Self-similar Traffic Input Research Articles

Performance analysis of asynchronous priority-based internet router under self-similar traffic input - queueing system with Markovian input and hyper-exponential services

In this paper, queueing behaviour of asynchronous priority-based internet router with self-similar traffic input is analysed. As Markov modulated Poisson process (MMPP) emulates self-similar traffic, it is used as input process of pertinent queueing system. For quality of service (QoS) guarantee in a broadband integrated services digital network (B-ISDN), partial buffer sharing (PBS) mechanism is promising one. Since, network traffic is asynchronous and of variable packet lengths, wavelength division multiplexing (WDM) technology is to be employed, according to which, each output port is modelled as multi server queueing system. The service times (packet lengths) are assumed to follow hyper-exponential (Hk) distribution. For the said reasons, router here is modelled as MMPP/Hk/s/C queueing system employing PBS mechanism. High and low priority packet loss probabilities, and mean lengths of non-critical and critical periods are computed, and presented graphically. This analysis is useful in dimensioning the priority-based asynchronous router with self-similar traffic input.

Performance analysis of asynchronous priority-based internet router under self-similar traffic input - queueing system with Markovian input and hyper-exponential services

In this paper, queueing behaviour of asynchronous priority-based internet router with self-similar traffic input is analysed. As Markov modulated Poisson process (MMPP) emulates self-similar traffic, it is used as input process of pertinent queueing system. For quality of service (QoS) guarantee in a broadband integrated services digital network (B-ISDN), partial buffer sharing (PBS) mechanism is promising one. Since, network traffic is asynchronous and of variable packet lengths, wavelength division multiplexing (WDM) technology is to be employed, according to which, each output port is modelled as multi server queueing system. The service times (packet lengths) are assumed to follow hyper-exponential (Hk) distribution. For the said reasons, router here is modelled as MMPP/Hk/s/C queueing system employing PBS mechanism. High and low priority packet loss probabilities, and mean lengths of non-critical and critical periods are computed, and presented graphically. This analysis is useful in dimensioning the priority-based asynchronous router with self-similar traffic input.

Loss behaviour analysis of asynchronous internet switch under self-similar traffic input using MMPP/PH/c/K queueing system employing PBS mechanism

In this paper, we analyse the loss behaviour of the wavelength division multiplexing (WDM) priority-based switch with self-similar traffic. As Markov modulated Poisson process (MMPP) emulates self-similar internet traffic one can use MMPP that is fitted for self-similar traffic as input process to investigate the queueing behaviour of the switch. In view of WDM technology in networking, each output port of switch is modelled as multi-server queueing system. In general, network traffic is asynchronous and of variable packet lengths. Service times (packet lengths) are assumed to follow more general one namely phase-type (PH) distribution. Partial buffer sharing (PBS) mechanism is employed to guarantee quality of service (QoS). Finally, switch under consideration is equivalent to MMPP/PH/c/K queueing system with PBS mechanism. The performance measures, high priority and low priority packet loss probabilities are computed. This type of analysis is useful in dimensioning the switch employing PBS mechanism under self-similar traffic input.

Loss behaviour analysis of asynchronous internet switch under self-similar traffic input using MMPP/PH/c/K queueing system employing PBS mechanism

Loss behaviour analysis of asynchronous internet switch under self-similar traffic input using MMPP/PH/c/K queueing system employing PBS mechanism

Loss behavior of internet router with priority based self-similar synchronous traffic-multi server queueing system with Markovian input

In this paper, queueing behavior of the Internet router employing priority based partial buffer sharing mechanism under synchronous self-similar traffic input is investigated. Input traffic is modelled by Markov modulated Poisson process (MMPP). In view of wavelength division multiplexing technology, output port of the router is modelled as multi-server (MMPP/D/c/K) queueing system. Service times (packet lengths) are assumed to be deterministic as the traffic under consideration is slotted synchronous. Performance measures, namely, high priority and low priority packet loss probabilities, and mean length of non-critical and critical periods against the system parameters and traffic parameters are computed by means of matrix-geometric methods and approximate Markovian model. These results are useful in dimensioning the router to provide differentiated services and quality of service guarantee.

Performance Analysis of Wavelength Division Multiplexing Asynchronous Internet Router Employing Space Priority Mechanism under Self-Similar Traffic Input—Multi-Server Queueing System with Markovian Input and Erlang-k Services

In this paper, we analyze the queueing behaviour of wavelength division multiplexing (WDM) Internet router employing partial buffer sharing (PBS) mechanism with self-similar traffic input. In view of WDM technology in networking, each output port of the router is modelled as multi-server queueing system. To guarantee the quality of service (QoS) in Broadband integrated services digital network (B-ISDN), PBS mechanism is a promising one. As Markov modulated Poisson process (MMPP) emulates self-similar Internet traffic, we can use MMPP as input process of queueing system to investigate queueing behaviour of the router. In general, as network traffic is asynchronous (unslotted) and of variable packet lengths, service times (packet lengths) are assumed to follow Erlang-k distribution. Since, the said distribution is relatively general compared to deterministic and exponential. Hence, specific output port of the router is modelled as MMPP/Ek/s/C queueing system. The long-term performance measures namely high priority and low priority packet loss probabilities and the short-term performance measures namely mean lengths of critical and non-critical periods against the system parameters and traffic parameters are computed by means of matrix-geometric methods and approximate Markovian model. This kind of analysis is useful in dimensioning the router under self-similar traffic input employing PBS mechanism to provide differentiated services (DiffServ) and QoS guarantee.

Performance Analysis of Hybrid Polling Schemes with Multiple Classes of Self-Similar and Long-Range Dependent Traffic Input

Queuing delay have significant impact on the performance of network applications. To meet distinct delay requirements of multi-classend-user traffic,various queuing and scheduling schemeshave been proposed. These schemes are analogous to a polling mechanism in which multiple traffic queues are concurrently handled by a single scheduler. However, researchers were unable to analyze this synergy between the conventional queuingcum- scheduling and polling models. Moreover, research on analyzing polling models assumed traditional Poisson traffic distribution which is unable to capture self-similar and long-range dependent (LRD) characteristics and hence yield misleading results. Furthermore, published work related to self-similar traffic modeling is mainly based on conventional queuing-cum-scheduling which are simple approximations.The objective of this work is to analyze different combinations of conventional queuing and polling models. In this paper, we exploit the synergy between traditional queuing-cum-scheduling and polling models. We analyze different combinations of queuing and polling mechanisms with realistic traffic distributions i.e., selfsimilar and LRD. An analytical framework for G/M/1 queuing system is developedwhich contemplatesmultiple classes of self-similar and LRDtraffic as input.We formulate the Markov chain for G/M/1 queuing system and extract closed-form expressions of queuing delay for corresponding traffic classes. We analyzea combination of limited service polling model with non-pre-emptive priority queuing. Different combinations of polling models (i.e., exhaustive, gated and limited service) are also analyzed. We validate the performance of the proposed analytical framework through simulations. Simulation results suggest that synergy of polling and schedulingdangle promising results.

The Exact Analysis of Limited Service Polling Systems Combined with Non-preemptive Priority Scheduling under Self-similar Traffic Input

The cyclic execution of several multi-typed queues through a unified server requires superlative tactics of polling strategies. Further, a number of traditional scheduling schemes have been put forward to provide assured Quality of Service (QoS) to the end-user. In the prior work, no effort has been put to combine the traditional scheduling schemes with polling mechanisms. Moreover, in the prior work, the researchers have utilized traditional Poisson distribution to analyze a variety of polling mechanisms to offer the standardized QoS to the end user. However, it has been proven through numerous studies that traffic carried by internet is self-similar and unfortunately, the traditional Poisson models are unable to capture the bursty nature of internet traffic. To overcome the limitations of prior work, in the present study, we combine the limited service polling model with traditional non-preemptive scheduling scheme in two different ways. We build an analytical framework considering multiple classes of self-similar traffic and analyze their behavior on the basis of G/M/1 queuing system. We construct the Markov chain for G/M/1 queuing system and present the closed form expressions of packet latencies for related traffic classes. Simulated experiments in C++ were performed to test our proposed analytical framework for evaluating the QoS parameters and Markov chain transformation. This study clearly indicates that the combination of traditional polling mechanism with common scheduling scheme such as priority can offer a differential treatment to facilitate the required QoS for latest 4G wireless network applications according to their requirement.

Approximate Markovian model for delay behavior of internet router under self – similar traffic input

It has been reported that Internet Protocol (IP) packet traffic exhibits self-similarity or long range dependence (LRD) and causes degradation of router performance. Therefore, it is crucial for an appropriate buff er design of router. In this paper, we propose an approximate Markovian model for delay behavior of router under self-similar traffic input. Original 16 −MMPP which emulates the self-similar input traffic is approximated by 2 − MAP. Input traffic is assumed to be of asynchronous variable length. Numerical examples show that our method gives accurate results. This result can be applied in evaluating real time asynchronous router.

Optical Router Control Architecture and Contention Resolution Algorithms Capable of Asynchronous, Variable-Length Packet Switching

This paper presents a new optical-label switching (OLS) router control plane controller for multihop asynchronous, variable-length packet switching incorporating fast, fair, and wavelength-aware arbitration. The proposed optical router controller implements efficient unicast/multicast packet contention resolution algorithms and channel scheduling schemes to resolve the data plane switch fabric contention. The paper evaluates the performance of proposed algorithms in a multihop OLS simulation network with self-similar traffic input under various traffic scenarios. The simulation results demonstrate that the proposed algorithms effectively improve the multihop OLS network performance. The hardware-efficient design and implementation of the proposed router controller and major modules are evaluated in terms of the area and delay for various switch sizes on a Xilinx XCV1000E field programmable gate array (FPGA) chip. Finally, this paper experimentally demonstrates the combined unicast and multicast video streaming enabled by the proposed OLS router control techniques over a label switching testbed with edge routers and realistic Ethernet/IP traffic input.

Analysis of Queuing Behaviors with Self-similar Traffic in Wireless Channels

Many measurement studies showed that network traffic usually exhibits self-similar nature, meanwhile, wireless fading channels lead to the time-variant service rates of network nodes. Compared with classical queuing systems with Markov sources or constant service rates, the queuing system with self-similar input in a wireless fading channel is more complicated, and it is very difficult to obtain closed-form formulae for the queuing performances. In this paper, we study queuing behaviors with self-similar traffic input in wireless channels by establishing a queuing system model, and present a convenient and efficient algorithm to estimate the queue length distributions. Simulation results validate the accuracy of the proposed estimation algorithm. Finally, we analyze effective service rates of wireless channels based on the estimation algorithm, and draw some meaningful conclusions.

Transient process relaxation time research under the condition of self-similar traffic input in wireless networks

In the article, the results of measuring the traffic in wireless networks are presented. The results provide evidence of the traffic being notably self-similar. The two following models were developed in order to estimate the parameters of a wireless network operating along with the input traffic being self-similar: a model for systems with no restrictions on the quantity of the orders in the system lines and a model for systems with limited buffer volumes. The two types of incoming traffic that each system was simulated for were the Poisson and self-similar traffic.

Edge node buffer usage in optical burst switching networks

Optical Burst Switching (OBS) combines the benefits of Optical Packet Switching and Optical Circuit Switching technologies to provide an efficient, yet cost effective, method for data transmission in an all-optical, bufferless, core network. While most studies on OBS has concentrated on the core OBS network, we contribute new studies for the buffer requirement of an OBS edge node. The buffer usage for OBS systems only arises in the edge nodes since they contain an array of assemblers which combines electronic data with a common destination into an OBS burst stream for transmission in an all-optical bufferless core network. Specifically, we present two analytical results for buffer usage in an OBS edge node: one for Poisson traffic and the other for self-similar traffic input. The results show that the aggregated traffic from many assemblers inherits the characteristics of the source input traffic. This means that the output traffic approaches Poisson if the input traffic is Poisson, and the output traffic remains self-similar if the input is self-similar. These results lead to the following important design issues when dimensioning buffer requirements in an OBS edge node: if the traffic input is Poisson, the M/G/m model is the model to use for obtaining the upper bound on buffer usage in an OBS edge node; and for the case of self-similar traffic, Brichet’s method can be used to provide the upper and lower bound.

Multiscale Analysis and Control of Networks with Fractal Traffic

A recently introduced multiscale framework is used to develop efficient analysis and design techniques for networks with self-similar traffic. These allow the interarrival density function for fractal point processes under Bernoulli random erasure to be determined, as well as the counting process distribution for superposition of these processes. The results suggest that fractal characteristics are preserved under traffic branching and merging, which may, in turn, provide insight into the prevalence of self-similarity in aggregate traffic broadly observed on real networks. Multiscale techniques are also developed for analyzing fractal queueing scenarios. The persistent memory inherent in the underlying point processes leads to substantially different behavior than is observed in traditional queueing scenarios, and important implications on resource consumption and quality of service are discussed. Finally, we show how multiscale methods can be used with dynamic programming techniques to develop efficient and practical control policies for these fractal queues. In particular, optimal server control is developed for a memoryless queueing system with self-similar traffic input, and optimal flow control is formulated for self-similar service of memoryless traffic. Exploiting recent history, these controllers are shown to achieve substantially better performance—both in terms of quality of service and resource utilization—than queueing control strategies traditionally used.