http://smartech.gatech.edu/handle/1853/5978 Original work by students of College of Computing Search the Channel search http://smartech.gatech.edu/simple-search http://smartech.gatech.edu/handle/1853/22688 Title: End-to-end Available Bandwidth Estimation and its Applications <br/> <br/>Authors: Jain, Manish <br/> <br/>Abstract: As the Internet continues to evolve, without providing any performance guarantees or explicit feedback to applications, the only way to infer the state of the network and to dynamically react to congestion is through end-to-end measurements. The emph{available bandwidth} (avail-bw) is an important metric that characterizes the dynamic state of a network path. Its measurement has been the focus of significant research during the last 15 years. However, its estimation remained elusive for several reasons. The main contribution of this thesis is the development of the first estimation methodology for the avail-bw in a network path using end-to-end measurements. In more detail, our first contribution is an end-to-end methodology, called SLoPS, to determine whether the avail-bw is larger than a given rate based on the sequence of one-way delays experienced by a periodic packet stream. The second contribution is the design of two algorithms, based on SLoPS, to estimate the mean and the variation range, respectively, of the avail-bw process. These algorithms have been implemented in two measurement tools, referred to as PathLoad and PathVar. We have validated the accuracy of the tools using analysis, simulation, and extensive experimentation. Pathload has been downloaded by more than 6000 users since 2003. We have also used PathVar to study the variability of the avail-bw process as a function of various important factors, including traffic load and degree of multiplexing. Finally, we present an application of avail-bw estimation in video streaming. Specifically, we show that avail-bw measurements can be used in the dynamic selection of the best possible overlay path. The proposed scheme results in better perceived video quality than path selection algorithms that rely on jitter or loss-rate measurements. http://smartech.gatech.edu/handle/1853/22677 Title: Virtualization Services: Scalable Methods for Virtualizing Multicore Systems <br/> <br/>Authors: Raj, Himanshu <br/> <br/>Abstract: Multi-core technology is bringing parallel processing capabilities from servers to laptops and even handheld devices. At the same time, platform support for system virtualization is making it easier to consolidate server and client resources, when and as needed by applications. This consolidation is achieved by dynamically mapping the virtual machines on which applications run to underlying physical machines and their processing cores. Low cost processor and I/O virtualization methods efficiently scaled to different numbers of processing cores and I/O devices are key enablers of such consolidation. This dissertation develops and evaluates new methods for scaling virtualization functionality to multi-core and future many-core systems. Specifically, it re-architects virtualization functionality to improve scalability and better exploit multi-core system resources. Results from this work include a self-virtualized I/O abstraction, which virtualizes I/O so as to flexibly use different platforms' processing and I/O resources. Flexibility affords improved performance and resource usage and most importantly, better scalability than that offered by current I/O virtualization solutions. Further, by describing system virtualization as a service provided to virtual machines and the underlying computing platform, this service can be enhanced to provide new and innovative functionality. For example, a virtual device may provide obfuscated data to guest operating systems to maintain data privacy; it could mask differences in device APIs or properties to deal with heterogeneous underlying resources; or it could control access to data based on the ``trust' properties of the guest VM. This thesis demonstrates that extended virtualization services are superior to existing operating system or user-level implementations of such functionality, for multiple reasons. First, this solution technique makes more efficient use of key performance-limiting resource in multi-core systems, which are memory and I/O bandwidth. Second, this solution technique better exploits the parallelism inherent in multi-core architectures and exhibits good scalability properties, in part because at the hypervisor level, there is greater control in precisely which and how resources are used to realize extended virtualization services. Improved control over resource usage makes it possible to provide value-added functionalities for both guest VMs and the platform. Specific instances of virtualization services described in this thesis are the network virtualization service that exploits heterogeneous processing cores, a storage virtualization service that provides location transparent access to block devices by extending the functionality provided by network virtualization service, a multimedia virtualization service that allows efficient media device sharing based on semantic information, and an object-based storage service with enhanced access control. http://smartech.gatech.edu/handle/1853/22662 Title: ROSENET: A Remote Server-based Network Emulation System <br/> <br/>Authors: Gu, Yan <br/> <br/>Abstract: Network emulation has been widely used to aid in the development and evaluation of real-time applications. Many of today s applications and protocols need to be tested and evaluated in large scale network environments such as the Internet, which requires emulation tools that meet the requirements of scale, accuracy, timeliness. Due to physical resource constraints in network emulators, existing emulation tools fail to meet these requirements as they are either limited to small and static networks, use simplified network models, or fail to deliver timely emulation results. If more physical resources are devoted to network emulation by utilizing high performance computing facilities, the accuracy and scalability of network emulation can be greatly improved. However, for many users, high performance computing facilities may not be readily available in a local laboratory environment, and co-locating application code with a remote high performance computing facility may be cumbersome and inconvenient. This thesis proposes a network emulation approach called ROSENET (RemOte SErver-based Network EmulaTion) that utilizes a distributed server-based architecture in which local low-fidelity emulators provide real-time QoS predictions to distributed applications, coupled with a remote large scale high-fidelity simulator that continuously updates and calibrates the local low-fidelity emulators. A library-based modeling approach based on online simulation data collection is proposed and a system identification modeling technique is presented. Experimental results examining emulation end-to-end delay and loss show that ROSENET provides a promising approach to network emulation supporting accuracy and scale while meeting real-time constraints. Challenges faced in applying ROSENET to real world applications are addressed through two case studies including applying synthetic workload on DARPA s NMS network topology for large scale network simulation and a contemporary real-time distributed VoIP application Skype. http://smartech.gatech.edu/handle/1853/22643 Title: Probabilistic Topological Maps <br/> <br/>Authors: Ranganathan, Ananth <br/> <br/>Abstract: Topological maps are light-weight, graphical representations of environments that are scalable and amenable to symbolic manipulation. Thus, they are well- suited for basic robot navigation applications, and also provide a representational basis for the procedural and semantic information needed for higher-level robotic tasks. However, their widespread use has been impeded in part by the lack of reliable, general purpose algorithms for their construction. In this dissertation, I present a probabilistic framework for the construction of topological maps that addresses topological ambiguity, is failure-aware, computa- tionally efficient, and can incorporate information from various sensing modalities. The framework addresses the two major problems of topological mapping, namely topological ambiguity and landmark detection. The underlying idea behind overcoming topological ambiguity is that the com- putation of the Bayesian posterior distribution over the space of topologies is an effective means of quantifying this ambiguity, caused due to perceptual aliasing and environment variability. Since the space of topologies is combinatorial, the posterior on it cannot be computed exactly. Instead, I introduce the concept of Probabilistic Topological Maps (PTMs), a sample-based representation that ap- proximates the posterior distribution over topologies given the available sensor measurements. Sampling algorithms for the efficient computation of PTMs are described. The PTM framework can be used with a wide variety of landmark detection schemes under mild assumptions. As part of the evaluation, I describe a novel landmark detection technique that makes use of the notion of "surprise" in mea- surements that the robot obtains, the underlying assumption being that landmarks are places in the environment that generate surprising measurements. The com- putation of surprise in a Bayesian framework is described and applied to various sensing modalities for the computation of PTMs. The PTM framework is the first instance of a probabilistic technique for topo- logical mapping that is systematic and comprehensive. It is especially relevant for future robotic applications which will need a sparse representation capable of accomodating higher level semantic knowledge. Results from experiments in real environments demonstrate that the framework can accomodate diverse sensors such as camera rigs and laser scanners in addition to odometry. Finally, results are pre- sented using various landmark detection schemes besides the surprise-based one.