RoadRunner: Infrastructure-less vehicular congestion control

RoadRunner is an in-vehicle app for traffic congestion control without costly roadside infrastructure, instead judiciously harnessing vehicle-to-vehicle communications, cellular connectivity, and onboard computation and sensing to enable large-scale traffic congestion control at higher penetration and finer granularity than previously possible. RoadRunner limits the number of vehicles in a congested region or road by requiring each to possess a token for entry. Tokens can circulate and be reused among multiple vehicles as vehicles move between regions. We built RoadRunner as an Android app utilizing LTE, 802.11p, and 802.11n radios, deployed it on 10 vehicles, and measured cellular access reductions of up to 84% and response time improvements of up to 80%. In a microscopic agent-based traffic simulator, RoadRunner achieved travel speed improvements of up to 7.7% over an industry-strength electronic road pricing system.Singapore-MIT Alliance for Research and TechnologyAmerican Society for Engineering Education. National Defense Science and Engineering Graduate Fellowshi

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

Quality of service differentiation for multimedia delivery in wireless LANs

Delivering multimedia content to heterogeneous devices over a variable networking environment while maintaining high quality levels involves many technical challenges. The research reported in this thesis presents a solution for Quality of Service (QoS)-based service differentiation when delivering multimedia content over the wireless LANs. This thesis has three major contributions outlined below: 1. A Model-based Bandwidth Estimation algorithm (MBE), which estimates the available bandwidth based on novel TCP and UDP throughput models over IEEE 802.11 WLANs. MBE has been modelled, implemented, and tested through simulations and real life testing. In comparison with other bandwidth estimation techniques, MBE shows better performance in terms of error rate, overhead, and loss. 2. An intelligent Prioritized Adaptive Scheme (iPAS), which provides QoS service differentiation for multimedia delivery in wireless networks. iPAS assigns dynamic priorities to various streams and determines their bandwidth share by employing a probabilistic approach-which makes use of stereotypes. The total bandwidth to be allocated is estimated using MBE. The priority level of individual stream is variable and dependent on stream-related characteristics and delivery QoS parameters. iPAS can be deployed seamlessly over the original IEEE 802.11 protocols and can be included in the IEEE 802.21 framework in order to optimize the control signal communication. iPAS has been modelled, implemented, and evaluated via simulations. The results demonstrate that iPAS achieves better performance than the equal channel access mechanism over IEEE 802.11 DCF and a service differentiation scheme on top of IEEE 802.11e EDCA, in terms of fairness, throughput, delay, loss, and estimated PSNR. Additionally, both objective and subjective video quality assessment have been performed using a prototype system. 3. A QoS-based Downlink/Uplink Fairness Scheme, which uses the stereotypes-based structure to balance the QoS parameters (i.e. throughput, delay, and loss) between downlink and uplink VoIP traffic. The proposed scheme has been modelled and tested through simulations. The results show that, in comparison with other downlink/uplink fairness-oriented solutions, the proposed scheme performs better in terms of VoIP capacity and fairness level between downlink and uplink traffic

Master of Science

thesisCurrent solutions for switching between cellular networks and WiFi, such as those provided by Google and Samsung, do not work well in many scenarios. For example, a Samsung Galaxy S4 smartphone connected to a WiFi network remains in the WiFi mode for more than 5 minutes, even when the Internet connectivity beyond the first hop is unavailable. Therefore, there is a strong need for an efficient and automated switching mechanism between WiFi and cellular networks that has wide applicability. We design an adaptive, energy-efficient methodology to switch between WiFi and cellular networks to provide robust Internet connectivity. When using a WiFi network, we utilize a combination of active and passive monitoring techniques to detect unavailability of Internet connectivity via WiFi. When using the cellular network, we design two algorithms, namely the dormant probing algorithm, and a variable heartbeat probing algorithm, to detect the availability of Internet connectivity via WiFi. We implement the algorithms and mechanisms we design on smartphones. We also implement the capability of simultaneously accessing WiFi and cellular networks on smartphones. We evaluate our design and implementation using an Internet availability simulator which is based on a two-state continuous time Markov chain. Our experimental results show that we are able to detect unavailability of Internet connectivity beyond the first hop when using WiFi and switch to the cellular network fairly quickly. Furthermore, with the variable heartbeat algorithm, we are able to switch back to WiFi within 60 seconds of Internet connectivity becoming available, 90% of the time, with minimal probing overhead

Mobile Networks

The growth in the use of mobile networks has come mainly with the third generation systems and voice traffic. With the current third generation and the arrival of the 4G, the number of mobile users in the world will exceed the number of landlines users. Audio and video streaming have had a significant increase, parallel to the requirements of bandwidth and quality of service demanded by those applications. Mobile networks require that the applications and protocols that have worked successfully in fixed networks can be used with the same level of quality in mobile scenarios. Until the third generation of mobile networks, the need to ensure reliable handovers was still an important issue. On the eve of a new generation of access networks (4G) and increased connectivity between networks of different characteristics commonly called hybrid (satellite, ad-hoc, sensors, wired, WIMAX, LAN, etc.), it is necessary to transfer mechanisms of mobility to future generations of networks. In order to achieve this, it is essential to carry out a comprehensive evaluation of the performance of current protocols and the diverse topologies to suit the new mobility conditions

Performance analysis of mobile networks under signalling storms

There are numerous security challenges in cellular mobile networks, many of which originate from the Internet world. One of these challenges is to answer the problem with increasing rate of signalling messages produced by smart devices. In particular, many services in the Internet are provided through mobile applications in an unobstructed manner, such that users get an always connected feeling. These services, which usually come from instant messaging, advertising and social networking areas, impose significant signalling loads on mobile networks by frequent exchange of control data in the background. Such services and applications could be built intentionally or unintentionally, and result in denial of service attacks known as signalling attacks or storms. Negative consequences, among others, include degradations of mobile network’s services, partial or complete net- work failures, increased battery consumption for infected mobile terminals. This thesis examines the influence of signalling storms on different mobile technologies, and proposes defensive mechanisms. More specifically, using stochastic modelling techniques, this thesis first presents a model of the vulnerability in a single 3G UMTS mobile terminal, and studies the influence of the system’s internal parameters on stability under a signalling storm. Further on, it presents a queueing network model of the radio access part of 3G UMTS and examines the effect of the radio resource control (RRC) inactivity timers. In presence of an attack, the proposed dynamic setting of the timers manage to lower the signalling load in the network and to increase the threshold above which a network failure could happen. Further on, the network model is upgraded into a more generic and detailed model, represent different generations of mobile technologies. It is than used to compare technologies with dedicated and shared organisation of resource allocation, referred to as traditional and contemporary networks, using performance metrics such as: signalling and communication delay, blocking probability, signalling load on the network’s nodes, bandwidth holding time, etc. Finally, based on the carried analysis, two mechanisms are proposed for detection of storms in real time, based on counting of same-type bandwidth allocations, and usage of allocated bandwidth. The mechanisms are evaluated using discrete event simulation in 3G UMTS, and experiments are done combining the detectors with a simple attack mitigation approach.Open Acces

Toward Open and Programmable Wireless Network Edge

Increasingly, the last hop connecting users to their enterprise and home networks is wireless. Wireless is becoming ubiquitous not only in homes and enterprises but in public venues such as coffee shops, hospitals, and airports. However, most of the publicly and privately available wireless networks are proprietary and closed in operation. Also, there is little effort from industries to move forward on a path to greater openness for the requirement of innovation. Therefore, we believe it is the domain of university researchers to enable innovation through openness. In this thesis work, we introduce and defines the importance of open framework in addressing the complexity of the wireless network. The Software Defined Network (SDN) framework has emerged as a popular solution for the data center network. However, the promise of the SDN framework is to make the network open, flexible and programmable. In order to deliver on the promise, SDN must work for all users and across all networks, both wired and wireless. Therefore, we proposed to create new modules and APIs to extend the standard SDN framework all the way to the end-devices (i.e., mobile devices, APs). Thus, we want to provide an extensible and programmable abstraction of the wireless network as part of the current SDN-based solution. In this thesis work, we design and develop a framework, weSDN (wireless extension of SDN), that extends the SDN control capability all the way to the end devices to support client-network interaction capabilities and new services. weSDN enables the control-plane of wireless networks to be extended to mobile devices and allows for top-level decisions to be made from an SDN controller with knowledge of the network as a whole, rather than device centric configurations. In addition, weSDN easily obtains user application information, as well as the ability to monitor and control application flows dynamically. Based on the weSDN framework, we demonstrate new services such as application-aware traffic management, WLAN virtualization, and security management

Transport Architectures for an Evolving Internet

In the Internet architecture, transport protocols are the glue between an application’s needs and the network’s abilities. But as the Internet has evolved over the last 30 years, the implicit assumptions of these protocols have held less and less well. This can cause poor performance on newer networks—cellular networks, datacenters—and makes it challenging to roll out networking technologies that break markedly with the past. Working with collaborators at MIT, I have built two systems that explore an objective-driven, computer-generated approach to protocol design. My thesis is that making protocols a function of stated assumptions and objectives can improve application performance and free network technologies to evolve. Sprout, a transport protocol designed for videoconferencing over cellular networks, uses probabilistic inference to forecast network congestion in advance. On commercial cellular networks, Sprout gives 2-to-4 times the throughput and 7-to-9 times less delay than Skype, Apple Facetime, and Google Hangouts. This work led to Remy, a tool that programmatically generates protocols for an uncertain multi-agent network. Remy’s computer-generated algorithms can achieve higher performance and greater fairness than some sophisticated human-designed schemes, including ones that put intelligence inside the network. The Remy tool can then be used to probe the difficulty of the congestion control problem itself—how easy is it to “learn” a network protocol to achieve desired goals, given a necessarily imperfect model of the networks where it ultimately will be deployed? We found weak evidence of a tradeoff between the breadth of the operating range of a computer-generated protocol and its performance, but also that a single computer-generated protocol was able to outperform existing schemes over a thousand-fold range of link rates