Queueing and Fluid Analysis of Partial Message Discarding Policy

We consider a stream of packets that arrive at a queue with a finite buffer. A group of consecutive packets constitutes a frame. We assume that when an arriving packet finds the queue full, not only is the packet lost but also the future packets that belong to the same frame will be rejected. The first part of the paper deals with a detailed packet level queueing model; we obtain exact expressions for the stationary queue length distribution and the goodput ratio (i.e. the fraction of arriving frames that experience no losses). The second part deals with a fluid model and the fluid analysis leads to simple closed form expressions for the stationary workload process and the fluid goodput ratio.     

On queueing delays of dispersed messages

We study the message queueing delays in a node of a communication system, where a message consists of a block of consecutive packets. The message delay is defined as the time elapsing between the arrival epoch of the first packet of the message to the system until after the transmission of the last packet of that message is completed. We distinguish between two types of message generation processes. The message can be generated as abatch or it can bedispersed over time. In this paper we focus on the dispersed generation model. The main difficulty in the analysis is due to the correlation between the system states observed by different packets of the same message. This paper introduces a new technique to analyze the message delay in such systems for different arrival models and different number of sessions. For anM/M/1 system with variable size messages and for the bursty traffic model, we obtain an explicit expression for the Laplace-Stieltjes transform (LST) of the message delay. Derivations are also provided for anM/G/1 system, for multiple session systems and for fixed message sizes. We show that the correlation has a strong effect on the performance of the system, and that the commonly usedindependence assumption, i.e., the assumption that the delays of packets are independent from packet to packet, can lead to wrong conclusions.     

Jittering performance of random deflection routing in packet networks

This paper reports a study of random deflection routing protocol and its impact on delay-jitter over packet networks. In case of congestion, routers with a random deflection routing protocol can forward incoming packets to links laying off shortest paths; namely, packets can be “deflected” away from their original paths. However, random deflection routing may send packets to several different paths, thereby introducing packet re-ordering. This could affect the quality of receptions, it could also impair the overall performance in transporting data traffic. Nevertheless, the present study reveals that deflection routing could actually reduce delay-jitter when the traffic loading on the network is not heavy.     

Real-time optimisation of access control lists for efficient Internet packet filtering

This paper considers an optimisation problem encountered in the implementation of traffic policies on network routers, namely the ordering of rules in an access control list to minimise or reduce processing time and hence packet latency. The problem is formulated as an objective function with constraints and shown to be NP-complete by translation to a known problem. Exact and heuristic solution methods are introduced, discussed and compared and computational results given. The emphasis throughout is on practical implementation of the optimisation process, that is within the tight constraints of a production network router seeking to reduce latency, on-line, in real-time but without the overhead of significant extra computation.     

Internet packet routing: Application of a K-quickest path algorithm

This paper describes a study on the application of an algorithm to rank the K-quickest paths to the routing of data packets in Internet networks. For this purpose an experimental framework was developed by considering two types of random generated networks. To simulate values of the IP packet sizes, a truncated Pareto distribution was defined, having in mind to reflect a key feature of Internet traffic, namely its self-similar stochastic nature. Results concerning the average CPU times of the algorithm for the different sets of experiments will be presented and discussed.     

Scheduling Multiclass Packet Streams to Minimize Weighted Loss

We consider the problem of scheduling an arriving sequence of packets at a single server. Associated with each packet is a deadline by which the packet must be scheduled. Each packet belongs to one of a predetermined set of classes, and each class has an associated weight value. The goal is to minimize the total weighted value of the packets that miss their deadlines. We first prove that there is no policy that minimizes this weighted loss for all finite arrival sequences of packets. We then present a class of greedy scheduling policies, called the current-minloss throughput-optimal (CMTO) policies. We characterize all CMTO policies, and provide examples of easily implementable CMTO policies. We compare CMTO policies with a multiclass extension of the earliest-deadline-first (EDF) policy, called EDF+, establishing that a subclass of CMTO policies achieves no more weighted loss than EDF+ for any traffic sequence, and at the same time achieves a substantial weighted-loss advantage over EDF+ for some traffic sequences – this advantage is shown to be arbitrarily close to the maximum possible achievable advantage. We also provide empirical results to quantify the weighted-loss advantage of CMTO policies over EDF+ and the static-priority (SP) policy, showing an advantage exceeding an order of magnitude when serving heavy-tailed aggregations of MPEG traces.     

Extremal dependence analysis of network sessions

We refine a stimulating study by Sarvotham et al. (Comput Networks 48:335–350, 2005) which highlighted the influence of peak transmission rate on network burstiness. From TCP packet headers, we amalgamate packets into sessions where each session is characterized by a 5-tuple (S,D,R,R ^∨,Γ)=(total payload, duration, average transmission rate, peak transmission rate, initiation time). After careful consideration, a new definition of peak rate is required. Unlike Sarvotham et al. (Comput Networks 48:335–350, 2005) who segmented sessions into two groups labelled alpha and beta, we segment into 10 sessions according to the empirical quantiles of the peak rate variable as a demonstration that the beta group is far from homogeneous. Our more refined segmentation reveals additional structure that is missed by segmentation into two groups. In each segment, we study the dependence structure of (S,D,R) and find that it varies across the groups. Furthermore, within each segment, session initiation times are well approximated by a Poisson process whereas this property does not hold for the data set taken as a whole. Therefore, we conclude that the peak rate level is important for understanding structure and for constructing accurate simulations of data in the wild. We outline a simple method of simulating network traffic based on our findings.     

Performance & packet traffic dynamics of Packet Switching Network model

Dynamics of packet traffic in data communication networks can be complex and often not well understood. Understanding of these complex dynamics is important for their control, prediction purposes and for the data networks design. The engineering community has described wired data networks architectures and studied them by means of a layered, hierarchical abstraction called ISO OSI (International Standard Organization Open System Interconnect) Reference Model. The Network Layer of the ISO OSI Reference Model is responsible for routing packets across the network from their sources to their destinations and for control of congestion in data networks. Using an abstraction of the Network Layer that we developed, we investigate packet traffic dynamics in our data network models of data communication networks of packet switching type, in particular near the phase transition point from free flow to congestion. We explore how these dynamics and network performance indicators are affected by network connection topology and routing algorithms. We consider static and adaptive routing algorithms. (© 2008 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim)     

A packet filter placement problem with application to defense against spoofed denial of service attacks

We analyze a problem in computer network security, wherein packet filters are deployed to defend a network against spoofed denial of service attacks. Information on the Internet is transmitted by the exchange of IP packets, which must declare their origin and destination addresses. A route-based packet filter verifies whether the purported origin of a packet is correct with respect to the current route map. We examine the optimization problem of finding a minimum cardinality set of nodes to filter in the network such that no spoofed packet can reach its destination. We prove that this problem is NP-hard, and derive properties that explicitly relate the filter placement problem to the vertex cover problem. We identify topologies and routing policies for which a polynomial-time solution to the minimum filter placement problem exists, and prove that under certain routing conditions a greedy heuristic for the filter placement problem yields an optimal solution.     

Dynamic power control in a fading downlink channel subject to an energy constraint

A central controller chooses a state-dependent transmission rate for each user in a fading, downlink channel by varying transmission power over time. For each user, the state of the channel evolves over time according to an exogenous continuous-time Markov chain (CTMC), which affects the quality of transmission. The traffic for each user, arriving at the central controller, is modeled as a finite-buffer Markovian queue with adjustable service rates. That is, for each user data packets arrive to the central controller according to a Poisson process and packet size is exponentially distributed; an arriving packet is dropped if the associated buffer is full, which results in degradation of quality of service. The controller forwards (downlink) the arriving packets to the corresponding user according to an optimally chosen transmission rate from a fixed set A _i of available values for each user i, depending on the backlog in the system and the channel state of all users. The objective is to maximize quality of service subject to an upper bound on the long-run average power consumption. We show that the optimal transmission rate for each user is solely a function of his own packet queue length and channel state; the dependence among users is captured through a penalty rate. Further, we explicitly characterize the optimal transmission rate for each user. This project is partially supported by Motorola grant # 0970-350-AF24. The authors thank Phil Fleming,Randy Berry and Achal Bassamboo for helpful comments.     

Energy and coherence loss rates in a one-dimensional vibrational system interacting with a bath

We consider the problem of the dynamics of a Gaussian wave packet in a one-dimensional harmonic ocsillator interacting with a bath. This problem arises in many chemical and biochemical applications related to the dynamics of chemical reactions. We take the bath-oscillator interaction into account in the framework of the Redfield theory. We obtain closed expressions for Redfield-tensor elements, which allows finding the explicit time dependence of the average vibrational energy. We show that the energy loss rate is temperature-independent, is the same for all wave packets, and depends only on the spectral function of the bath. We determine the degree of coherence of the vibrational motion as the trace of the density-matrix projection on a coherently moving wave packet. We find an explicit expression for the initial coherence loss rate, which depends on the wave packet width and is directly proportional to the intensity of the interaction with the bath. The minimum coherence loss rate is observed for a “coherent” Gaussian wave packet whose width corresponds to the oscillator frequency. We calculate the limiting value of the degree of coherence for large times and show that it is independent of the structural characteristics of the bath and depends only on the parameters of the wave packet and on the temperature. It is possible that residual coherence can be preserved at low temperatures. __________ Translated from Teoreticheskaya i Matematicheskaya Fizika, Vol. 153, No. 1, pp. 130–144, October, 2007.     

Queueing models for the analysis of communication systems

Queueing models can be used to model and analyze the performance of various subsystems in telecommunication networks; for instance, to estimate the packet loss and packet delay in network routers. Since time is usually synchronized, discrete-time models come natural. We start this paper with a review of suitable discrete-time queueing models for communication systems. We pay special attention to two important characteristics of communication systems. First, traffic usually arrives in bursts, making the classic modeling of the arrival streams by Poisson processes inadequate and requiring the use of more advanced correlated arrival models. Second, different applications have different quality-of-service requirements (packet loss, packet delay, jitter, etc.). Consequently, the common first-come-first-served (FCFS) scheduling is not satisfactory and more elaborate scheduling disciplines are required. Both properties make common memoryless queueing models (M/M/1-type models) inadequate. After the review, we therefore concentrate on a discrete-time queueing analysis with two traffic classes, heterogeneous train arrivals and a priority scheduling discipline, as an example analysis where both time correlation and heterogeneity in the arrival process as well as non-FCFS scheduling are taken into account. Focus is on delay performance measures, such as the mean delay experienced by both types of packets and probability tails of these delays.     

Delay analysis of multiclass queues with correlated train arrivals and a hybrid priority/FIFO scheduling discipline

We analyze the delay experienced in a discrete-time priority queue with a train-arrival process. An infinite user population is considered. Each user occasionally sends packets in the form of trains: a variable number of fixed-length packets is generated and these packets arrive to the queue at the rate of one packet per slot. This is an adequate arrival process model for network traffic. Previous studies assumed two traffic classes, with one class getting priority over the other. We extend these studies to cope with a general number M of traffic classes that can be partitioned in an arbitrary number N of priority classes (1 ≤ N ≤ M). The lengths of the trains are traffic-class-dependent and generally distributed. To cope with the resulting general model, an (M × )∞-sized Markovian state vector is introduced. By using probability generating functions, moments and tail probabilities of the steady-state packet delays of all traffic classes are calculated. Since this study can be useful in deciding how to partition traffic classes in priority classes, we demonstrate the impact of this partitioning for some specific cases.     

Impact of Bursty Traffic on Queues

The impact of bursty traffic on queues is investigated in this paper. We consider a discrete-time single server queue with an infinite storage room, that releases customers at the constant rate of c customers/slot. The queue is fed by an M/G/∞ process. The M/G/∞ process can be seen as a process resulting from the superposition of infinitely many ‘sessions’: sessions become active according to a Poisson process; a station stays active for a random time, with probability distribution G, after which it becomes inactive. The number of customers entering the queue in the time-interval [t, t + 1) is then defined as the number of active sessions at time t (t = 0,1, ...) or, equivalently, as the number of busy servers at time t in an M/G/∞ queue, thereby explaining the terminology. The M/G/∞ process enjoys several attractive features: First, it can display various forms of dependencies, the extent of which being governed by the service time distribution G. The heavier the tail of G, the more bursty the M/G/∞ process. Second, this process arises naturally in teletraffic as the limiting case for the aggregation of on/off sources [27]. Third, it has been shown to be a good model for various types of network traffic, including telnet/ftp connections [37] and variable-bit-rate (VBR) video traffic [24]. Last but not least, it is amenable to queueing analysis due to its very strong structural properties. In this paper, we compute an asymptotic lower bound for the tail distribution of the queue length. This bound suggests that the queueing delays will dramatically increase as the burstiness of the M/G/∞ input process increases. More specifically, if the tail of G is heavy, implying a bursty input process, then the tail of the queue length will also be heavy. This result is in sharp contrast with the exponential decay rate of the tail distribution of the queue length in presence of ‘non-bursty’ traffic (e.g. Poisson-like traffic). This revised version was published online in August 2006 with corrections to the Cover Date.     

Structural properties and stochastic bounds for a buffer problem in packetized voice transmission

We consider a communication channel which carries packetized voice. A fixed number (K) of calls are being transmitted. Each of these calls generates one packet at everyC timeslots and the channel can transmit at most one packet every timeslot. We consider the nontrivial caseK ≤C. We study the effectsK, C and the arrival process have on the number of packets in the buffer. When the call origination epochs in the firstC timeslots of theK calls are uniformly distributed (i.e. when the arrivals during the firstC timeslots have a multinomial distribution) it is shown that the stationary number of calls waiting in the buffer is stochastically increasing and convex in the number of calls. For a fixed average number of calls per slot, it is shown that increasing the number of slots per frame increases the stationary number of packets in the buffer in the sense of increasing convex ordering. Using this, it is shown that the stationary number of packets in the buffer is bounded from above by the number of packets in a stationary discreteM/D/1 queue with arrival rateK/C and unit service time. This bound is in the sense of the increasing convex order.     

On a packet scheduling problem for smart antennas and polyhedra defined by circular-ones matrices

In [E. Amaldi, A. Capone, F. Malucelli, Circular Arc Models and Algorithms for Packet Scheduling in Smart Antennas, IV ALIO/EURO Workshop on Applied Combinatorial Optimization, see: http://www-di.inf.puc-rio.br/~celso/artigos/pucon.ps, E. Amaldi, A. Capone, F. Malucelli, Discrete models and algorithms for packet scheduling in smart antennas, 2nd Cologne Twente Workshop on Graphs and Combinatorial Optimization] E. Amaldi et al. posed a combinatorial optimization problem that arises when scheduling packets in a smart antenna. The objective is to partition the set of users so as to minimize the number of time slots needed to transmit all the given packets. Here we will present a polynomial time algorithm for solving this packet scheduling problem. More generally, the algorithm solves an integer decomposition problem for polyhedra determined by a circular-ones constraint matrix, which might make it interesting also for other cyclic scheduling problems.     

Routing optimization in packet switching communication networks

For routing assignments a special model and an optimization algorithm are proposed. The efficiency of the routing assignments is evaluated by the average value of the total cost of delays for all packets in the network. It is the objective function. The main idea is that traffic, which is transmitted from the source node to the destination node, can be split between two or more logical paths. The minimum of the objective function can be found by varying the traffic on every path and simultaneously from all the source nodes to the destination nodes. If this approach is applied, then the objective function is nonseparable and nonlinear. Because its shape is unknown in advance, an adaptive nonlinear optimization algorithm is proposed. For evaluating its efficiency a special set of test functions has been used.     

Analysis of queueing policies in QoS switches

It is widely accepted that next-generation networks will provide guaranteed services, in contrast to the “best effort” approach today. We study and analyze queueing policies for network switches that support the QoS (Quality of Service) feature. One realization of the QoS feature is that packets are not necessarily all equal, with some having higher priorities than the others. We model this situation by assigning an intrinsic value to each packet. In this paper we are concerned with three different queueing policies: the nonpreemptive model, the FIFO preemptive model, and the bounded delay model. We concentrate on the situation where the incoming traffic overloads the queue, resulting in packet loss. The objective is to maximize the total value of packets transmitted by the queueing policy. The difficulty lies in the unpredictable nature of the future packet arrivals. We analyze the performance of the online queueing policies via competitive analysis, providing upper and lower bounds for the competitive ratios. We develop practical yet sophisticated online algorithms (queueing policies) for the three queueing models. The algorithms in many cases have provably optimal worst-case bounds. For the nonpreemptive model, we devise an optimal online algorithm for the common 2-value model. We provide a tight logarithmic bound for the general nonpreemptive model. For the FIFO preemptive model, we improve the general lower bound to 1.414, while showing a tight bound of 1.434 for the special case of queue size 2. We prove that the bounded delay model with uniform delay 2 is equivalent to a modified FIFO preemptive model with queue size 2. We then give improved upper and lower bounds on the 2-uniform bounded delay model. We also show an improved lower bound of 1.618 for the 2-variable bounded delay model, matching the previously known upper bound.