Network-provider-independent overlays for resilience and quality of service.

PhDOverlay networks are viewed as one of the solutions addressing the inefficiency and slow evolution of the Internet and have been the subject of significant research. Most existing overlays providing resilience and/or Quality of Service (QoS) need cooperation among different network providers, but an inter-trust issue arises and cannot be easily solved. In this thesis, we mainly focus on network-provider-independent overlays and investigate their performance in providing two different types of service. Specifically, this thesis addresses the following problems: Provider-independent overlay architecture: A provider-independent overlay framework named Resilient Overlay for Mission-Critical Applications (ROMCA) is proposed. We elaborate its structure including component composition and functions and also provide several operational examples. Overlay topology construction for providing resilience service: We investigate the topology design problem of provider-independent overlays aiming to provide resilience service. To be more specific, based on the ROMCA framework, we formulate this problem mathematically and prove its NP-hardness. Three heuristics are proposed and extensive simulations are carried out to verify their effectiveness. Application mapping with resilience and QoS guarantees: Assuming application mapping is the targeted service for ROMCA, we formulate this problem as an Integer Linear Program (ILP). Moreover, a simple but effective heuristic is proposed to address this issue in a time-efficient manner. Simulations with both synthetic and real networks prove the superiority of both solutions over existing ones. Substrate topology information availability and the impact of its accuracy on overlay performance: Based on our survey that summarizes the methodologies available for inferring the selective substrate topology formed among a group of nodes through active probing, we find that such information is usually inaccurate and additional mechanisms are needed to secure a better inferred topology. Therefore, we examine the impact of inferred substrate topology accuracy on overlay performance given only inferred substrate topology information

Quality of service (QoS) support for multimedia applications in large-scale networks

This dissertation studied issues pertaining to QoS provision for multimedia applications at the application layer. We initially studied Internet routing pathology and Internet routing stability by repeating experimental and analytical methods conducted by Paxson in 1996. No similar study was done in recent years. Our findings show that routing behavior of the Internet in 2006 are different from those reported in 1996 in some important aspects. Second, we investigated different stochastic models (e.g. self-similar processes, Auto-Regressive Integrated Moving-Average (ARIMA)) in order to find a suitable model that describes available bandwidth over time of an end-to-end path between two Internet hosts. Our finding of the suitable model is beneficial to predicting of future values of available bandwidth along an end-to-end path. To the best of our knowledge, no similar study was conducted. Third, we designed and evaluated a new path monitoring algorithm inferring available bandwidth of an end-to-end path without monitoring all the paths to minimize monitoring overhead. Our algorithm does not rely on underlying network-layer topology information as required in topology-aware path monitoring techniques. Finally, to complement the above study, we introduced our multicast protocol named core-set routing for transmitting multimedia data from a set of senders to a set of receivers, taking QoS into account. The protocol is suitable for interactive multi-sender multimedia applications such as video conferencing and network gaming

A measurement-based approach to service modeling and bandwidth estimation in IEEE 802.11 wireless networks

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Packet level measurement over wireless access

PhDPerformance Measurement of the IP packet networks mainly comprise of monitoring the network performance in terms of packet losses and delays. If used appropriately, these network parameters (i.e. delay, loss and bandwidth etc) can indicate the performance status of the network and they can be used in fault and performance monitoring, network provisioning, and traffic engineering. Globally, there is a growing need for accurate network measurement to support the commercial use of IP networks. In wireless networks, transmission losses and communication delays strongly affect the performance of the network. Compared to wired networks, wireless networks experience higher levels of data dropouts, and corruption due to issues of channel fading, noise, interference and mobility. Performance monitoring is a vital element in the commercial future of broadband packet networking and the ability to guarantee quality of service in such networks is implicit in Service Level Agreements. Active measurements are performed by injecting probes, and this is widely used to determine the end to end performance. End to end delay in wired networks has been extensively investigated, and in this thesis we report on the accuracy achieved by probing for end to end delay over a wireless scenario. We have compared two probing techniques i.e. Periodic and Poisson probing, and estimated the absolute error for both. The simulations have been performed for single hop and multi- hop wireless networks. In addition to end to end latency, Active measurements have also been performed for packet loss rate. The simulation based analysis has been tried under different traffic scenarios using Poisson Traffic Models. We have sampled the user traffic using Periodic probing at different rates for single hop and multiple hop wireless scenarios. 5 Active probing becomes critical at higher values of load forcing the network to saturation much earlier. We have evaluated the impact of monitoring overheads on the user traffic, and show that even small amount of probing overhead in a wireless medium can cause large degradation in network performance. Although probing at high rate provides a good estimation of delay distribution of user traffic with large variance yet there is a critical tradeoff between the accuracy of measurement and the packet probing overhead. Our results suggest that active probing is highly affected by probe size, rate, pattern, traffic load, and nature of shared medium, available bandwidth and the burstiness of the traffic

Replica Placement and Location using Distributed Hash Tables

Abstract—Interest in distributed storage is fueled by demand for reliability and resilience combined with decreasing hardware costs. Peer-to-peer storage networks based on distributed hash tables are attractive for their efficient use of resources and result-ing performance. The placement and subsequent efficient location of replicas in such systems remain open problems, especially (1) the requirement to update replicated content, (2) working in the absence of global information, and (3) determination of the locations in a dynamic system without introducing single points of failure. We present and evaluate a novel and versatile technique, replica enumeration, which allows for controlled replication and replica access. The possibility of enumerating and addressing individual replicas allows dynamic updates as well as superior performance without burdening the network with state informa-tion, yet taking advantage of locality information when available. We simulate, analyze, and prove properties of the system, and discuss some applications. I

Scalable and Distributed Resource Management Protocols for Cloud and Big Data Clusters

Cloud data centers require an operating system to manage resources and satisfy operational requirements and management objectives. The growth of popularity in cloud services causes the appearance of a new spectrum of services with sophisticated workload and resource management requirements. Also, data centers are growing by addition of various type of hardware to accommodate the ever-increasing requests of users. Nowadays a large percentage of cloud resources are executing data-intensive applications which need continuously changing workload fluctuations and specific resource management. To this end, cluster computing frameworks are shifting towards distributed resource management for better scalability and faster decision making. Such systems benefit from the parallelization of control and are resilient to failures. Throughout this thesis we investigate algorithms, protocols and techniques to address these challenges in large-scale data centers. We introduce a distributed resource management framework which consolidates virtual machine to as few servers as possible to reduce the energy consumption of data center and hence decrease the cost of cloud providers. This framework can characterize the workload of virtual machines and hence handle trade-off energy consumption and Service Level Agreement (SLA) of customers efficiently. The algorithm is highly scalable and requires low maintenance cost with dynamic workloads and it tries to minimize virtual machines migration costs. We also introduce a scalable and distributed probe-based scheduling algorithm for Big data analytics frameworks. This algorithm can efficiently address the problem job heterogeneity in workloads that has appeared after increasing the level of parallelism in jobs. The algorithm is massively scalable and can reduce significantly average job completion times in comparison with the-state of-the-art. Finally, we propose a probabilistic fault-tolerance technique as part of the scheduling algorithm

Efficient techniques for end-to-end bandwidth estimation: performance evaluations and scalable deployment

Several applications, services, and protocols are conjectured to benefit from the knowledge of the end-to-end available bandwidth on a given Internet path. Unfortunately, despite the availability of several bandwidth estimation techniques, there has been only a limited adoption of these in contemporary applications. We identify two issues that contribute to this state of affairs. First, there is a lack of comprehensive evaluations that can help application developers in calibrating the relative performance of these tools--this is especially limiting since the performance of these tools depends on algorithmic, implementation, as well as temporal aspects of probing for available bandwidth. Second, most existing bandwidth estimation tools impose a large probing overhead on the paths over which bandwidth is measured. This can be a significant deterrent for deploying these tools in distributed infrastructures that need to measure bandwidth on several paths periodically. In this dissertation, we address the two issues raised above by making the following contributions: We conduct the first comprehensive black-box evaluation of a large suite of prominent available bandwidth estimation tools on a high-speed network. In this evaluation,we also illustrate the impact that technological and implementation limitations can have on the performance of bandwidth-estimation tools. We conduct the first comprehensive evaluation of available bandwidth estimation algorithms, independent of systemic and implementation biases. In this evaluation, we also illustrate the impact temporal factor such as measurement timescales have on the observed relative performance of bandwidth-estimation tools. We demonstrate that temporal properties can significantly impact the AB estimation process. We redesign the interfaces of existing bandwidth-estimation tools to allow temporal parameters to be explicitly specified and controlled. We design AB inference schemes which can be used to scalably and collaboratively infer the available bandwidth for a large set of end-to-end paths. These schemes allow an operator to select the desired operating point in the trade-off between accuracy and overhead of AB estimation. We further demonstrate that in order to monitor the bandwidth on all paths of a network we do not need access to per-hop bandwidth estimates and can simply rely on end-to-end bandwidth estimates

Exploiting the power of multiplicity: a holistic survey of network-layer multipath

The Internet is inherently a multipath network: For an underlying network with only a single path, connecting various nodes would have been debilitatingly fragile. Unfortunately, traditional Internet technologies have been designed around the restrictive assumption of a single working path between a source and a destination. The lack of native multipath support constrains network performance even as the underlying network is richly connected and has redundant multiple paths. Computer networks can exploit the power of multiplicity, through which a diverse collection of paths is resource pooled as a single resource, to unlock the inherent redundancy of the Internet. This opens up a new vista of opportunities, promising increased throughput (through concurrent usage of multiple paths) and increased reliability and fault tolerance (through the use of multiple paths in backup/redundant arrangements). There are many emerging trends in networking that signify that the Internet's future will be multipath, including the use of multipath technology in data center computing; the ready availability of multiple heterogeneous radio interfaces in wireless (such as Wi-Fi and cellular) in wireless devices; ubiquity of mobile devices that are multihomed with heterogeneous access networks; and the development and standardization of multipath transport protocols such as multipath TCP. The aim of this paper is to provide a comprehensive survey of the literature on network-layer multipath solutions. We will present a detailed investigation of two important design issues, namely, the control plane problem of how to compute and select the routes and the data plane problem of how to split the flow on the computed paths. The main contribution of this paper is a systematic articulation of the main design issues in network-layer multipath routing along with a broad-ranging survey of the vast literature on network-layer multipathing. We also highlight open issues and identify directions for future work