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检索条件"任意字段=Proceedings of the ACM Symposium on Principles of Distributed Computing"

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Authenticated and Auditable Data Sharing via Smart Contract 20

Authenticated and Auditable Data Sharing via Smart Contract

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35th Annual acm symposium on Applied computing (SAC)

作者： Reniers, Vincent Gao, Yuan Zhang, Ren Viviani, Paolo Madhusudan, Akash Lagaisse, Bert Nikova, Svetla Van Landuyt, Dimitri Lombardi, Riccardo Preneel, Bart Joosen, Wouter Katholieke Univ Leuven imec DistriNet Leuven Belgium Katholieke Univ Leuven imec COSIC Leuven Belgium Katholieke Univ Leuven Nervos & imec COSIC Leuven Belgium Univ Torino Noesis Solut NV Turin Italy

ISBN: (纸本)9781450368667

Our main use case features multiple companies that iteratively optimize on the architectural properties of aircraft components in a decentralized manner. In each optimization step of the so-called multi-disciplinary optimization (MDO) process, sensitive data is exchanged between organizations, and we require auditability and traceability of actions taken to assure compliance with signed legal agreements. In this paper, we present a distributed protocol that coordinates authenticated and auditable exchanges of files, leveraging a smart contract. The entire life cycle of a file exchange, including file registration, access request and key distribution, is recorded and traceable via the smart contract. Moreover, when one party raises a dispute, the smart contract can be used to identify the dishonest party without compromising the file's confidentiality. The proposed protocol provides a simple, novel, yet efficient approach to exchange files with support for data access auditability between companies involved in a private consortium with no incentive to share files outside of the protocol. We implemented the protocol in Solidity, deployed it on a private Ethereum blockchain, and validated it within the use case of a decentralized workflow.

关键词： Blockchain storage distributed shared ledger Data sharing smart contract Auditable data sharing

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Model-based auto-scaling of distributed data stream processing applications 21

Model-based auto-scaling of distributed data stream processi...

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21st International Middleware Conference Doctoral symposium, Middleware 2020 - Part of Middleware 2020

作者： Russo, Gabriele Russo University of Rome Tor Vergata Rome Italy

ISBN: (纸本)9781450382007

Data Stream Processing (DSP) enables near real-time analysis of fast data streams, produced, e.g., by Internet-of-Things devices. distributed DSP systems exploit distributed computing infrastructures, possibly spanning both Cloud and Fog/Edge platforms, to scale their execution and cope with high-volume streams. To avoid resource under-provisioning or wastage in face of highly variable workloads, DSP applications should elastically acquire and release resources as needed. In this doctoral work we investigate mechanisms and policies to auto-scale DSP applications. Differently from most previous works, we consider resource heterogeneity and model uncertainty as primary challenges. Moreover, we devise a hierarchical control scheme to avoid the scalability issues that may affect centralized solutions. © 2020 acm.

关键词： Reinforcement learning

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A study on real-time image processing applications with edge computing support for mobile devices 21

A study on real-time image processing applications with edge...

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proceedings of the 2021 IEEE/acm 25th International symposium on distributed Simulation and Real Time Applications

作者： Gabriele Proietti Mattia Roberto Beraldi Sapienza University of Rome

ISBN: (纸本)9781665433266

Different libraries allow performing computer vision tasks, e.g., object recognition, in almost every mobile device that has a computing capability. In modern smartphones, such tasks are compute-intensive, energy hungry computation running on the GPU or the particular Machine Learning (ML) processor embedded in the device. Task offloading is a strategy adopted to move compute-intensive tasks and hence their energy consumption to external computers, in the edge network or in the cloud. In this paper, we report an experimental study that measure under different mobile computer vision set-ups the energy reduction when the inference of an image processing is moved to an edge node, and the capability to still meet real-time *** particular, our experiments show that offloading the task - in our case real-time object recognition - to a possible next-to-the-user node allows saving about the 70% of battery consumption while maintaining the same frame rate (fps) that local processing can achieve.

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On distributed Listing of Cliques 20

On Distributed Listing of Cliques

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39th symposium on principles of distributed computing

作者： Censor-Hillel, Keren Le Gall, Francois Leitersdorf, Dean Technion Dept Comp Sci Haifa Israel Nagoya Univ Grad Sch Math Nagoya Aichi Japan

ISBN: (纸本)9781450375825

We show an (O) over tilde (n(p/(p+2)))-round algorithm in the CONGEST model for listing of K-p (a clique with p nodes), for all p = 4, p >= 6. For p = 5, we show an (O) over tilde (n(3/4))-round algorithm. For p = 4 and p = 5, our results improve upon the previous state-of-the-art of O(n(5/6+o(1))) and O(n(21/22+o(1))), respectively, by Eden et al. [DISC 2019]. For all p >= 6, ours is the first sub-linear round algorithm for Kp listing. We leverage the recent expander decomposition algorithm of Chang et al. [SODA 2019] to create clusters with a good mixing time. Three key novelties in our algorithm are: (1) we carefully iterate our listing process with coupled values of min-degree within the clusters and arboricity outside the clusters, (2) all the listing is done within the cluster, which necessitates new techniques for bringing into the cluster the information about all edges that can potentially form K-p instances with the cluster edges, and (3) within each cluster we use a sparsity-aware listing algorithm, which is faster than a general listing algorithm and which we can allow the cluster to use since we make sure to sparsify the graph as the iterations proceed. As a byproduct of our algorithm, we show an optimal sparsityaware algorithm for K-p listing, which runs in Theta(1 + m/n(1+2/p)) rounds in the CONGESTED CLIQUE model. Previously, Pandurangan et al. [SPAA 2018], Chang et al. [SODA 2019], and Censor-Hillel et al. [TCS 2020] showed sparsity-aware algorithms for the case of p = 3, yet ours is the first such sparsity aware algorithm for p >= 4.

关键词： Clustering algorithms

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T-Lease: A trusted lease primitive for distributed systems 11

T-Lease: A trusted lease primitive for distributed systems

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11th acm symposium on Cloud computing, SoCC 2020

作者： Trach, Bohdan Faqeh, Rasha Oleksenko, Oleksii Ozga, Wojciech Bhatotia, Pramod Fetzer, Christof TU Dresden Germany TU Munich Germany

ISBN: (纸本)9781450381376

A lease is an important primitive for building distributed protocols, and it is ubiquitously employed in distributed systems. However, the scope of the classic lease abstraction is restricted to the trusted computing infrastructure. Unfortunately, this important primitive cannot be employed in the untrusted computing infrastructure because the trusted execution environments (TEEs) do not provide a trusted time source. In the untrusted environment, an adversary can easily manipulate the system clock to violate the correctness properties of lease-based systems. We tackle this problem by introducing trusted lease - -a lease that maintains its correctness properties even in the presence of a clock-manipulating attacker. To achieve these properties, we follow a "trust but verify"approach for an untrusted timer, and transform it into a trusted timing primitive by leveraging two hardware-assisted ISA extensions (Intel TSX and SGX) available in commodity CPUs. We provide a design and implementation of trusted lease in a system called T-Lease - -the first trusted lease system that achieves high security, performance, and precision. For the application developers, T-Lease exposes an easy-to-use generic APIs that facilitate its usage to build a wide range of distributed protocols. © 2020 acm.

关键词： Clocks

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Practice-Centered HCI: Teaching in Undergraduate computing Courses in Brazil 20

Practice-Centered HCI: Teaching in Undergraduate Computing C...

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19th Brazilian symposium on Human Factors in computing Systems (IHC)

作者： Guimaraes, Tatiane Gomes Prates, Raquel Oliveira Univ Fed Minas Gerais Belo Horizonte MG Brazil

ISBN: (纸本)9781450381727

Human-Computer Interaction is a multidisciplinary field that is taught in computing undergraduate courses. Although HCI Education has been a theme for research both nationally and internationally, much of this existing research is focused on syllabi guidelines and the topics being taught. We propose an in-depth research so we can better understand how HCI is being taught in computing undergraduate courses in Brazil. For that, we chose to use the UDUM method, conducting semi-structured interviews with thirteen geographically distributed HCI professors that teach introductory courses in computing departments and courses in Brazil. Among our results, an aspect that stood out was the high value given to practice by our interviewees, which is the focus of this paper. The interviewees value conducting the course itself guided by a life cycle in HCI, walking through different phases and teaching respective methods and techniques in a practical way, where students can exercise and practice what they are learning in hands-on projects during the course.

关键词： Human-Computer Interaction HCI Education HCI Teaching computing Education HCI in Brazil

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Beyond CS principles: Bringing the Frontiers of computing to K12 21

Beyond CS Principles: Bringing the Frontiers of Computing to...

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proceedings of the 52nd acm Technical symposium on Computer Science Education

作者： Ákos Lédeczi Shuchi Grover Veronica Catete Brian Broll Vanderbilt University Nashville TN USA Looking Glass Venture Palo Alto CA USA North Carolina State University Raleigh NC USA

ISBN: (纸本)9781450380621

The AP Computer Science principles (CSP) high school course introduces students to computer science and programming. What should motivated students study after successful completion of AP CSP? The AP CSA class teaches Java programming and it has traditionally not attracted students from underrepresented groups. We are working on an alternative, projects-based course that will teach cutting edge CS concepts, such as distributed computing, computer networking, cybersecurity, the internet of things and machine learning, in a hands-on, accessible manner. Such an approach enables students to work on problems that interest them making computing more relevant and the curriculum more engaging. We utilize NetsBlox, a collaborative, block-based programming environment that extends Snap! with a few carefully selected abstractions that open up the vast array of resources freely available on the internet for student programs. Moreover, the tool enables students to work together on the same project remotely similarly to how Google Docs operate. This demonstration will introduce the environment and highlight its utility in creating distributed applications such as a shared whiteboard app and projects that access public domain scientific data sources and visualize them in various ways using online services such as Google Maps or charting. More information is available at https://***.

关键词： distributed computing block-based programming internet of things computer networking cybersecurity

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Semi-dynamic load balancing: Efficient distributed learning in non-dedicated environments 11

Semi-dynamic load balancing: Efficient distributed learning ...

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11th acm symposium on Cloud computing, SoCC 2020

作者： Chen, Chen Weng, Qizhen Wang, Wei Li, Baochun Li, Bo HKUST Hong Kong University of Toronto Canada

ISBN: (纸本)9781450381376

Machine learning (ML) models are increasingly trained in clusters with non-dedicated workers possessing heterogeneous resources. In such scenarios, model training efficiency can be negatively affected by stragglers - -workers that run much slower than others. Efficient model training requires eliminating such stragglers, yet for modern ML workloads, existing load balancing strategies are inefficient and even infeasible. In this paper, we propose a novel strategy called semi-dynamic load balancing to eliminate stragglers of distributed ML workloads. The key insight is that ML workers shall be load-balanced at iteration boundaries, being non-intrusive to intra-iteration execution. We develop LB-BSP based on such an insight, which is an integrated worker coordination mechanism that adapts workers' load to their instantaneous processing capabilities by right-sizing the sample batches at the synchronization barriers. We have custom-designed the batch sizing algorithm respectively for CPU and GPU clusters based on their own characteristics. LB-BSP has been implemented as a Python module for ML frameworks like TensorFlow and PyTorch. Our EC2 deployment confirms that LB-BSP is practical, effective and light-weight, and is able to accelerating distributed training by up to 54%. © 2020 acm.

关键词： Human resource management

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Session details: Theme: distributed systems: DAPP - Decentralized applications with blockchain, DLT and crypto-currencies track 21

Session details: Theme: Distributed systems: DAPP - Decentra...

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proceedings of the 36th Annual acm symposium on Applied computing

作者： Jean-Marc Seigneur University of Geneva Switzerland

No abstract available.

ISBN: (纸本)9781450381048

No abstract available.

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Orchestrating Fault Prediction with Live Migration and Checkpointing 20

Orchestrating Fault Prediction with Live Migration and Check...

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29th International Conference on High-Performance Parallel and distributed computing (HPDC)

作者： Behera, Subhendu Wan, Lipeng Mueller, Frank Wolf, Matthew Klasky, Scott North Carolina State Univ Raleigh NC 27695 USA Oak Ridge Natl Lab Oak Ridge TN USA

ISBN: (纸本)9781450370523

Checkpoint/Restart (C/R) is widely used to provide fault tolerance on High-Performance computing (HPC) systems. However, Parallel File System (PFS) overhead and failure uncertainty cause significant application overhead. This paper develops an adaptive multi-level C/R model that incorporates a failure prediction and analysis model, which orchestrates failure prediction, checkpointing, checkpoint frequency, and proactive live migration along with the additional benefit of Burst Buffers (BB). It effectively reduces the overheads due to failures, checkpointing, and recovery. Simulation results for the Summit supercomputer yield a reduction of approximate to 20%-86% in application overhead due to BBs, orchestrated failure prediction, and migration. We also observe a approximate to 29% decrease in checkpoint writes to BBs, which can increase the longevity of the BB storage devices.

关键词： High Performance computing Failure Prediction Resilience

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