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Register a new userMigration in the Stencil Pluralist Cloud Architecture
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Added by
Tai Liu
Publication date
2021
fields
Informatics Engineering
and research's language is
English
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A debate in the research community has buzzed in the background for years: should large-scale Internet services be centralized or decentralized? Now-common centralized cloud and web services have downsides -- user lock-in and loss of privacy and data control -- that are increasingly apparent. However, their decentralized counterparts have struggled to gain adoption, suffer from their own problems of scalability and trust, and eventually may result in the exact same lock-in they intended to prevent. In this paper, we explore the design of a pluralist cloud architecture, Stencil, one that can serve as a narrow waist for user-facing services such as social media. We aim to enable pluralism via a unifying set of abstractions that support migration from one service to a competing service. We find that migrating linked data introduces many challenges in both source and destination services as links are severed. We show how Stencil enables correct and efficient data migration between services, how it supports the deployment of new services, and how Stencil could be incrementally deployed.
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Online discourse takes place in corporate-controlled spaces thought by users to be public realms. These platforms in name enable free speech but in practice implement varying degrees of censorship either by government edict or by uneven and unseen corporate policy. This kind of censorship has no countervailing accountability mechanism, and as such platform owners, moderators, and algorithms shape public discourse without recourse or transparency. Systems research has explored approaches to decentralizing or democratizing Internet infrastructure for decades. In parallel, the Internet censorship literature is replete with efforts to measure and overcome online censorship. However, in the course of designing specialized open-source platforms and tools, projects generally neglect the needs of supportive but uninvolved `average users. In this paper, we propose a pluralistic approach to democratizing online discourse that considers both the systems-related and user-facing issues as first-order design goals.
Mobility is the backbone of urban life and a vital economic factor in the development of the world. Rapid urbanization and the growth of mega-cities is bringing dramatic changes in the capabilities of vehicles. Innovative solutions like autonomy, electrification, and connectivity are on the horizon. How, then, we can provide ubiquitous connectivity to the legacy and autonomous vehicles? This paper seeks to answer this question by combining recent leaps of innovation in network virtualization with remarkable feats of wireless communications. To do so, this paper proposes a novel paradigm called the Internet of autonomous vehicles (IoAV). We begin painting the picture of IoAV by discussing the salient features, and applications of IoAV which is followed by a detailed discussion on the key enabling technologies. Next, we describe the proposed layered architecture of IoAV and uncover some critical functions of each layer. This is followed by the performance evaluation of IoAV which shows the significant advantage of the proposed architecture in terms of transmission time and energy consumption. Finally, to best capture the benefits of IoAV, we enumerate some social and technological challenges and explain how some unresolved issues can disrupt the widespread use of autonomous vehicles in the future.
Currently, many countries are facing the problems of aging population, serious imbalance of medical resources supply and demand, as well as uneven geographical distribution, resulting in a huge demand for remote e-health. Particularly, with invasions of COVID-19, the health of people and even social stability have been challenged unprecedentedly. To contribute to these urgent problems, this article proposes a general architecture of the remote e-health, where the city hospital provides the technical supports and services for remote hospitals. Meanwhile, 5G technologies supported telemedicine is introduced to satisfy the high-speed transmission of massive multimedia medical data, and further realize the sharing of medical resources. Moreover, to turn passivity into initiative to prevent COVID-19, a broad area epidemic prevention and control scheme is also investigated, especially for the remote areas. We discuss their principles and key features, and foresee the challenges, opportunities, and future research trends. Finally, a node value and content popularity based caching strategy is introduced to provide a preliminary solution of the massive data storage and low-latency transmission.
Industry 4.0 applications foster new business opportunities but they also pose new and challenging requirements, such as low latency communications and highly reliable systems. They enable to exploit novel wireless technologies (5G), but it would also be crucial to rely on architectures that appropriately support them. Thus, the combination of fog and cloud computing is emerging as one potential solution. It can dynamically allocate the workload depending on the specific needs of each application. Our main goal is to provide a highly reliable and dynamic architecture, which minimizes the time that an end node or user, for instance a car in a smart mobility application, spends in downloading the required data. In order to achieve this, we have developed an optimal distribution algorithm that decides, based on multiple parameters of the proposed system model, the amount of information that should be stored at, or retrieved from, each node to minimize the data download time. Our scheme exploits Network Coding (NC) as a tool for data distribution, as a key enabler of the proposed solution. We compare the performance of our proposed scheme with other alternative solutions, and the results show that there is a clear gain in terms of the download time.
Stencil computations are a key part of many high-performance computing applications, such as image processing, convolutional neural networks, and finite-difference solvers for partial differential equations. Devito is a framework capable of generating highly-optimized code given symbolic equations expressed in Python, specialized in, but not limited to, affine (stencil) codes. The lowering process---from mathematical equations down to C++ code---is performed by the Devito compiler through a series of intermediate representations. Several performance optimizations are introduced, including advanced common sub-expressions elimination, tiling and parallelization. Some of these are obtained through well-established stencil optimizers, integrated in the back-end of the Devito compiler. The architecture of the Devito compiler, as well as the performance optimizations that are applied when generating code, are presented. The effectiveness of such performance optimizations is demonstrated using operators drawn from seismic imaging applications.
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