Robust Mobile Data Transport: Modeling, Measurements, and Implementation

Advances in wireless technologies and the pervasive influence of multi-homed devices have significantly changed the way people use the Internet. These changes of user behavior and the evolution of multi-homing technologies have brought a huge impact to today\u27s network study and provided new opportunities to improve mobile data transport. In this thesis, we investigate challenges related to human mobility, with emphases on network performance at both system level and user level. More specifically, we seek to answer the following two questions: 1) How to model user mobility in the networks and use the model for network provisioning? 2) Is it possible to utilize network diversity to provide robust data transport in wireless environments? We first study user mobility in a large scale wireless network. We propose a mixed queueing model of mobility and show that this model can accurately predict both system-level and user-level performance metrics. Furthermore, we demonstrate how this model can be used for network dimensioning. Secondly, with the increasing demand of multi-homed devices that interact with heterogeneous networks such as WiFi and cellular 3G/4G, we explore how to leverage this path diversity to assist data transport. We investigate the technique of multi-path TCP (MPTCP) and evaluate how MPTCP performs in the wild through extensive measurements in various wireless environments using WiFi and cellular 3G/4G simultaneously. We study the download latencies of MPTCP when using different congestion controllers and number of paths under various traffic loads and over different cellular carriers. We further study the impact of short flows on MPTCP by modeling MPTCP\u27s delay startup mechanism of additional flows. As flow sizes increase, we observe that traffic in cellular networks exhibits large and varying packet round trip times, called bufferbloat. We analyze the phenomenon of bufferbloat, and illustrate how bufferbloat can result in numerous MPTCP performance issues. We provide an effective solution to mitigate the performance degradation. Finally, as popular content is replicated at multiple locations, we develop mechanisms that take advantage of this source diversity along with path diversity to provide robust mobile data transport. We demonstrate this in the context of online video streaming, because of its popularity and significant contribution to Internet traffic. We therefore propose MSPlayer, a client-based solution for online video streaming that adjusts network traffic distribution over each path to network dynamics. MSPlayer bypasses the deployment limitations of MPTCP while maintaining the benefits of path diversity, and exploits different content sources simultaneously. MSPlayer can significantly reduce video start-up latency and quickly refill playout buffer for high quality video streaming. We evaluate MSPlayer\u27s performance through YouTube

Fast network configuration in Software Defined Networking

Software Defined Networking (SDN) provides a framework to dynamically adjust and re-program the data plane with the use of flow rules. The realization of highly adaptive SDNs with the ability to respond to changing demands or recover after a network failure in a short period of time, hinges on efficient updates of flow rules. We model the time to deploy a set of flow rules by the update time at the bottleneck switch, and formulate the problem of selecting paths to minimize the deployment time under feasibility constraints as a mixed integer linear program (MILP). To reduce the computation time of determining flow rules, we propose efficient heuristics designed to approximate the minimum-deployment-time solution by relaxing the MILP or selecting the paths sequentially. Through extensive simulations we show that our algorithms outperform current, shortest path based solutions by reducing the total network configuration time up to 55% while having similar packet loss, in the considered scenarios. We also demonstrate that in a networked environment with a certain fraction of failed links, our algorithms are able to reduce the average time to reestablish disrupted flows by 40%

Exploring intelligent service migration in a highly mobile network

Mobile services allow services to be migrated or replicated closer to users as they move around. This is now regarded as a viable mechanism to provide good Quality of Service to users in highly mobile environments such as vehicular networks. The vehicular environment is rapidly becoming a significant part of the internet and this presents various challenges that must be addressed; this is due to continuous handovers as mobile devices change their point of attachment to these networks resulting in a loss of service. Therefore, this explains the need to build a framework for intelligent service migration. This thesis addresses these issues. It starts by discussing the requirements for intelligent service migration. Then it investigates a low latency Quality of Service Aware Framework as well as an experimental transport protocol that would be favoured by vehicular networks. Furthermore, two analytical models are developed using the Zero-Server Markov Chain technique which is a way of analysing scenarios when the server is not continuously available to serve. Using the Zero-Server Markov Chain, the first analytical model looks at lost service due to continuous handovers and the communication dynamics of vehicular networks, while the second model analyses how service migration affects service delivery in these networks. Formulas are developed to yield the average number of packets in the system, the response time, the probability of blocking and a new parameter called the probability of lost service. These formulas are then applied to the Middlesex VANET Testbed to look at reactive and proactive service migration. These techniques are then incorporated into a new Service Management Framework to provide sustainable Quality of Service and Quality of Experience to mobile users in vehicular networks. This thesis also shows that this new approach is better than current approaches as it addresses key issues in intelligent service migration in such environments, and hence can play a significant part in the development of Intelligent Transport Systems for Smart Cities

A New CAC Policy Based on Traffic Characterization in Cellular Networks

The Call Admission Control (CAC) method presented in this paper is based on the statistical properties of the network’s traffic variables. It probabilistically estimates the time until the release of a seized channel: the admission control depends on the computed mean remaining time averaged along all channels at a specific instant and on a time threshold. The policy produces a smooth transition between the QoS metrics, giving the operator the freedom to design the network at the desired QoS point. Another valuable property is that the algorithm is straightforward and fed only by simple teletraffic metrics: distribution and the first and second moments of Channel Holding Time (CHT). Simplicity is important for a CAC method because decisions for accepting or rejecting calls must be computed quickly and frequently.Peer Reviewe

Performance Modelling and Resource Allocation of the Emerging Network Architectures for Future Internet

With the rapid development of information and communications technologies, the traditional network architecture has approached to its performance limit, and thus is unable to meet the requirements of various resource-hungry applications. Significant infrastructure improvements to the network domain are urgently needed to guarantee the continuous network evolution and innovation. To address this important challenge, tremendous research efforts have been made to foster the evolution to Future Internet. Long-term Evolution Advanced (LTE-A), Software Defined Networking (SDN) and Network Function Virtualisation (NFV) have been proposed as the key promising network architectures for Future Internet and attract significant attentions in the network and telecom community. This research mainly focuses on the performance modelling and resource allocations of these three architectures. The major contributions are three-fold: 1) LTE-A has been proposed by the 3rd Generation Partnership Project (3GPP) as a promising candidate for the evolution of LTE wireless communication. One of the major features of LTE-A is the concept of Carrier Aggregation (CA). CA enables the network operators to exploit the fragmented spectrum and increase the peak transmission data rate, however, this technical innovation introduces serious unbalanced loads among in the radio resource allocation of LTE-A. To alleviate this problem, a novel QoS-aware resource allocation scheme, termed as Cross-CC User Migration (CUM) scheme, is proposed in this research to support real-time services, taking into consideration the system throughput, user fairness and QoS constraints. 2) SDN is an emerging technology towards next-generation Internet. In order to improve the performance of the SDN network, a preemption-based packet-scheduling scheme is firstly proposed in this research to improve the global fairness and reduce the packet loss rate in SDN data plane. Furthermore, in order to achieve a comprehensive and deeper understanding of the performance behaviour of SDN network, this work develops two analytical models to investigate the performance of SDN in the presence of Poisson Process and Markov Modulated Poisson Process (MMPP) respectively. 3) NFV is regarded as a disruptive technology for telecommunication service providers to reduce the Capital Expenditure (CAPEX) and Operational Expenditure (OPEX) through decoupling individual network functions from the underlying hardware devices. While NFV faces a significant challenging problem of Service-Level-Agreement (SLA) guarantee during service provisioning. In order to bridge this gap, a novel comprehensive analytical model based on stochastic network calculus is proposed in this research to investigate end-to-end performance of NFV network. The resource allocation strategies proposed in this study significantly improve the network performance in terms of packet loss probability, global allocation fairness and throughput per user in LTE-A and SDN networks; the analytical models designed in this study can accurately predict the network performances of SDN and NFV networks. Both theoretical analysis and simulation experiments are conducted to demonstrate the effectiveness of the proposed algorithms and the accuracy of the designed models. In addition, the models are used as practical and cost-effective tools to pinpoint the performance bottlenecks of SDN and NFV networks under various network conditions

A Comprehensive Survey of the Tactile Internet: State of the art and Research Directions

The Internet has made several giant leaps over the years, from a fixed to a mobile Internet, then to the Internet of Things, and now to a Tactile Internet. The Tactile Internet goes far beyond data, audio and video delivery over fixed and mobile networks, and even beyond allowing communication and collaboration among things. It is expected to enable haptic communication and allow skill set delivery over networks. Some examples of potential applications are tele-surgery, vehicle fleets, augmented reality and industrial process automation. Several papers already cover many of the Tactile Internet-related concepts and technologies, such as haptic codecs, applications, and supporting technologies. However, none of them offers a comprehensive survey of the Tactile Internet, including its architectures and algorithms. Furthermore, none of them provides a systematic and critical review of the existing solutions. To address these lacunae, we provide a comprehensive survey of the architectures and algorithms proposed to date for the Tactile Internet. In addition, we critically review them using a well-defined set of requirements and discuss some of the lessons learned as well as the most promising research directions