Self-Similarity in a multi-stage queueing ATM switch fabric

Recent studies of digital network traffic have shown that arrival processes in such an environment are more accurately modeled as a statistically self-similar process, rather than as a Poisson-based one. We present a simulation of a combination sharedoutput queueing ATM switch fabric, sourced by two models of self-similar input. The effect of self-similarity on the average queue length and cell loss probability for this multi-stage queue is examined for varying load, buffer size, and internal speedup. The results using two self-similar input models, Pareto-distributed interarrival times and a Poisson-Zeta ON-OFF model, are compared with each other and with results using Poisson interarrival times and an ON-OFF bursty traffic source with Ge ometrically distributed burst lengths. The results show that at a high utilization and at a high degree of self-similarity, switch performance improves slowly with increasing buffer size and speedup, as compared to the improvement using Poisson-based traffic

Optimum traffic allocation in bundled energy-efficient ethernet links

The energy demands of Ethernet links have been an active focus of research in the recent years. This work has enabled a new generation of energy-efficient Ethernet (EEE) interfaces able to adapt their power consumption to the actual traffic demands, thus yielding significant energy savings. With the energy consumption of single network connections being a solved problem, in this paper, we focus on the energy demands of link aggregates that are commonly used to increase the capacity of a network connection. We build on known energy models of single EEE links to derive the energy demands of the whole aggregate as a function on how the traffic load is spread among its powered links. We then provide a practical method to share the load that minimizes overall energy consumption with controlled packet delay and prove that it is valid for a wide range of EEE links. Finally, we validate our method with both synthetic and real traffic traces captured in Internet backbones.Xunta de Galici

Leveraging energy saving capabilities of current EEE interfaces via pre-coalescing

The low power idle mode implemented by Energy Efficient Ethernet (EEE) allows network interfaces to save up to 90% of their nominal energy consumption when idling. There is an ample body of research that recommends the use of frame coalescing algorithms—that enter the low power mode as soon as there is no more traffic waiting to be sent, and delay the exit from this mode until there is an acceptable amount of traffic queued—to minimize energy usage while maintaining an acceptable performance. However, EEE capable hardware from several manufactures delays the entrance to the low power mode for a considerable amount of time (hysteresis). In this paper we augment existing EEE energy models to account for the hysteresis delay and show that, using the configuration ranges provided by manufacturers, most existing EEE networking devices are unable to obtain significant energy savings. To improve their energy efficiency, we propose to implement frame coalescing directly at traffic sources, before reaching the network interface. We also derive the optimum coalescing parameters to obtain a given target energy consumption at the EEE device when its configuration parameters are known in advance.Agencia Estatal de Investigación | Ref. TEC2017-85587-

Connection admission control and packet scheduling for IEEE 802.16 networks

Includes bibliographical references.The IEEE 802.16 standard introduced as one of the Wireless Metropolitan Area Networks (WMAN) for Broadband Wireless Access (BWA) which is known as Worldwide Interoperability for Microwave Access (WiMAX), provides a solution of broadband connectivity to areas where wired infrastructure is economically and technically infeasible. Apart from the advantage of having high speeds and low costs, IEEE 802.16 has the capability to simultaneously support various service types with required QoS characteristics. ... While IEEE 802.16 standard defines medium access control (MAC) and physical (PHY) layers specification, admission control and packet scheduling mechanisms which are important elements of QoS provisioning are left to vendors to design and implement for service differentiation and QoS support

A hybrid queueing model for fast broadband networking simulation

PhDThis research focuses on the investigation of a fast simulation method for broadband telecommunication networks, such as ATM networks and IP networks. As a result of this research, a hybrid simulation model is proposed, which combines the analytical modelling and event-driven simulation modelling to speeding up the overall simulation. The division between foreground and background traffic and the way of dealing with these different types of traffic to achieve improvement in simulation time is the major contribution reported in this thesis. Background traffic is present to ensure that proper buffering behaviour is included during the course of the simulation experiments, but only the foreground traffic of interest is simulated, unlike traditional simulation techniques. Foreground and background traffic are dealt with in a different way. To avoid the need for extra events on the event list, and the processing overhead, associated with the background traffic, the novel technique investigated in this research is to remove the background traffic completely, adjusting the service time of the queues for the background traffic to compensate (in most cases, the service time for the foreground traffic will increase). By removing the background traffic from the event-driven simulator the number of cell processing events dealt with is reduced drastically. Validation of this approach shows that, overall, the method works well, but the simulation using this method does have some differences compared with experimental results on a testbed. The reason for this is mainly because of the assumptions behind the analytical model that make the modelling tractable. Hence, the analytical model needs to be adjusted. This is done by having a neural network trained to learn the relationship between the input traffic parameters and the output difference between the proposed model and the testbed. Following this training, simulations can be run using the output of the neural network to adjust the analytical model for those particular traffic conditions. The approach is applied to cell scale and burst scale queueing to simulate an ATM switch, and it is also used to simulate an IP router. In all the applications, the method ensures a fast simulation as well as an accurate result