Dynamic Service Rate Control for a Single Server Queue with Markov Modulated Arrivals

We consider the problem of service rate control of a single server queueing system with a finite-state Markov-modulated Poisson arrival process. We show that the optimal service rate is non-decreasing in the number of customers in the system; higher congestion rates warrant higher service rates. On the contrary, however, we show that the optimal service rate is not necessarily monotone in the current arrival rate. If the modulating process satisfies a stochastic monotonicity property the monotonicity is recovered. We examine several heuristics and show where heuristics are reasonable substitutes for the optimal control. None of the heuristics perform well in all the regimes. Secondly, we discuss when the Markov-modulated Poisson process with service rate control can act as a heuristic itself to approximate the control of a system with a periodic non-homogeneous Poisson arrival process. Not only is the current model of interest in the control of Internet or mobile networks with bursty traffic, but it is also useful in providing a tractable alternative for the control of service centers with non-stationary arrival rates.Comment: 32 Pages, 7 Figure

Queuing Modelling and Performance Analysis of Content Transfer in Information Centric Networks

With the rapid development of multimedia services and wireless technology, new generation of network traffic like short-form video and live streaming have put tremendous pressure on the current network infrastructure. To meet the high bandwidth and low latency needs of this new generation of traffic, the focus of Internet architecture has moved from host-centric end-to-end communication to requester-driven content retrieval. This shift has motivated the development of Information-Centric Networking (ICN), a promising new paradigm for the future Internet. ICN aims to improve information retrieval on the Internet by identifying and routing data using unified names. In-network caching and the use of a pending interest table (PIT) are two key features of ICN that are designed to efficiently handle bulk data dissemination and retrieval, as well as reduce bandwidth consumption. Performance analysis has been and continues to be key research interests of ICN. This thesis starts with the evaluation of content delivery delays in ICN. The main component of delay is composed of propagation delay, transmission delay,processing delay and queueing delay. To characterize the main components of content delivery delay, queueing network theory has been exploited to coordinate with cache miss rate in modelling the content delivery time in ICN. Moreover, different topologies and network conditions have been taken into account to evaluate the performance of content transfer in ICN. ICN is intrinsically compatible with wireless networks. To evaluate the performance of content transfer in wireless networks, an analytical model to evaluate the mean service time based on consumer and provider mobility has been proposed. The accuracy of the analytical model is validated through extensive simulation experiments. Finally, the analytical model is used to evaluate the impact of key metrics, such as the cache size, content size and content popularity on the performance of PIT and content transfer in ICN. Pending interest table (PIT) is one of the essential components of the ICN forwarding plane, which is responsible for stateful routing in ICN. It also aggregates the same interests to alleviate request flooding and network congestion. The aggregation feature of PIT improves performance of content delivery in ICN. Thus, having an analytical model to characterize the impact of PIT on content delivery time could allow for a more precise evaluation of content transfer performance. In parallel, if the size of the PIT is not properly determined, the interest drop rate may be too high, resulting in a reduction in quality of service for consumers as their requests have to be retransmitted. Furthermore, PIT is a costly resource as it requires to operate at wirespeed in the forwarding plane. Therefore, in order to ensure that interests drop rate less than the requirement, an analytical model of PIT occupancy has been developed to determine the minimum PIT size. In this thesis, the proposed analytical models are used to efficiently and accurately evaluate the performance of ICN content transfer and investigate the key component of ICN forwarding plane. Leveraging the insights discovered by these analytical models, the minimal PIT size and proper interest timeout can be determined to enhance the performance of ICN. To widen the outcomes achieved in the thesis, several interesting yet challenging research directions are pointed out

Performance evaluation of information-centric networking for multimedia services

This is the author accepted manuscript. The final version is available from the publisher via the DOI in this record.The rapid development in multimedia services has shifted the major function of the current Internet from host-centric communication to service-oriented content dissemination. Motivated by this significant change, Information-Centric Networking (ICN) has emerged as a new networking paradigm, which aims at providing natural support for efficient information retrieval over the Internet. As a crucial characteristic of ICN, in-network caching enables users to efficiently access popular content from ubiquitous caches to improve the Quality-of-Experience (QoE). Therefore, in-network caching for ICN has received considerable attention in recent years and many cache schemes and models have been proposed. However, there is a lack of research into ICN cache models under practical environments such as arbitrary topology and multimedia services exhibiting bursty nature. To bridge the gap, this paper proposes a new analytical model to gain valuable insight into the caching performance of ICN with arbitrary topology and bursty content requests. The accuracy of the proposed model is validated by comparing the analytical results with those obtained from simulation experiments. The analytical model is then used as a cost-efficient tool to investigate the impact of key network and content parameters on the performance of caching in ICN

HetHetNets: Heterogeneous Traffic Distribution in Heterogeneous Wireless Cellular Networks

A recent approach in modeling and analysis of the supply and demand in heterogeneous wireless cellular networks has been the use of two independent Poisson point processes (PPPs) for the locations of base stations (BSs) and user equipments (UEs). This popular approach has two major shortcomings. First, although the PPP model may be a fitting one for the BS locations, it is less adequate for the UE locations mainly due to the fact that the model is not adjustable (tunable) to represent the severity of the heterogeneity (non-uniformity) in the UE locations. Besides, the independence assumption between the two PPPs does not capture the often-observed correlation between the UE and BS locations. This paper presents a novel heterogeneous spatial traffic modeling which allows statistical adjustment. Simple and non-parameterized, yet sufficiently accurate, measures for capturing the traffic characteristics in space are introduced. Only two statistical parameters related to the UE distribution, namely, the coefficient of variation (the normalized second-moment), of an appropriately defined inter-UE distance measure, and correlation coefficient (the normalized cross-moment) between UE and BS locations, are adjusted to control the degree of heterogeneity and the bias towards the BS locations, respectively. This model is used in heterogeneous wireless cellular networks (HetNets) to demonstrate the impact of heterogeneous and BS-correlated traffic on the network performance. This network is called HetHetNet since it has two types of heterogeneity: heterogeneity in the infrastructure (supply), and heterogeneity in the spatial traffic distribution (demand).Comment: JSA

Performance modelling with adaptive hidden Markov models and discriminatory processor sharing queues

In modern computer systems, workload varies at different times and locations. It is important to model the performance of such systems via workload models that are both representative and efficient. For example, model-generated workloads represent realistic system behaviour, especially during peak times, when it is crucial to predict and address performance bottlenecks. In this thesis, we model performance, namely throughput and delay, using adaptive models and discrete queues. Hidden Markov models (HMMs) parsimoniously capture the correlation and burstiness of workloads with spatiotemporal characteristics. By adapting the batch training of standard HMMs to incremental learning, online HMMs act as benchmarks on workloads obtained from live systems (i.e. storage systems and financial markets) and reduce time complexity of the Baum-Welch algorithm. Similarly, by extending HMM capabilities to train on multiple traces simultaneously it follows that workloads of different types are modelled in parallel by a multi-input HMM. Typically, the HMM-generated traces verify the throughput and burstiness of the real data. Applications of adaptive HMMs include predicting user behaviour in social networks and performance-energy measurements in smartphone applications. Equally important is measuring system delay through response times. For example, workloads such as Internet traffic arriving at routers are affected by queueing delays. To meet quality of service needs, queueing delays must be minimised and, hence, it is important to model and predict such queueing delays in an efficient and cost-effective manner. Therefore, we propose a class of discrete, processor-sharing queues for approximating queueing delay as response time distributions, which represent service level agreements at specific spatiotemporal levels. We adapt discrete queues to model job arrivals with distributions given by a Markov-modulated Poisson process (MMPP) and served under discriminatory processor-sharing scheduling. Further, we propose a dynamic strategy of service allocation to minimise delays in UDP traffic flows whilst maximising a utility function.Open Acces

Performance Analysis and Optimisation of In-network Caching for Information-Centric Future Internet

The rapid development in wireless technologies and multimedia services has radically shifted the major function of the current Internet from host-centric communication to service-oriented content dissemination, resulting a mismatch between the protocol design and the current usage patterns. Motivated by this significant change, Information-Centric Networking (ICN), which has been attracting ever-increasing attention from the communication networks research community, has emerged as a new clean-slate networking paradigm for future Internet. Through identifying and routing data by unified names, ICN aims at providing natural support for efficient information retrieval over the Internet. As a crucial characteristic of ICN, in-network caching enables users to efficiently access popular contents from on-path routers equipped with ubiquitous caches, leading to the enhancement of the service quality and reduction of network loads. Performance analysis and optimisation has been and continues to be key research interests of ICN. This thesis focuses on the development of efficient and accurate analytical models for the performance evaluation of ICN caching and the design of optimal caching management schemes under practical network configurations. This research starts with the proposition of a new analytical model for caching performance under the bursty multimedia traffic. The bursty characteristic is captured and the closed formulas for cache hit ratio are derived. To investigate the impact of topology and heterogeneous caching parameters on the performance, a comprehensive analytical model is developed to gain valuable insight into the caching performance with heterogeneous cache sizes, service intensity and content distribution under arbitrary topology. The accuracy of the proposed models is validated by comparing the analytical results with those obtained from extensive simulation experiments. The analytical models are then used as cost-efficient tools to investigate the key network and content parameters on the performance of caching in ICN. Bursty traffic and heterogeneous caching features have significant influence on the performance of ICN. Therefore, in order to obtain optimal performance results, a caching resource allocation scheme, which leverages the proposed model and targets at minimising the total traffic within the network and improving hit probability at the nodes, is proposed. The performance results reveal that the caching allocation scheme can achieve better caching performance and network resource utilisation than the default homogeneous and random caching allocation strategy. To attain a thorough understanding of the trade-off between the economic aspect and service quality, a cost-aware Quality-of-Service (QoS) optimisation caching mechanism is further designed aiming for cost-efficiency and QoS guarantee in ICN. A cost model is proposed to take into account installation and operation cost of ICN under a realistic ISP network scenario, and a QoS model is presented to formulate the service delay and delay jitter in the presence of heterogeneous service requirements and general probabilistic caching strategy. Numerical results show the effectiveness of the proposed mechanism in achieving better service quality and lower network cost. In this thesis, the proposed analytical models are used to efficiently and accurately evaluate the performance of ICN and investigate the key performance metrics. Leveraging the insights discovered by the analytical models, the proposed caching management schemes are able to optimise and enhance the performance of ICN. To widen the outcomes achieved in the thesis, several interesting yet challenging research directions are pointed out

Approximation of the two-dimensional output process of a retrial queue with MMPP input

In this paper, we review a retrial queue with MMPP input and two-way communication. Incoming requests arriving at the server and finding it busy join the source of retrial calls and try to enter the server again after some exponentially distributed time. While idle, the server makes outgoing calls and serves them with another delay parameter. MMPP (Markov Modulated Poisson Process) is an input process in which control is driven by a continuous Markov chain. Changing its state entails a change in the intensity of the input process. For this model, we present an asymptotic approximation of the two-dimensional characteristic function under the condition of a long delay of requests in the source of retrial calls. For this approximation, we carried out a numerical experiment, where asymptotic results were compared to computations obtained via simulation

Availability modeling and evaluation of web-based services - A pragmatic approach

Cette thèse porte sur le développement d’une approche de modélisation pragmatique permettant aux concepteurs d’applications et systèmes mis en oeuvre sur le web d’évaluer la disponibilité du service fourni aux utilisateurs. Plusieurs sources d’indisponibilité du service sont prises en compte, en particulier i) les défaillances matérielles ou logicielles affectant les serveurs et ii) des dégradations de performance (surcharge des serveurs, temps de réponse trop long, etc.). Une approche hiérarchique multi-niveau basée sur une modélisation de type performabilité est proposée, combinant des chaînes de Markov et des modèles de files d’attente. Les principaux concepts et la faisabilité de cette approche sont illustrés à travers l’exemple d’une agence de voyage. Plusieurs modèles analytiques et études de sensibilité sont présentés en considérant différentes hypothèses concernant l’architecture, les stratégies de recouvrement, les fautes, les profils d’utilisateurs, et les caractéristiques du trafic. ABSTRACT : This thesis presents a pragmatic modeling approach allowing designers of web-based applications and systems to evaluate the service availability provided to the users. Multiple sources of service unavailability are taken into account, in particular i) hardware and software failures affecting the servers, and ii) performance degradation (overload of servers, very long response time, etc.). An hierarchical multi-level approach is proposed based on performability modeling, combining Markov chains and queueing models. The main concepts and the feasibility of this approach are illustrated using a web-based travel agency. Various analytical models and sensitivity studies are presented considering different assumptions with respect to the architectures, recovery strategies, faults, users profile and traffic characteristics

Traffic modeling in mobile internet protocol : version 6.

Thesis (M.Sc.Eng.)-University of KwaZulu-Natal, Durban, 2005.Mobile Internet Protocol Version 6 (lPv6) is the new version of the Internet Protocol (IP) born out of the great success of Internet Protocol version 4 (IPv4). The motivation behind the development of Mobile IPv6 standard stems from user's demand for mobile devices which can connect and move seamlessly across a growing number of connectivity options. It is both suitable for mobility between subnets across homogenous and inhomogeneous media. The protocol allows a mobile node to communicate with other hosts after changing its point of attachment from one subnet to another. The huge address space available meets the requirements for rapid development of internet as the number of mobile nodes increases tremendously with the rapid expansion of the internet. Mobility, security and quality of service (QoS) being integrated in Mobile TPv6 makes it the important foundation stone for building the mobile information society and the future internet. Convergence between current network technologies: the intern et and mobile telephony is taking place, but the internet's IP routing was designed to work with conventional static nodes. Mobile IPv6 is therefore considered to be one of the key technologies for realizing convergence which enables seamless communication between fixed and mobile access networks. For this reason, there is numerous works in location registrations and mobility management, traffic modeling, QoS, routing procedures etc. To meet the increased demand for mobile telecommunications, traffic modeling is an important step towards understanding and solving performance problems in the future wireless IP networks. Understanding the nature of this traffic, identifying its characteristics and developing appropriate traffic models coupled with appropriate mobility management architectures are of great importance to the traffic engineering and performance evaluation of these networks. It is imperative that the mobility management used keeps providing good performance to mobile users and maintain network load due to signaling and packet delivery as low as possible. To reduce this load, Intemet Engineering Task Force (IETF) proposed a regional mobility management. The load is reduced by allowing local migrations to be handled locally transparent from the Home Agent and the Correspondent Node as the mobile nodes roams freely around the network. This dissertation tackles two major aspects. Firstly, we propose the dynamic regional mobility management (DRMM) architecture with the aim to minimize network load while keeping an optimal number of access routers in the region. The mobility management is dynamic based on the movement and population of the mobile nodes around the network. Most traffic models in telecommunication networks have been based on the exponential Poisson processes. This model unfortunately has been proved to be unsuitable for modeling busty IP traffic. Several approaches to model IP traffic using Markovian processes have been developed using the Batch Markovian Alrival Process (BMAP) by characterizing arrivals as batches of sizes of different distributions. The BMAP is constructed by generalizing batch Poisson processes to allow for non-exponential times between arrivals of batches while maintaining an underlying Markovian structure. The second aspect of this dissertation covers the traffic characterization. We give the analysis of an access router as a single server queue with unlimited waiting space under a non pre-emptive priority queuing discipline. We model the arrival process as a superposition of BMAP processes. We characterize the superimposed arrival processes using the BMAP presentation. We derive the queue length and waiting time for this type of queuing system. Performance of this traffic model is evaluated by obtaining numerical results in terms of queue length and waiting time and its distribution for the high and low priority traffic. We finally present a call admission control scheme that supports QoS