Efficient and Effective Schemes for Streaming Media Delivery

The rapid expansion of the Internet and the increasingly wide deployment of wireless networks provide opportunities to deliver streaming media content to users at anywhere, anytime. To ensure good user experience, it is important to battle adversary effects, such as delay, loss and jitter. In this thesis, we first study efficient loss recovery schemes, which require pure XOR operations. In particular, we propose a novel scheme capable of recovering up to 3 packet losses, and it has the lowest complexity among all known schemes. We also propose an efficient algorithm for array codes decoding, which achieves significant throughput gain and energy savings over conventional codes. We believe these schemes are applicable to streaming applications, especially in wireless environments. We then study quality adaptation schemes for client buffer management. Our control-theoretic approach results in an efficient online rate control algorithm with analytically tractable performance. Extensive experimental results show that three goals are achieved: fast startup, continuous playback in the face of severe congestion, and maximal quality and smoothness over the entire streaming session. The scheme is later extended to streaming with limited quality levels, which is then directly applicable to existing systems

Code Constructions for Distributed Storage With Low Repair Bandwidth and Low Repair Complexity

We present the construction of a family of erasure correcting codes for distributed storage that achieve low repair bandwidth and complexity at the expense of a lower fault tolerance. The construction is based on two classes of codes, where the primary goal of the first class of codes is to provide fault tolerance, while the second class aims at reducing the repair bandwidth and repair complexity. The repair procedure is a two- step procedure where parts of the failed node are repaired in the first step using the first code. The downloaded symbols during the first step are cached in the memory and used to repair the remaining erased data symbols at minimal additional read cost during the second step. The first class of codes is based on MDS codes modified using piggybacks, while the second class is designed to reduce the number of additional symbols that need to be downloaded to repair the remaining erased symbols. We numerically show that the proposed codes achieve better repair bandwidth compared to MDS codes, codes constructed using piggybacks, and local reconstruction/Pyramid codes, while a better repair complexity is achieved when compared to MDS, Zigzag, Pyramid codes, and codes constructed using piggybacks.Comment: To appear in IEEE Transactions on Communication

On the design and optimization of heterogeneous distributed storage systems

Durant la última dècada, la demanda d’emmagatzematge de dades ha anat creixent exponencialment any rere any. Apart de demanar més capacitat d’emmagatzematge, el usuaris actualment també demanen poder accedir a les seves dades des de qualsevol lloc i des de qualsevol dispositiu. Degut a aquests nous requeriments, els usuaris estan actualment movent les seves dades personals (correus electrònics, documents, fotografies, etc.) cap a serveis d’emmagatzematge en línia com ara Gmail, Facebook, Flickr o Dropbox. Malauradament, aquests serveis d’emmagatzematge en línia estan sostinguts per unes grans infraestructures informàtiques que poques empreses poden finançar. Per tal de reduir el costs d’aquestes grans infraestructures informàtiques, ha sorgit una nova onada de serveis d’emmagatzematge en línia que obtenen grans infraestructures d’emmagatzematge a base d’integrar els recursos petits centres de dades, o fins i tot a base d’integrar els recursos d’emmagatzematge del usuaris finals. No obstant això, els recursos que formen aquestes noves infraestructures d’emmagatzematge són molt heterogenis, cosa que planteja un repte per al dissenyadors d’aquests sistemes: Com es poden dissenyar sistemes d’emmagatzematge en línia, fiables i eficients, quan la infraestructura emprada és tan heterogènia? Aquesta tesis presenta un estudi dels principals problemes que sorgeixen quan un vol respondre a aquesta pregunta. A més proporciona diferents eines per tal d’optimitzar el disseny de sistemes d’emmagatzematge distribuïts i heterogenis. Les principals contribucions són: Primer, creem un marc d’anàlisis per estudiar els efectes de la redundància de dades en el cost dels sistemes d’emmagatzematge distribuïts. Donat un esquema de redundància específic, el marc d’anàlisis presentat permet predir el cost mitjà d’emmagatzematge i el cost mitjà de comunicació d’un sistema d’emmagatzematge implementat sobre qualsevol infraestructura informàtica distribuïda. Segon, analitzem els impactes que la redundància de dades té en la disponibilitat de les dades, i en els temps de recuperació. Donada una redundància, i donat un sistema d’emmagatzematge heterogeni, creem un grup d’algorismes per a determinar la disponibilitat de les dades esperada, i els temps de recuperació esperats. Tercer, dissenyem diferents polítiques d’assignació de dades per a diferents sistemes d’emmagatzematge. Diferenciem entre aquells escenaris on la totalitat de la infraestructura està administrada per una sola organització, i els escenaris on diferents parts auto administrades contribueixen els seus recursos. Els objectius de les nostres polítiques d’assignació de dades són: (i) minimitzar la redundància necessària, (ii) garantir la equitat entre totes les parts que participen al sistema, i (iii) incentivar a les parts perquè contribueixin els seus recursos al sistema.Over the last decade, users’ storage demands have been growing exponentially year over year. Besides demanding more storage capacity and more data reliability, today users also demand the possibility to access their data from any location and from any device. These new needs encourage users to move their personal data (e.g., E-mails, documents, pictures, etc.) to online storage services such as Gmail, Facebook, Flickr or Dropbox. Unfortunately, these online storage services are built upon expensive large datacenters that only a few big enterprises can afford. To reduce the costs of these large datacenters, a new wave of online storage services has recently emerged integrating storage resources from different small datacenters, or even integrating user storage resources into the provider’s storage infrastructure. However, the storage resources that compose these new storage infrastructures are highly heterogeneous, which poses a challenging problem to storage systems designers: How to design reliable and efficient distributed storage systems over heterogeneous storage infrastructures? This thesis provides an analysis of the main problems that arise when one aims to answer this question. Besides that, this thesis provides different tools to optimize the design of heterogeneous distributed storage systems. The contribution of this thesis is threefold: First, we provide a novel framework to analyze the effects that data redundancy has on the storage and communication costs of distributed storage systems. Given a generic redundancy scheme, the presented framework can predict the average storage costs and the average communication costs of a storage system deployed over a specific storage infrastructure. Second, we analyze the impacts that data redundancy has on data availability and retrieval times. For a given redundancy and a heterogeneous storage infrastructure, we provide a set of algorithms that allow to determine the expected data availability and expected retrieval times. Third, we design different data assignment policies for different storage scenarios. We differentiate between scenarios where the entire storage infrastructure is managed by the same organization, and scenarios where different parties contribute their storage resources. The aims of our assignment policies are: (i) to minimize the required redundancy, (ii) to guarantee fairness among all parties, and (iii) to encourage different parties to contribute their local storage resources to the system

Computer Aided Verification

This open access two-volume set LNCS 13371 and 13372 constitutes the refereed proceedings of the 34rd International Conference on Computer Aided Verification, CAV 2022, which was held in Haifa, Israel, in August 2022. The 40 full papers presented together with 9 tool papers and 2 case studies were carefully reviewed and selected from 209 submissions. The papers were organized in the following topical sections: Part I: Invited papers; formal methods for probabilistic programs; formal methods for neural networks; software Verification and model checking; hyperproperties and security; formal methods for hardware, cyber-physical, and hybrid systems. Part II: Probabilistic techniques; automata and logic; deductive verification and decision procedures; machine learning; synthesis and concurrency. This is an open access book

Scaling and Resilience in Numerical Algorithms for Exascale Computing

The first Petascale supercomputer, the IBM Roadrunner, went online in 2008. Ten years later, the community is now looking ahead to a new generation of Exascale machines. During the decade that has passed, several hundred Petascale capable machines have been installed worldwide, yet despite the abundance of machines, applications that scale to their full size remain rare. Large clusters now routinely have 50.000+ cores, some have several million. This extreme level of parallelism, that has allowed a theoretical compute capacity in excess of a million billion operations per second, turns out to be difficult to use in many applications of practical interest. Processors often end up spending more time waiting for synchronization, communication, and other coordinating operations to complete, rather than actually computing. Component reliability is another challenge facing HPC developers. If even a single processor fail, among many thousands, the user is forced to restart traditional applications, wasting valuable compute time. These issues collectively manifest themselves as low parallel efficiency, resulting in waste of energy and computational resources. Future performance improvements are expected to continue to come in large part due to increased parallelism. One may therefore speculate that the difficulties currently faced, when scaling applications to Petascale machines, will progressively worsen, making it difficult for scientists to harness the full potential of Exascale computing. The thesis comprises two parts. Each part consists of several chapters discussing modifications of numerical algorithms to make them better suited for future Exascale machines. In the first part, the use of Parareal for Parallel-in-Time integration techniques for scalable numerical solution of partial differential equations is considered. We propose a new adaptive scheduler that optimize the parallel efficiency by minimizing the time-subdomain length without making communication of time-subdomains too costly. In conjunction with an appropriate preconditioner, we demonstrate that it is possible to obtain time-parallel speedup on the nonlinear shallow water equation, beyond what is possible using conventional spatial domain-decomposition techniques alone. The part is concluded with the proposal of a new method for constructing Parallel-in-Time integration schemes better suited for convection dominated problems. In the second part, new ways of mitigating the impact of hardware failures are developed and presented. The topic is introduced with the creation of a new fault-tolerant variant of Parareal. In the chapter that follows, a C++ Library for multi-level checkpointing is presented. The library uses lightweight in-memory checkpoints, protected trough the use of erasure codes, to mitigate the impact of failures by decreasing the overhead of checkpointing and minimizing the compute work lost. Erasure codes have the unfortunate property that if more data blocks are lost than parity codes created, the data is effectively considered unrecoverable. The final chapter contains a preliminary study on partial information recovery for incomplete checksums. Under the assumption that some meta knowledge exists on the structure of the data encoded, we show that the data lost may be recovered, at least partially. This result is of interest not only in HPC but also in data centers where erasure codes are widely used to protect data efficiently

Abstracts on Radio Direction Finding (1899 - 1995)

The files on this record represent the various databases that originally composed the CD-ROM issue of "Abstracts on Radio Direction Finding" database, which is now part of the Dudley Knox Library's Abstracts and Selected Full Text Documents on Radio Direction Finding (1899 - 1995) Collection. (See Calhoun record https://calhoun.nps.edu/handle/10945/57364 for further information on this collection and the bibliography). Due to issues of technological obsolescence preventing current and future audiences from accessing the bibliography, DKL exported and converted into the three files on this record the various databases contained in the CD-ROM. The contents of these files are: 1) RDFA_CompleteBibliography_xls.zip [RDFA_CompleteBibliography.xls: Metadata for the complete bibliography, in Excel 97-2003 Workbook format; RDFA_Glossary.xls: Glossary of terms, in Excel 97-2003 Workbookformat; RDFA_Biographies.xls: Biographies of leading figures, in Excel 97-2003 Workbook format]; 2) RDFA_CompleteBibliography_csv.zip [RDFA_CompleteBibliography.TXT: Metadata for the complete bibliography, in CSV format; RDFA_Glossary.TXT: Glossary of terms, in CSV format; RDFA_Biographies.TXT: Biographies of leading figures, in CSV format]; 3) RDFA_CompleteBibliography.pdf: A human readable display of the bibliographic data, as a means of double-checking any possible deviations due to conversion