Modelling Internet Traffic Streams with Ga/M/1/K Queuing Systems under Self-similarity

High-intensity concurrent arrivals of request packets in Internet traffic can cause dependence of event-to-event-times of the requests being served, which causes non-memoryless, modelled with heavy-tail distributions unlike common known traffics. The performance of Internet traffic can be examined using analytical models for the purpose of optimizing the system to reduce its operating costs. Therefore, our study examined a Ga/M/1/K Internet queue class (Gamma arrival processes, Ga; with memoryless-Poisson service process, M; a single server, 1, and K waiting room) and proposed specific derivations of its performance indicators. Real-life data of a corporate organisation Internet server was monitored at both peak and off-peak periods of its usage for Internet traffic data analysis. The minimum ‘0’ in the arrival process indicates self-similarity and was assessed using Hurst parameter, H, and their (standard deviation). ‘H’ > 0.5 arrival process in the peak period only, indicates self-similarity. Performance of Ga/M/1/K was compared with various queuing Internet traffic models used in existing literatures. Results showed that the value of the waiting room size for Ga/M/1/K has closest ties with true self-similar model at peak-periods usage of the Internet, which indicates possible concurrent arrival of clients' requests leading to more usage of the waiting room, but with light-tailed queue model at the off-peak periods. Therefore, the proposed Ga/M/1/K model can assist in evaluating the performance of high-intensity self-similar Internet traffic.      Keywords: Internet traffic; self-similarity; Ga/M/1/K model; gamma distributio

Non-Intrusive Measurement in Packet Networks and its Applications

PhDNetwork measurementis becoming increasingly important as a meanst o assesst he performanceo f packet networks. Network performance can involve different aspects such as availability, link failure detection etc, but in this thesis, we will focus on Quality of Service (QoS). Among the metrics used to define QoS, we are particularly interested in end-to-end delay performance. Recently, the adoption of Service Level Agreements (SLA) between network operators and their customersh as becomea major driving force behind QoS measurementm: easurementi s necessaryt o produce evidence of fulfilment of the requirements specified in the SLA. Many attempts to do QoS based packet level measurement have been based on Active Measurement, in which the properties of the end-to-end path are tested by adding testing packets generated from the sending end. The main drawback of active probing is its intrusive nature which causes extraburden on the network, and has been shown to distort the measured condition of the network. The other category of network measurement is known as Passive Measurement. In contrast to Active Measurement, there are no testing packets injected into the network, therefore no intrusion is caused. The proposed applications using Passive Measurement are currently quite limited. But Passive Measurement may offer the potential for an entirely different perspective compared with Active Measurements In this thesis, the objective is to develop a measurement methodology for the end-to-end delay performance based on Passive Measurement. We assume that the nodes in a network domain are accessible.F or example, a network domain operatedb y a single network operator. The novel idea is to estimate the local per-hop delay distribution based on a hybrid approach (model and measurement-based)W. ith this approach,t he storagem easurementd ata requirement can be greatly alleviated and the overhead put in each local node can be minimized, so maintaining the fast switching operation in a local switcher or router. Per-hop delay distributions have been widely used to infer QoS at a single local node. However, the end-to-end delay distribution is more appropriate when quantifying delays across an end-to-end path. Our approach is to capture every local node's delay distribution, and then the end-to-end delay distribution can be obtained by convolving the estimated delay distributions. In this thesis, our algorithm is examined by comparing the proximity of the actual end-to-end delay distribution with the estimated one obtained by our measurement method under various conditions. e. g. in the presence of Markovian or Power-law traffic. Furthermore, the comparison between Active Measurement and our scheme is also studied. 2 Network operators may find our scheme useful when measuring the end-to-end delay performance. As stated earlier, our scheme has no intrusive effect. Furthermore, the measurement result in the local node can be re-usable to deduce other paths' end-to-end delay behaviour as long as this local node is included in the path. Thus our scheme is more scalable compared with active probing

Meeting Real-Time Constraint of Spectrum Management in TV Black-Space Access

The TV set feedback feature standardized in the next generation TV system, ATSC 3.0, would enable opportunistic access of active TV channels in future Cognitive Radio Networks. This new dynamic spectrum access approach is named as black-space access, as it is complementary of current TV white space, which stands for inactive TV channels. TV black-space access can significantly increase the available spectrum of Cognitive Radio Networks in populated urban markets, where spectrum shortage is most severe while TV whitespace is very limited. However, to enable TV black-space access, secondary user has to evacuate a TV channel in a timely manner when TV user comes in. Such strict real-time constraint is an unique challenge of spectrum management infrastructure of Cognitive Radio Networks. In this paper, the real-time performance of spectrum management with regard to the degree of centralization of infrastructure is modeled and tested. Based on collected empirical network latency and database response time, we analyze the average evacuation time under four structures of spectrum management infrastructure: fully distribution, city-wide centralization, national-wide centralization, and semi-national centralization. The results show that national wide centralization may not meet the real-time requirement, while semi-national centralization that use multiple co-located independent spectrum manager can achieve real-time performance while keep most of the operational advantage of fully centralized structure.Comment: 9 pages, 7 figures, Technical Repor

Filter Scheduling Function Model In Internet Server: Resource Configuration, Performance Evaluation And Optimal Scheduling

ABSTRACT FILTER SCHEDULING FUNCTION MODEL IN INTERNET SERVER: RESOURCE CONFIGURATION, PERFORMANCE EVALUATION AND OPTIMAL SCHEDULING by MINGHUA XU August 2010 Advisor: Dr. Cheng-Zhong Xu Major: Computer Engineering Degree: Doctor of Philosophy Internet traffic often exhibits a structure with rich high-order statistical properties like selfsimilarity and long-range dependency (LRD). This greatly complicates the problem of server performance modeling and optimization. On the other hand, popularity of Internet has created numerous client-server or peer-to-peer applications, with most of them, such as online payment, purchasing, trading, searching, publishing and media streaming, being timing sensitive and/or financially critical. The scheduling policy in Internet servers is playing central role in satisfying service level agreement (SLA) and achieving savings and efficiency in operations. The increasing popularity of high-volume performance critical Internet applications is a challenge for servers to provide individual response-time guarantees. Existing tools like queuing models in most cases only hold in mean value analysis under the assumption of simplified traffic structures. Considering the fact that most Internet applications can tolerate a small percentage of deadline misses, we define a decay function model characterizes the relationship between the request delay constraint, deadline misses, and server capacity in a transfer function based filter system. The model is general for any time-series based or measurement based processes. Within the model framework, a relationship between server capacity, scheduling policy, and service deadline is established in formalism. Time-invariant (non-adaptive) resource allocation policies are design and analyzed in the time domain. For an important class of fixed-time allocation policies, optimality conditions with respect to the correlation of input traffic are established. The upper bound for server capacity and service level are derived with general Chebshev\u27s inequality, and extended to tighter boundaries for unimodal distributions by using VysochanskiPetunin\u27s inequality. For traffic with strong LRD, a design and analysis of the decay function model is done in the frequency domain. Most Internet traffic has monotonically decreasing strength of variation functions over frequency. For this type of input traffic, it is proved that optimal schedulers must have a convex structure. Uniform resource allocation is an extreme case of the convexity and is proved to be optimal for Poisson traffic. With an integration of the convex-structural principle, an enhance GPS policy improves the service quality significantly. Furthermore, it is shown that the presence of LRD in the input traffic results in shift of variation strength from high frequency to lower frequency bands, leading to a degradation of the service quality. The model is also extended to support server with different deadlines, and to derive an optimal time-variant (adaptive) resource allocation policy that minimizes server load variances and server resource demands. Simulation results show time-variant scheduling algorithm indeed outperforms time-invariant optimal decay function scheduler. Internet traffic has two major dynamic factors, the distribution of request size and the correlation of request arrival process. When applying decay function model as scheduler to random point process, corresponding two influences for server workload process is revealed as, first, sizing factor--interaction between request size distribution and scheduling functions, second, correlation factor--interaction between power spectrum of arrival process and scheduling function. For the second factor, it is known from this thesis that convex scheduling function will minimize its impact over server workload. Under the assumption of homogeneous scheduling function for all requests, it shows that uniform scheduling is optimal for the sizing factor. Further more, by analyzing the impact from queueing delay to scheduling function, it shows that queueing larger tasks vs. smaller ones leads to less reduction in sizing factor, but at the benefit of more decreasing in correlation factor in the server workload process. This shows the origin of optimality of shortest remain processing time (SRPT) scheduler

Analysis of GPRS Limitations

The General Packet Radio Service (GPRS) is a new standard for mobile data communications, which is implemented under the existing infrastructure of Global System for Mobile Communications (GSM). The promise capability of handling Internet Protocol traffic enables instant and constant connection to global network regardless of location and time. With its packet-based nature, the new technology facilitates new applications in wireless communications that have not been available previously. Nonetheless, there are numbers of limitations that have to be taken into consideration b~fore this technology can be implemented commercially. Despite all arguments and challenges, the GPRS system is here to stay and evolving towards the third generation mobile communications. This report covers the background of the GPRS and discusses the issues involved in implementing this current technology besides considering the deployment of third generation networks beyond GPRS