An acceleration simulation method for power law priority traffic

A method for accelerated simulation for simulated self-similar processes is proposed. This technique simplifies the simulation model and improves the efficiency by using excess packets instead of packet-by-packet source traffic for a FIFO and non-FIFO buffer scheduler. In this research is focusing on developing an equivalent model of the conventional packet buffer that can produce an output analysis (which in this case will be the steady state probability) much faster. This acceleration simulation method is a further development of the Traffic Aggregation technique, which had previously been applied to FIFO buffers only and applies the Generalized Ballot Theorem to calculate the waiting time for the low priority traffic (combined with prior work on traffic aggregation). This hybrid method is shown to provide a significant reduction in the process time, while maintaining queuing behavior in the buffer that is highly accurate when compared to results from a conventional simulatio

Characteristics of WAP traffic

This paper considers the characteristics of Wireless Application Protocol (WAP) traffic. We start by constructing a WAP traffic model by analysing the behaviour of users accessing public WAP sites via a monitoring system. A wide range of different traffic scenarios were considered, but most of these scenarios resolve to one of two basic types. The paper then uses this traffic model to consider the effects of large quantities of WAP traffic on the core network. One traffic characteristic which is of particular interest in network dimensioning is the degree of self-similarity, so the paper looks at the characteristics of aggregated traffic with WAP, Web and packet speech components to estimate its self-similarity. The results indicate that, while WAP traffic alone does not exhibit a significant degree of self-similarity, a combined load from various traffic sources retains almost the same degree of self-similarity as the most self-similar individual source

QuickCast: Fast and Efficient Inter-Datacenter Transfers using Forwarding Tree Cohorts

Large inter-datacenter transfers are crucial for cloud service efficiency and are increasingly used by organizations that have dedicated wide area networks between datacenters. A recent work uses multicast forwarding trees to reduce the bandwidth needs and improve completion times of point-to-multipoint transfers. Using a single forwarding tree per transfer, however, leads to poor performance because the slowest receiver dictates the completion time for all receivers. Using multiple forwarding trees per transfer alleviates this concern--the average receiver could finish early; however, if done naively, bandwidth usage would also increase and it is apriori unclear how best to partition receivers, how to construct the multiple trees and how to determine the rate and schedule of flows on these trees. This paper presents QuickCast, a first solution to these problems. Using simulations on real-world network topologies, we see that QuickCast can speed up the average receiver's completion time by as much as $10\times$ while only using $1.04\times$ more bandwidth; further, the completion time for all receivers also improves by as much as $1.6\times$ faster at high loads.Comment: [Extended Version] Accepted for presentation in IEEE INFOCOM 2018, Honolulu, H

ABC: A Simple Explicit Congestion Controller for Wireless Networks

We propose Accel-Brake Control (ABC), a simple and deployable explicit congestion control protocol for network paths with time-varying wireless links. ABC routers mark each packet with an "accelerate" or "brake", which causes senders to slightly increase or decrease their congestion windows. Routers use this feedback to quickly guide senders towards a desired target rate. ABC requires no changes to header formats or user devices, but achieves better performance than XCP. ABC is also incrementally deployable; it operates correctly when the bottleneck is a non-ABC router, and can coexist with non-ABC traffic sharing the same bottleneck link. We evaluate ABC using a Wi-Fi implementation and trace-driven emulation of cellular links. ABC achieves 30-40% higher throughput than Cubic+Codel for similar delays, and 2.2X lower delays than BBR on a Wi-Fi path. On cellular network paths, ABC achieves 50% higher throughput than Cubic+Codel

Traffic Characterization of an Internet of Things(IOT) Network Architecture

Internet of things (IoT) is an evolving paradigm that is currently getting more attention and rapidly gaining importance. The basic idea of IoT is to connect everyone and everything to the Internet for information exchange. It is essential to develop a clear understanding of characteristics of IoT traffic sources as well as to find a traffic model that efficiently characterizes the statistical behavior of IoT traffic. Since many IoT devices generate relatively small sized data, we are particularly interested in an IoT network architecture where data from a number of different IoT devices are aggregated at an IoT gateway. We focus on characterizing the IoT aggregated traffic pattern for three common IoT applications with real-time and non-real-time quality of service (QoS) requirements. These applications include healthcare, smart cities, and video surveillance. Our study is based on generating a real IoT traffic trace in a lab by using various sensors and devices in the aforementioned applications. The generated traffic trace is transmitted wirelessly over the air using Wi-Fi technology to an IoT gateway. The input network traffic to this gateway is characterized. In the experiments, the amount of input traffic to the gateway is varied and different traffic patterns for each of the selected applications are examined. Statistical tests and parameters are used to determine the best matching packet inter-arrival time distribution for different traffic penetrations. Moreover, we also examine packet size distributions. Based on our empirical data, the experimental results indicate that IoT packet inter-arrival time follows a Pareto distribution. However, it can be better modeled as a Weibull distribution in some traffic patterns. Our experimental results also reveal that the packet size distribution of different penetrations of the studied IoT applications is not in a good match with the commonly used Geometric distribution. Furthermore, we investigate the impact of traffic characterization on the performance of the considered IoT network architecture for a certain availability of network resources using computer simulations