79 research outputs found

    Adaptive and secured resource management in distributed and Internet systems

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    The effectiveness of computer system resource management has been always determined by two major factors: (1) workload demands and management objectives, (2) the updates of the computer technology. These two factors are dynamically changing, and resource management systems must be timely adaptive to the changes. This dissertation attempts to address several important and related resource management issues.;We first study memory system utilization in centralized servers by improving memory performance of sorting algorithms, which provides fundamental understanding on memory system organizations and its performance optimizations for data-intensive workloads. to reduce different types of cache misses, we restructure the mergesort and quicksort algorithms by integrating tiling, padding, and buffering techniques and by repartitioning the data set. Our study shows substantial performance improvements from our new methods.;We have further extended the work to improve load sharing for utilizing global memory resources in distributed systems. Aiming at reducing the memory resource contention caused by page faults and I/O activities, we have developed and examined load sharing policies by considering effective usage of global memory in addition to CPU load balancing in both homogeneous and heterogeneous clusters.;Extending our research from clusters to Internet systems, we have further investigated memory and storage utilizations in Web caching systems. We have proposed several novel management schemes to restructure and decentralize the existing caching system by exploiting data locality at different levels of the global memory hierarchy and by effectively sharing data objects among the clients and their proxy caches.;Data integrity and communication anonymity issues are raised from our decentralized Web caching system design, which are also security concerns for general peer-to-peer systems. We propose an integrity protocol to ensure data integrity, and several protocols to achieve mutual communication anonymity between an information requester and a provider.;The potential impact and contributions of this dissertation are briefly stated as follows: (1) two major research topics identified in this dissertation are fundamentally important for the growth and development of information technology, and will continue to be demanding topics for a long term. (2) Our proposed cache-effective sorting methods bridge a serious gap between analytical complexity of algorithms and their execution complexity in practice due to the increasingly deep memory hierarchy in computer systems. This approach can also be used to improve memory performance at different levels of the memory hierarchy, such as I/O and file systems. (3) Our load sharing principle of giving a high priority to the requests of data accesses in memory and I/Os timely adapts the technology changes and effectively responds to the increasing demand of data-intensive applications. (4) Our proposed decentralized Web caching framework and its resource management schemes present a comprehensive case study to examine the P2P model. Our results and experiences can be used for related and further studies in distributed computing. (5) The proposed data integrity and communication anonymity protocols address limits and weaknesses of existing ones, and place a solid foundation for us to continue our work in this important area

    Cellular networks for smart grid communication

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    The next-generation electric power system, known as smart grid, relies on a robust and reliable underlying communication infrastructure to improve the efficiency of electricity distribution. Cellular networks, e.g., LTE/LTE-A systems, appear as a promising technology to facilitate the smart grid evolution. Their inherent performance characteristics and well-established ecosystem could potentially unlock unprecedented use cases, enabling real-time and autonomous distribution grid operations. However, cellular technology was not originally intended for smart grid communication, associated with highly-reliable message exchange and massive device connectivity requirements. The fundamental differences between smart grid and human-type communication challenge the classical design of cellular networks and introduce important research questions that have not been sufficiently addressed so far. Motivated by these challenges, this doctoral thesis investigates novel radio access network (RAN) design principles and performance analysis for the seamless integration of smart grid traffic in future cellular networks. Specifically, we focus on addressing the fundamental RAN problems of network scalability in massive smart grid deployments and radio resource management for smart grid and human-type traffic. The main objective of the thesis lies on the design, analysis and performance evaluation of RAN mechanisms that would render cellular networks the key enabler for emerging smart grid applications. The first part of the thesis addresses the radio access limitations in LTE-based networks for reliable and scalable smart grid communication. We first identify the congestion problem in LTE random access that arises in large-scale smart grid deployments. To overcome this, a novel random access mechanism is proposed that can efficiently support real-time distribution automation services with negligible impact on the background traffic. Motivated by the stringent reliability requirements of various smart grid operations, we then develop an analytical model of the LTE random access procedure that allows us to assess the performance of event-based monitoring traffic under various load conditions and network configurations. We further extend our analysis to include the relation between the cell size and the availability of orthogonal random access resources and we identify an additional challenge for reliable smart grid connectivity. To this end, we devise an interference- and load-aware cell planning mechanism that enhances reliability in substation automation services. Finally, we couple the problem of state estimation in wide-area monitoring systems with the reliability challenges in information acquisition. Using our developed analytical framework, we quantify the impact of imperfect communication reliability in the state estimation accuracy and we provide useful insights for the design of reliability-aware state estimators. The second part of the thesis builds on the previous one and focuses on the RAN problem of resource scheduling and sharing for smart grid and human-type traffic. We introduce a novel scheduler that achieves low latency for distribution automation traffic while resource allocation is performed in a way that keeps the degradation of cellular users at a minimum level. In addition, we investigate the benefits of Device-to-Device (D2D) transmission mode for event-based message exchange in substation automation scenarios. We design a joint mode selection and resource allocation mechanism which results in higher data rates with respect to the conventional transmission mode via the base station. An orthogonal resource partition scheme between cellular and D2D links is further proposed to prevent the underutilization of the scarce cellular spectrum. The research findings of this thesis aim to deliver novel solutions to important RAN performance issues that arise when cellular networks support smart grid communication.Las redes celulares, p.e., los sistemas LTE/LTE-A, aparecen como una tecnología prometedora para facilitar la evolución de la próxima generación del sistema eléctrico de potencia, conocido como smart grid (SG). Sin embargo, la tecnología celular no fue pensada originalmente para las comunicaciones en la SG, asociadas con el intercambio fiable de mensajes y con requisitos de conectividad de un número masivo de dispositivos. Las diferencias fundamentales entre las comunicaciones en la SG y la comunicación de tipo humano desafían el diseño clásico de las redes celulares e introducen importantes cuestiones de investigación que hasta ahora no se han abordado suficientemente. Motivada por estos retos, esta tesis doctoral investiga los principios de diseño y analiza el rendimiento de una nueva red de acceso radio (RAN) que permita una integración perfecta del tráfico de la SG en las redes celulares futuras. Nos centramos en los problemas fundamentales de escalabilidad de la RAN en despliegues de SG masivos, y en la gestión de los recursos radio para la integración del tráfico de la SG con el tráfico de tipo humano. El objetivo principal de la tesis consiste en el diseño, el análisis y la evaluación del rendimiento de los mecanismos de las RAN que convertirán a las redes celulares en el elemento clave para las aplicaciones emergentes de las SGs. La primera parte de la tesis aborda las limitaciones del acceso radio en redes LTE para la comunicación fiable y escalable en SGs. En primer lugar, identificamos el problema de congestión en el acceso aleatorio de LTE que aparece en los despliegues de SGs a gran escala. Para superar este problema, se propone un nuevo mecanismo de acceso aleatorio que permite soportar de forma eficiente los servicios de automatización de la distribución eléctrica en tiempo real, con un impacto insignificante en el tráfico de fondo. Motivados por los estrictos requisitos de fiabilidad de las diversas operaciones en la SG, desarrollamos un modelo analítico del procedimiento de acceso aleatorio de LTE que nos permite evaluar el rendimiento del tráfico de monitorización de la red eléctrica basado en eventos bajo diversas condiciones de carga y configuraciones de red. Además, ampliamos nuestro análisis para incluir la relación entre el tamaño de celda y la disponibilidad de recursos de acceso aleatorio ortogonales, e identificamos un reto adicional para la conectividad fiable en la SG. Con este fin, diseñamos un mecanismo de planificación celular que tiene en cuenta las interferencias y la carga de la red, y que mejora la fiabilidad en los servicios de automatización de las subestaciones eléctricas. Finalmente, combinamos el problema de la estimación de estado en sistemas de monitorización de redes eléctricas de área amplia con los retos de fiabilidad en la adquisición de la información. Utilizando el modelo analítico desarrollado, cuantificamos el impacto de la baja fiabilidad en las comunicaciones sobre la precisión de la estimación de estado. La segunda parte de la tesis se centra en el problema de scheduling y compartición de recursos en la RAN para el tráfico de SG y el tráfico de tipo humano. Presentamos un nuevo scheduler que proporciona baja latencia para el tráfico de automatización de la distribución eléctrica, mientras que la asignación de recursos se realiza de un modo que mantiene la degradación de los usuarios celulares en un nivel mínimo. Además, investigamos los beneficios del modo de transmisión Device-to-Device (D2D) en el intercambio de mensajes basados en eventos en escenarios de automatización de subestaciones eléctricas. Diseñamos un mecanismo conjunto de asignación de recursos y selección de modo que da como resultado tasas de datos más elevadas con respecto al modo de transmisión convencional a través de la estación base. Finalmente, se propone un esquema de partición de recursos ortogonales entre enlaces celulares y D2Postprint (published version

    A Hybrid client-server based technique for navigation in large terrains using mobile devices

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    We describe a hybrid client-server technique for remote adaptive streaming and rendering of large terrains in resource-limited mobile devices. The technique has been designed to achieve an interactive rendering performance on a mobile device connected to a low-bandwidth wireless network. The rendering workload is split between the client and the server. The terrain area close to the viewer is rendered in real-time by the client using a hierarchical multiresolution scheme. The terrain located far from the viewer is portrayed as view-dependent impostors, rendered by the server on demand and, then sent to the client. The hybrid technique provides tools to dynamically balance the rendering workload according to the resources available at the client side and to the saturation of the network and server. A prototype has been built and an exhaustive set of experiments covering several platforms, wireless networks and a wide range of viewer velocities has been conducted. Results show that the approach is feasible, effective and robust.Postprint (published version

    A Framework for Dynamic Terrain with Application in Off-road Ground Vehicle Simulations

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    The dissertation develops a framework for the visualization of dynamic terrains for use in interactive real-time 3D systems. Terrain visualization techniques may be classified as either static or dynamic. Static terrain solutions simulate rigid surface types exclusively; whereas dynamic solutions can also represent non-rigid surfaces. Systems that employ a static terrain approach lack realism due to their rigid nature. Disregarding the accurate representation of terrain surface interaction is rationalized because of the inherent difficulties associated with providing runtime dynamism. Nonetheless, dynamic terrain systems are a more correct solution because they allow the terrain database to be modified at run-time for the purpose of deforming the surface. Many established techniques in terrain visualization rely on invalid assumptions and weak computational models that hinder the use of dynamic terrain. Moreover, many existing techniques do not exploit the capabilities offered by current computer hardware. In this research, we present a component framework for terrain visualization that is useful in research, entertainment, and simulation systems. In addition, we present a novel method for deforming the terrain that can be used in real-time, interactive systems. The development of a component framework unifies disparate works under a single architecture. The high-level nature of the framework makes it flexible and adaptable for developing a variety of systems, independent of the static or dynamic nature of the solution. Currently, there are only a handful of documented deformation techniques and, in particular, none make explicit use of graphics hardware. The approach developed by this research offloads extra work to the graphics processing unit; in an effort to alleviate the overhead associated with deforming the terrain. Off-road ground vehicle simulation is used as an application domain to demonstrate the practical nature of the framework and the deformation technique. In order to realistically simulate terrain surface interactivity with the vehicle, the solution balances visual fidelity and speed. Accurately depicting terrain surface interactivity in off-road ground vehicle simulations improves visual realism; thereby, increasing the significance and worth of the application. Systems in academia, government, and commercial institutes can make use of the research findings to achieve the real-time display of interactive terrain surfaces

    Towards Massive Machine Type Communications in Ultra-Dense Cellular IoT Networks: Current Issues and Machine Learning-Assisted Solutions

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    The ever-increasing number of resource-constrained Machine-Type Communication (MTC) devices is leading to the critical challenge of fulfilling diverse communication requirements in dynamic and ultra-dense wireless environments. Among different application scenarios that the upcoming 5G and beyond cellular networks are expected to support, such as eMBB, mMTC and URLLC, mMTC brings the unique technical challenge of supporting a huge number of MTC devices, which is the main focus of this paper. The related challenges include QoS provisioning, handling highly dynamic and sporadic MTC traffic, huge signalling overhead and Radio Access Network (RAN) congestion. In this regard, this paper aims to identify and analyze the involved technical issues, to review recent advances, to highlight potential solutions and to propose new research directions. First, starting with an overview of mMTC features and QoS provisioning issues, we present the key enablers for mMTC in cellular networks. Along with the highlights on the inefficiency of the legacy Random Access (RA) procedure in the mMTC scenario, we then present the key features and channel access mechanisms in the emerging cellular IoT standards, namely, LTE-M and NB-IoT. Subsequently, we present a framework for the performance analysis of transmission scheduling with the QoS support along with the issues involved in short data packet transmission. Next, we provide a detailed overview of the existing and emerging solutions towards addressing RAN congestion problem, and then identify potential advantages, challenges and use cases for the applications of emerging Machine Learning (ML) techniques in ultra-dense cellular networks. Out of several ML techniques, we focus on the application of low-complexity Q-learning approach in the mMTC scenarios. Finally, we discuss some open research challenges and promising future research directions.Comment: 37 pages, 8 figures, 7 tables, submitted for a possible future publication in IEEE Communications Surveys and Tutorial

    ENERGY CONSERVATION FOR WIRELESS AD HOC ROUTING

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    Self-configuring wireless ad hoc networks have attracted considerable attention in the last few years due to their valuable civil and military applications. One aspect of such networks that has been studied insufficiently is the energy efficiency. Energy efficiency is crucial to prolong the network lifetime and thus make the network more survivable.Nodes in wireless ad hoc networks are most likely to be driven by battery and hence operate on an extremely frugal energy budget. Conventional ad hoc routing protocols are focused on handling the mobility instead of energy efficiency. Energy efficient routing strategies proposed in literature either do not take advantage of sleep modes to conserve energy more efficiently, or incur much overhead in terms of control message and computing complexity to schedule sleep modes and thus are not scalable.In this dissertation, a novel strategy is proposed to manage the sleep of the nodes in the network so that energy can be conserved and network connectivity can be kept. The novelty of the strategy is its extreme simplicity. The idea is derived from the results of the percolation theory, typically called gossiping. Gossiping is a convenient and effective approach and has been successfully applied to several areas of the networking. In the proposed work, we will developa sleep management protocol from gossiping for both static and mobile wireless ad hoc networks. Then the protocol will be extended to the asynchronous network, where nodes manage their own states independently. Analysis and simulations will be conducted to show thecorrectness, effectiveness and efficiency of the proposed work. The comparison between analytical and simulation results will justify them for each other. We will investigate the most important performance aspects concerning the proposed strategy, including the effect ofparameter tuning and the impacts of routing protocols. Furthermore, multiple extensions will be developed to improve the performance and make the proposed strategy apply to different network scenarios

    Run-time optimization of adaptive irregular applications

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    Compared to traditional compile-time optimization, run-time optimization could offer significant performance improvements when parallelizing and optimizing adaptive irregular applications, because it performs program analysis and adaptive optimizations during program execution. Run-time techniques can succeed where static techniques fail because they exploit the characteristics of input data, programs' dynamic behaviors, and the underneath execution environment. When optimizing adaptive irregular applications for parallel execution, a common observation is that the effectiveness of the optimizing transformations depends on programs' input data and their dynamic phases. This dissertation presents a set of run-time optimization techniques that match the characteristics of programs' dynamic memory access patterns and the appropriate optimization (parallelization) transformations. First, we present a general adaptive algorithm selection framework to automatically and adaptively select at run-time the best performing, functionally equivalent algorithm for each of its execution instances. The selection process is based on off-line automatically generated prediction models and characteristics (collected and analyzed dynamically) of the algorithm's input data, In this dissertation, we specialize this framework for automatic selection of reduction algorithms. In this research, we have identified a small set of machine independent high-level characterization parameters and then we deployed an off-line, systematic experiment process to generate prediction models. These models, in turn, match the parameters to the best optimization transformations for a given machine. The technique has been evaluated thoroughly in terms of applications, platforms, and programs' dynamic behaviors. Specifically, for the reduction algorithm selection, the selected performance is within 2% of optimal performance and on average is 60% better than "Replicated Buffer," the default parallel reduction algorithm specified by OpenMP standard. To reduce the overhead of speculative run-time parallelization, we have developed an adaptive run-time parallelization technique that dynamically chooses effcient shadow structures to record a program's dynamic memory access patterns for parallelization. This technique complements the original speculative run-time parallelization technique, the LRPD test, in parallelizing loops with sparse memory accesses. The techniques presented in this dissertation have been implemented in an optimizing research compiler and can be viewed as effective building blocks for comprehensive run-time optimization systems, e.g., feedback-directed optimization systems and dynamic compilation systems

    Evaluation of IEEE 802.11ah Technology for Wireless Sensor Network Applications

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    We are entering into a new computing technological era where communications are established not just user to user, or user to machine, but also machine to machine (M2M), machine to infrastructure, machine to environment. This then brings out the idea of acquiring data from the environment, process that data and use it to obtain a benefit, and the way to make this happen is by deploying a network of sensors which will provide an application with the desired sensed data. A sensor network is for practical reasons, nowadays considered as a Wireless Sensor Network (WSN). As we move from static web to social networking and furthermore to ubiquitous computing, the amount of wireless devices out there is increasing exponentially. This has triggered a series of challenges for communications technologies as many new requirements need to be addressed. Low-cost, low-power and long-range coverage are the key requirements when designing a WSN. Since the communications subsystem in a WSN is the one dragging most resources, the WSN market is demanding new communication technologies to improve the performance of their current applications, but also to empower innovation by creating new application possibilities. Consequently, a new technology proposal has emerged as a solution to the previously mentioned requirements; the IEEE 802.11ah. This is an amendment to the well-known legacy IEEE 802.11 technologies and promises coverage for up to 1km with at least 100kbps, and support a large amount of stations. This Master’s Thesis offers an insight to this new technology by evaluating its performance through an analytical model which is first developed and then evaluated in MatLab 2014b. A series of performance metrics have been considered in this work with the intention of evaluating its feasibility for WSNs. Different use cases are presented to give an idea of how this new communications standard would perform in real-life scenarios. Based on the obtained results, it is concluded that the standard would perform well when implemented in WSN. But what differentiates the IEEE 802.11ah from its close competitors is the fact that substantial infrastructure using IEEE802.11ah and its amendments already exists, for which the transition to its use seems to be an easy bet. The IEEE 802.11ah is still under development and is expected to be ready for 2016

    [Activity of Institute for Computer Applications in Science and Engineering]

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    This report summarizes research conducted at the Institute for Computer Applications in Science and Engineering in applied mathematics, fluid mechanics, and computer science

    Out-of-core visualization using iterator-aware multidimensional prefetching

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