Control of transport dynamics in overlay networks

Transport control is an important factor in the performance of Internet protocols, particularly in the next generation network applications involving computational steering, interactive visualization, instrument control, and transfer of large data sets. The widely deployed Transport Control Protocol is inadequate for these tasks due to its performance drawbacks. The purpose of this dissertation is to conduct a rigorous analytical study on the design and performance of transport protocols, and systematically develop a new class of protocols to overcome the limitations of current methods. Various sources of randomness exist in network performance measurements due to the stochastic nature of network traffic. We propose a new class of transport protocols that explicitly accounts for the randomness based on dynamic stochastic approximation methods. These protocols use congestion window and idle time to dynamically control the source rate to achieve transport objectives. We conduct statistical analyses to determine the main effects of these two control parameters and their interaction effects. The application of stochastic approximation methods enables us to show the analytical stability of the transport protocols and avoid pre-selecting the flow and congestion control parameters. These new protocols are successfully applied to transport control for both goodput stabilization and maximization. The experimental results show the superior performance compared to current methods particularly for Internet applications. To effectively deploy these protocols over the Internet, we develop an overlay network, which resides at the application level to provide data transmission service using User Datagram Protocol. The overlay network, together with the new protocols based on User Datagram Protocol, provides an effective environment for implementing transport control using application-level modules. We also study problems in overlay networks such as path bandwidth estimation and multiple quickest path computation. In wireless networks, most packet losses are caused by physical signal losses and do not necessarily indicate network congestion. Furthermore, the physical link connectivity in ad-hoc networks deployed in unstructured areas is unpredictable. We develop the Connectivity-Through-Time protocols that exploit the node movements to deliver data under dynamic connectivity. We integrate this protocol into overlay networks and present experimental results using network to support a team of mobile robots

Design of false data injection attack on distributed process estimation

Herein, design of false data injection attack on a distributed cyber-physical system is considered. A stochastic process with linear dynamics and Gaussian noise is measured by multiple agent nodes, each equipped with multiple sensors. The agent nodes form a multi-hop network among themselves. Each agent node computes an estimate of the process by using its sensor observation and messages obtained from neighboring nodes, via Kalman-consensus filtering. An external attacker, capable of arbitrarily manipulating the sensor observations of some or all agent nodes, injects errors into those sensor observations. The goal of the attacker is to steer the estimates at the agent nodes as close as possible to a pre-specified value, while respecting a constraint on the attack detection probability. To this end, a constrained optimization problem is formulated to find the optimal parameter values of a certain class of linear attacks. The parameters of linear attack are learnt on-line via a combination of stochastic approximation based update of a Lagrange multiplier, and an optimization technique involving either the Karush-Kuhn-Tucker (KKT) conditions or online stochastic gradient descent. The problem turns out to be convex for some special cases. Desired convergence of the proposed algorithms are proved by exploiting the convexity and properties of stochastic approximation algorithms. Finally, numerical results demonstrate the efficacy of the attack

Secure Estimation in V2X Networks with Injection and Packet Drop Attacks

Vehicle-to-anything (V2X) communications are essential for facilitating cooperative intelligent transport system (C-ITS) components such as traffic safety and traffic efficiency applications. Integral to proper functioning of C-ITS systems is sensing and telemetery. To this end, this paper examines how to ensure security in sensing systems for V2X networks. In particular, secure remote estimation of a Gauss-Markov process based on measurements done by a set of vehicles is considered. The measurements are collected by the individual vehicles and are communicated via wireless links to the central fusion center. The system is attacked by malicious or compromised vehicles with the goal of increasing the estimation error. The attack is achieved by two mechanisms: false data injection (FDI) and garbage packet injection. This paper extends a previously proposed adaptive filtering algorithm for tackling FDI to accommodate both FDI and garbage packet injection, by filtering out malicious observations and thus enabling secure estimates. The efficacy of the proposed filter is demonstrated numerically

Designing Robust Collaborative Services in Distributed Wireless Networks

Wireless Sensor Networks (WSNs) are a popular class of distributed collaborative networks finding suitability from medical to military applications. However, their vulnerability to capture, their "open" wireless interfaces, limited battery life, all result in potential vulnerabilities. WSN-based services inherit these vulnerabilities. We focus on tactical environments where sensor nodes play complex roles in data sensing, aggregation and decision making. Services in such environments demand a high level of reliability and robustness. The first problem we studied is robust target localization. Location information is important for surveillance, monitoring, secure routing, intrusion detection, on-demand services etc. Target localization means tracing the path of moving entities through some known surveillance area. In a tactical environment, an adversary can often capture nodes and supply incorrect surveillance data to the system. In this thesis we create a target localization protocol that is robust against large amounts of such falsified data. Location estimates are generated by a Bayesian maximum-likelihood estimator. In order to achieve improved results with respect to fraudulent data attacks, we introduce various protection mechanisms. Further, our novel approach of employing watchdog nodes improves our ability to detect anomalies reducing the impact of an adversarial attack and limiting the amount of falsified data that gets accepted into the system. By concealing and altering the location where data is aggregated, we restrict the adversary to making probabilistic "guess" attacks at best, and increase robustness further. By formulating the problem of robust node localization under adversarial settings and casting it as a multivariate optimization problem, we solve for the system design parameters that correspond to the optimal solution. Together this results in a highly robust protocol design. In order for any collaboration to succeed, collaborating entities must have the same relative sense of time. This ensures that any measurements, surveillance data, mission commands, etc will be processed in the same epoch they are intended to serve. In most cases, data disseminated in a WSN is transient in nature, and applies for a short period of time. New data routinely replaces old data. It is imperative that data be placed in its correct time context; therefore..

Reliable multimedia transmission over wireless sensor network

Nowadays, video streaming application is widely used in wired as well as wireless environment. Extending this application into Wireless Sensor Networks (WSN) for IEEE 802.15.4 network has attracted lots of attention in the research community. Reliable data transmission is one of the most important requirements in WSN especially for multimedia application. Moreover, multimedia application requires high bandwidth and consumes large memory size in order to send video data that requires small end-to-end (ETE) delay. To overcome this problem, rate control serves as an important technique to control the bit rate of encoded video for transmission over a channel of limited bandwidth and low data rate which is 250kbps with small Maximum Transmission Unit (MTU) size of 127 bytes. Therefore, a rate control model called enhanced Video Motion Classification based (e-ViMoC) model using an optimal combination of parameter setting is proposed in this thesis. Another challenging task to maintain the video quality is the design of an enhanced transport protocol. Standard transport protocols cannot be directly applied in WSN specifically, but some modifications are required. Therefore, to achieve high reliability of video transmission, the advantages of User Datagram Protocol (UDP) features are applied to the proposed transport protocol called Lightweight Reliable Transport Protocol (LRTP) to tailor to the low data rate requirement of WSN. Besides, priority queue scheme is adopted to reduce the end-to-end delay while maintaining the reliability and energy efficiency. Evalvid simulation tool and exhaustive search method are used to determine optimal combination of quantization scale (q), frame rate (r) and Group of Picture (GOP) size (l) values to control the bit rate at the video encoder. The model of e-ViMoC is verified both with simulation and experimental work. The proposed transport protocol has been successfully studied and verified through simulation using Network Simulator 2 (NS-2). From the simulation results, the proposed e-ViMoC encoded video enhances the Packet Delivery Ratio (PDR) by 5.14%, reduces the energy consumed by 16.37%, improves the Peak Signal to Noise Ratio (PSNR) by 4.37% and reduces the ETE delay by 23.69% in average, compared to non-optimized encoded video. The tested experiment experiences slightly different result where the PDR is 6% lower than simulation results. Meanwhile, the combination of e-ViMoC and LRTP outperforms the standard transport protocol by average improvement of 142.9% for PDR, average reduction of 8.87% for energy consumption, average improvement of 4.1% for PSNR, and average reduction of 19.38% for ETE delay. Thus, the simulation results show that the combination of proposed e-ViMoC and LRTP provides better reliability performance in terms of the PDR while simultaneously improves the energy efficiency, the video quality and ETE delay

SimMobility Short-Term: An Integrated Microscopic Mobility Simulator

This paper presents the development of an integrated microscopic mobility simulator, SimMobility Short-Term (ST). The simulator is integrated because its models, inputs and outputs, simulated components, and code base are integrated within a multiscale agent- and activity-based simu- lation platform capable of simulating different spatiotemporal resolutions and accounting for different levels of travelers’ decision making. The simulator is microscopic because both the demand (agents and its trips) and the supply (trip realization and movements on the network) are microscopic (i.e., modeled individually). Finally, the simulator has mobility because it copes with the multimodal nature of urban networks and the need for the flexible simulation of innovative transportation ser - vices, such as on-demand and smart mobility solutions. This paper follows previous publications that describe SimMobility’s overall framework and models. SimMobility is an open-source, multiscale platform that considers land use, transportation, and mobility-sensitive behavioral models. SimMobility ST aims at simulating the high-resolution movement of agents (traffic, transit, pedestrians, and goods) and the operation of different mobility services and control and information systems. This paper presents the SimMobility ST modeling framework and system architecture and reports on its successful calibration for Singapore and its use in several scenarios of innovative mobility applications. The paper also shows how detailed performance measures from SimMobility ST can be integrated with a daily activity and mobility patterns simulator. Such integration is crucial to model accurately the effect of different technologies and service operations at the urban level, as the identity and preferences of simulated agents are maintained across temporal decision scales, ensuring the consistency and accuracy of simulated accessibility and performance measures of each scenario.Singapore. National Research Foundation (CREATE program)Singapore-MIT Alliance. Center. Future Urban Mobility Interdisciplinary Research Grou