356 research outputs found

    Resource-aware scheduling for 2D/3D multi-/many-core processor-memory systems

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    This dissertation addresses the complexities of 2D/3D multi-/many-core processor-memory systems, focusing on two key areas: enhancing timing predictability in real-time multi-core processors and optimizing performance within thermal constraints. The integration of an increasing number of transistors into compact chip designs, while boosting computational capacity, presents challenges in resource contention and thermal management. The first part of the thesis improves timing predictability. We enhance shared cache interference analysis for set-associative caches, advancing the calculation of Worst-Case Execution Time (WCET). This development enables accurate assessment of cache interference and the effectiveness of partitioned schedulers in real-world scenarios. We introduce TCPS, a novel task and cache-aware partitioned scheduler that optimizes cache partitioning based on task-specific WCET sensitivity, leading to improved schedulability and predictability. Our research explores various cache and scheduling configurations, providing insights into their performance trade-offs. The second part focuses on thermal management in 2D/3D many-core systems. Recognizing the limitations of Dynamic Voltage and Frequency Scaling (DVFS) in S-NUCA many-core processors, we propose synchronous thread migrations as a thermal management strategy. This approach culminates in the HotPotato scheduler, which balances performance and thermal safety. We also introduce 3D-TTP, a transient temperature-aware power budgeting strategy for 3D-stacked systems, reducing the need for Dynamic Thermal Management (DTM) activation. Finally, we present 3QUTM, a novel method for 3D-stacked systems that combines core DVFS and memory bank Low Power Modes with a learning algorithm, optimizing response times within thermal limits. This research contributes significantly to enhancing performance and thermal management in advanced processor-memory systems

    Cybersecurity: Past, Present and Future

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    The digital transformation has created a new digital space known as cyberspace. This new cyberspace has improved the workings of businesses, organizations, governments, society as a whole, and day to day life of an individual. With these improvements come new challenges, and one of the main challenges is security. The security of the new cyberspace is called cybersecurity. Cyberspace has created new technologies and environments such as cloud computing, smart devices, IoTs, and several others. To keep pace with these advancements in cyber technologies there is a need to expand research and develop new cybersecurity methods and tools to secure these domains and environments. This book is an effort to introduce the reader to the field of cybersecurity, highlight current issues and challenges, and provide future directions to mitigate or resolve them. The main specializations of cybersecurity covered in this book are software security, hardware security, the evolution of malware, biometrics, cyber intelligence, and cyber forensics. We must learn from the past, evolve our present and improve the future. Based on this objective, the book covers the past, present, and future of these main specializations of cybersecurity. The book also examines the upcoming areas of research in cyber intelligence, such as hybrid augmented and explainable artificial intelligence (AI). Human and AI collaboration can significantly increase the performance of a cybersecurity system. Interpreting and explaining machine learning models, i.e., explainable AI is an emerging field of study and has a lot of potentials to improve the role of AI in cybersecurity.Comment: Author's copy of the book published under ISBN: 978-620-4-74421-

    Geographic information extraction from texts

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    A large volume of unstructured texts, containing valuable geographic information, is available online. This information – provided implicitly or explicitly – is useful not only for scientific studies (e.g., spatial humanities) but also for many practical applications (e.g., geographic information retrieval). Although large progress has been achieved in geographic information extraction from texts, there are still unsolved challenges and issues, ranging from methods, systems, and data, to applications and privacy. Therefore, this workshop will provide a timely opportunity to discuss the recent advances, new ideas, and concepts but also identify research gaps in geographic information extraction

    Data Management for Dynamic Multimedia Analytics and Retrieval

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    Multimedia data in its various manifestations poses a unique challenge from a data storage and data management perspective, especially if search, analysis and analytics in large data corpora is considered. The inherently unstructured nature of the data itself and the curse of dimensionality that afflicts the representations we typically work with in its stead are cause for a broad range of issues that require sophisticated solutions at different levels. This has given rise to a huge corpus of research that puts focus on techniques that allow for effective and efficient multimedia search and exploration. Many of these contributions have led to an array of purpose-built, multimedia search systems. However, recent progress in multimedia analytics and interactive multimedia retrieval, has demonstrated that several of the assumptions usually made for such multimedia search workloads do not hold once a session has a human user in the loop. Firstly, many of the required query operations cannot be expressed by mere similarity search and since the concrete requirement cannot always be anticipated, one needs a flexible and adaptable data management and query framework. Secondly, the widespread notion of staticity of data collections does not hold if one considers analytics workloads, whose purpose is to produce and store new insights and information. And finally, it is impossible even for an expert user to specify exactly how a data management system should produce and arrive at the desired outcomes of the potentially many different queries. Guided by these shortcomings and motivated by the fact that similar questions have once been answered for structured data in classical database research, this Thesis presents three contributions that seek to mitigate the aforementioned issues. We present a query model that generalises the notion of proximity-based query operations and formalises the connection between those queries and high-dimensional indexing. We complement this by a cost-model that makes the often implicit trade-off between query execution speed and results quality transparent to the system and the user. And we describe a model for the transactional and durable maintenance of high-dimensional index structures. All contributions are implemented in the open-source multimedia database system Cottontail DB, on top of which we present an evaluation that demonstrates the effectiveness of the proposed models. We conclude by discussing avenues for future research in the quest for converging the fields of databases on the one hand and (interactive) multimedia retrieval and analytics on the other

    Fundamentals

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    Volume 1 establishes the foundations of this new field. It goes through all the steps from data collection, their summary and clustering, to different aspects of resource-aware learning, i.e., hardware, memory, energy, and communication awareness. Machine learning methods are inspected with respect to resource requirements and how to enhance scalability on diverse computing architectures ranging from embedded systems to large computing clusters

    Improving Data Availability in Decentralized Storage Systems

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    PhD thesis in Information technologyPreserving knowledge for future generations has been a primary concern for humanity since the dawn of civilization. State-of-the-art methods have included stone carvings, papyrus scrolls, and paper books. With each advance in technology, it has become easier to record knowledge. In the current digital age, humanity may preserve enormous amounts of knowledge on hard drives with the click of a button. The aggregation of several hard drives into a computer forms the basis for a storage system. Traditionally, large storage systems have comprised many distinct computers operated by a single administrative entity. With the rise in popularity of blockchain and cryptocurrencies, a new type of storage system has emerged. This new type of storage system is fully decentralized and comprises a network of untrusted peers cooperating to act as a single storage system. During upload, files are split into chunks and distributed across a network of peers. These storage systems encode files using Merkle trees, a hierarchical data structure that provides integrity verification and lookup services. While decentralized storage systems are popular and have a user base in the millions, many technical aspects are still in their infancy. As such, they have yet to prove themselves viable alternatives to traditional centralized storage systems. In this thesis, we contribute to the technical aspects of decentralized storage systems by proposing novel techniques and protocols. We make significant contributions with the design of three practical protocols that each improve data availability in different ways. Our first contribution is Snarl and entangled Merkle trees. Entangled Merkle trees are resilient data structures that decrease the impact hierarchical dependencies have on data availability. Whenever a chunk loss is detected, Snarl uses the entangled Merkle trees to find parity chunks to repair the lost chunk. Our results show that by encoding data as an entangled Merkle tree and using Snarl’s repair algorithm, the storage utilization in current systems could be improved by over five times, with improved data availability. Second, we propose SNIPS, a protocol that efficiently synchronizes the data stored on peers to ensure that all peers have the same data. We designed a Proof of Storage-like construction using a Minimal Perfect Hash Function. Each peer uses the PoS-like construction to create a storage proof for those chunks it wants to synchronize. Peers exchange storage proofs and use them to efficiently determine which chunks they are missing. The evaluation shows that by using SNIPS, the amount of synchronization data can be reduced by three orders of magnitude in current systems. Lastly, in our third contribution, we propose SUP, a protocol that uses cryptographic proofs to check if a chunk is already stored in the network before doing wasteful uploads. We show that SUP may reduce the amount of data transferred by up to 94 % in current systems. The protocols may be deployed independently or in combination to create a decentralized storage system that is more robust to major outages. Each of the protocols has been implemented and evaluated on a large cluster of 1,000 peers

    Cache Attacks and Defenses

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    In the digital age, as our daily lives depend heavily on interconnected computing devices, information security has become a crucial concern. The continuous exchange of data between devices over the Internet exposes our information vulnerable to potential security breaches. Yet, even with measures in place to protect devices, computing equipment inadvertently leaks information through side-channels, which emerge as byproducts of computational activities. One particular source of such side channels is the cache, a vital component of modern processors that enhances computational speed by storing frequently accessed data from random access memory (RAM). Due to their limited capacity, caches often need to be shared among concurrently running applications, resulting in vulnerabilities. Cache side-channel attacks, which exploit such vulnerabilities, have received significant attention due to their ability to stealthily compromise information confidentiality and the challenge in detecting and countering them. Consequently, numerous defense strategies have been proposed to mitigate these attacks. This thesis explores these defense strategies against cache side-channels, assesses their effectiveness, and identifies any potential vulnerabilities that could be used to undermine the effectiveness of these defense strategies. The first contribution of this thesis is a software framework to assess the security of secure cache designs. We show that while most secure caches are protected from eviction-set-based attacks, they are vulnerable to occupancybased attacks, which works just as well as eviction-set-based attacks, and therefore should be taken into account when designing and evaluating secure caches. Our second contribution presents a method that utilizes speculative execution to enable high-resolution attacks on low-resolution timers, a common cache attack countermeasure adopted by web browsers. We demonstrate that our technique not only allows for high-resolution attacks to be performed on low-resolution timers, but is also Turing-complete and is capable of performing robust calculations on cache states. Through this research, we uncover a new attack vector on low-resolution timers. By exposing this vulnerability, we hope to prompt the necessary measures to address the issue and enhance the security of systems in the future. Our third contribution is a survey, paired with experimental assessment of cache side-channel attack detection techniques using hardware performance counters. We show that, despite numerous claims regarding their efficacy, most detection techniques fail to perform proper evaluation of their performance, leaving them vulnerable to more advanced attacks. We identify and outline these shortcomings, and furnish experimental evidence to corroborate our findings. Furthermore, we demonstrate a new attack that is capable of compromising these detection methods. Our aim is to bring attention to these shortcomings and provide insights that can aid in the development of more robust cache side-channel attack detection techniques. This thesis contributes to a deeper comprehension of cache side-channel attacks and their potential effects on information security. Furthermore, it offers valuable insights into the efficacy of existing mitigation approaches and detection methods, while identifying areas for future research and development to better safeguard our computing devices and data from these insidious attacks.Thesis (MPhil) -- University of Adelaide, School of Computer and Mathematical Sciences, 202

    Images on the Move

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    In contemporary society, digital images have become increasingly mobile. They are networked, shared on social media, and circulated across small and portable screens. Accordingly, the discourses of spreadability and circulation have come to supersede the focus on production, indexicality, and manipulability, which had dominated early conceptions of digital photography and film. However, the mobility of images is neither technologically nor conceptually limited to the realm of the digital. The edited volume re-examines the historical, aesthetical, and theoretical relevance of image mobility. The contributors provide a materialist account of images on the move - ranging from wired photography to postcards to streaming media
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