentally improve upon alternative results d ..."
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Cited by 11 (6 self)
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Abstract—Convolutionform networks have the property that the endtoend service of network flows can be expressed in terms of a (min;+)convolution of the pernode services. This property is instrumental for deriving endtoend queueing results which fundamentally improve upon alternative results derived by a nodebynode analysis. This paper extends the class of convolutionform networks with stochastic settings to scenarios with flow transformations, e.g., by loss, dynamic routing or retransmissions. In these networks, it is shown that by using the tools developed in this paper endtoend delays grow as O(n) in the number of nodes n; in contrast, by using the alternative nodebynode analysis, endtoend delays grow as O (n2). I.
Network calculus and queueing theory: two sides of one coin
 in Proc. 4th International Conference on Performance Evaluation Methodologies and Tools (VALUETOOLS
, 2009
"... Network calculus is a theory dealing with queueing type problems encountered in computer networks, with particular focus on quality of service guarantee analysis. Queueing theory is the mathematical study of queues, proven to be applicable to a wide area of problems, generally concerning about the ( ..."
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Cited by 8 (3 self)
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Network calculus is a theory dealing with queueing type problems encountered in computer networks, with particular focus on quality of service guarantee analysis. Queueing theory is the mathematical study of queues, proven to be applicable to a wide area of problems, generally concerning about the (average) quantities in an equilibrium state. Since both network calculus and queueing theory are analytical tools for studying queues, a question arises naturally as is if and where network calculus and queueing theory meet. In this paper, we explore queueing principles that underlie network calculus and exemplify their use. Particularly, based on the network calculus queueing principles, we show that for GI/GI/1, similar inequalities in the theory of queues can be derived. In addition, we prove that the endtoend performance of a tandem network is independent of the order of servers in the network even under some general settings. Through these, we present a network calculus perspective on queues and relate network calculus to queueing theory. 1.
Nonasymptotic throughput and delay distributions in multihop wireless networks
 In Allerton Conference on Communications, Control and Computing
, 2010
"... Abstract—The class of GuptaKumar results give the asymptotic throughput in multihop wireless networks but cannot predict the throughput behavior in networks of typical size. This paper addresses the nonasymptotic analysis of the multihop wireless communication problem and provides, for the firs ..."
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Cited by 8 (4 self)
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Abstract—The class of GuptaKumar results give the asymptotic throughput in multihop wireless networks but cannot predict the throughput behavior in networks of typical size. This paper addresses the nonasymptotic analysis of the multihop wireless communication problem and provides, for the first time, closedform results on multihop throughput and delay distributions. The results are nonasymptotic in that they hold for any number of nodes and also fully account for transient regimes, i.e., finite time scales, delays, as well as bursty arrivals. Their accuracy is supported by the recovery of classical singlehop results, and also by simulations from empirical data sets with realistic mobility settings. Moreover, for a specific network scenario and a fixed pair of nodes, the results confirm GuptaKumar’s Ω