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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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Wukong: A scalable and locality-enhanced framework for serverless parallel computing 11

Wukong: A scalable and locality-enhanced framework for serve...

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11th acm symposium on Cloud computing, SoCC 2020

作者： Carver, Benjamin Zhang, Jingyuan Wang, Ao Anwar, Ali Wu, Panruo Cheng, Yue George Mason University United States IBM Research-Almaden United States University of Houston United States

ISBN: (纸本)9781450381376

Executing complex, burst-parallel, directed acyclic graph (DAG) jobs poses a major challenge for serverless execution frameworks, which will need to rapidly scale and schedule tasks at high throughput, while minimizing data movement across tasks. We demonstrate that, for serverless parallel computations, decentralized scheduling enables scheduling to be distributed across Lambda executors that can schedule tasks in parallel, and brings multiple benefits, including enhanced data locality, reduced network I/Os, automatic resource elasticity, and improved cost effectiveness. We describe the implementation and deployment of our new serverless parallel framework, called Wukong, on AWS Lambda. We show that Wukong achieves near-ideal scalability, executes parallel computation jobs up to 68.17X faster, reduces network I/O by multiple orders of magnitude, and achieves 92.96% tenant-side cost savings compared to numpywren. © 2020 acm.

关键词： Cost effectiveness

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distributed resource allocation with multi-agent deep reinforcement learning for 5G-V2V communication 20

Distributed resource allocation with multi-agent deep reinfo...

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21st acm International symposium on Mobile Ad Hoc Networking and computing, MobiHoc 2020

作者： Gündogan, Alperen Murat Gürsu, H. Pauli, Volker Kellerer, Wolfgang Nomor Research and Technical University of Munich Munich Germany Technical University of Munich Munich Germany

ISBN: (纸本)9781450380157

We consider the distributed resource selection problem in Vehicle-to-vehicle (V2V) communication in the absence of a base station. Each vehicle autonomously selects transmission resources from a pool of shared resources to disseminate Cooperative Awareness Messages (CAMs). This is a consensus problem where each vehicle has to select a unique resource. The problem becomes more challenging when-due to mobility-the number of vehicles in vicinity of each other is changing dynamically. In a congested scenario, allocation of unique resources for each vehicle becomes infeasible and a congested resource allocation strategy has to be developed. The standardized approach in 5G, namely semi-persistent scheduling (SPS) suffers from effects caused by spatial distribution of the vehicles. In our approach, we turn this into an advantage. We propose a novel distributed Resource Allocation mechanism using multi-agent reinforcement Learning (DIRAL) which builds on a unique state representation. One challenging issue is to cope with the non-stationarity introduced by concurrently learning agents which causes convergence problems in multi-agent learning systems. We aimed to tackle non-stationarity with unique state representation. Specifically, we deploy view-based positional distribution as a state representation to tackle non-stationarity and perform complex joint behavior in a distributed fashion. Our results showed that DIRAL improves PRR by 20% compared to SPS in challenging congested scenarios. © 2020 acm.

关键词： Reinforcement learning

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Towards HPC I/O Performance Prediction Through Large-scale Log Analysis 20

Towards HPC I/O Performance Prediction Through Large-scale L...

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

作者： Kim, Sunggon Sim, Alex Wu, Kesheng Byna, Suren Son, Yongseok Eom, Hyeonsang Seoul Natl Univ Seoul South Korea Lawrence Berkeley Natl Lab Berkeley CA USA Chung Ang Univ Seoul South Korea

ISBN: (纸本)9781450370523

Large-scale high performance computing (HPC) systems typically consist of many thousands of CPUs and storage units, while used by hundreds to thousands of users at the same time. Applications from these large numbers of users have diverse characteristics, such as varying compute, communication, memory, and I/O intensiveness. A good understanding of the performance characteristics of each user application is important for job scheduling and resource provisioning. Among these performance characteristics, the I/O performance is difficult to predict because the I/O system software is complex, the I/O system is shared among all users, and the I/O operations also heavily rely on networking systems. To improve the prediction of the I/O performance on HPC systems, we propose to integrate information from a number of different system logs and develop a regression-based approach that dynamically selects the most relevant features from the most recent log entries, and automatically select the best regression algorithm for the prediction task. Evaluation results show that our proposed scheme can predict the I/O performance with up to 84% prediction accuracy in the case of the I/O-intensive applications using the logs from CORI supercomputer at NERSC.

关键词： High Performance computing distributed File System I/O Performance Prediction Log Analysis

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Architectural principles for Autonomous Microservices 53

Architectural Principles for Autonomous Microservices

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53rd Annual Hawaii International Conference on System Sciences (HICSS)

作者： Mikkelsen, Anders Gronli, Tor-Morten Tamburri, Damian A. Kaman, Rick Systek Oslo Norway Kristiania Univ Coll Mobile Technol Lab Dept Technol Oslo Norway Tech Univ Eindhoven Jheronimus Acad Data Sci Eindhoven Netherlands Univ Hawaii Schidler Coll Business Honolulu HI USA

ISBN: (纸本)9780998133133

In the last decade architectural patterns like microservices and event-driven architectures have emerged to meet the challenges of distributed computing. This paper explores recent practices and research in microservice- and event-driven architectures to identify the challenges in architecting such systems. With a proof-of-concept study approach, we distilled a set of design principles to address these challenges, creating asynchronous and agnostic microservice architectures. Further, we provide a generic toolkit for implementing such architectures. An example of this architecture was implemented in the company TechnipFMC. Concurrently, an architecture trade-off analysis was performed using a utility-tree based approach, highlighting the impact and importance of our proposed principles and their generalizability. The evaluation provides evidence for the viability of the proposed design principles.

关键词： Economic and social effects

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Hardness of Minimal Symmetry Breaking in distributed computing 19

Hardness of Minimal Symmetry Breaking in Distributed Computi...

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38th acm symposium on principles of distributed computing (PODC)

作者： Balliu, Alkida Hirvonen, Juho Olivetti, Dennis Suomela, Jukka Aalto Univ Helsinki Finland

ISBN: (纸本)9781450362177

A graph is weakly 2-colored if the nodes are labeled with colors black and white such that each black node is adjacent to at least one white node and vice versa. In this work we study the distributed computational complexity of weak 2-coloring in the standard LOCAL model of distributed computing, and how it is related to the distributed computational complexity of other graph problems. First, we show that weak 2-coloring is a minimal distributed symmetry-breaking problem for regular even-degree trees and highgirth graphs: if there is any non-trivial locally checkable labeling problem that is solvable in o(log* n) rounds with a distributed graph algorithm in the middle of a regular even-degree tree, then weak 2-coloring is also solvable in o(log* n) rounds there. Second, we prove a tight lower bound of Omega(log* n) for the distributed computational complexity of weak 2-coloring in regular trees;previously only a lower bound of Omega(log log* n) was known. By minimality, the same lower bound holds for any non-trivial locally checkable problem inside regular even-degree trees.

关键词： distributed complexity theory graph algorithms locally checkable labelings LOCAL model

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GTSS-UC: a game theoretic approach for services' selection in UAV clouds 21

GTSS-UC: a game theoretic approach for services' selection i...

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

作者： Fatima Zohra Bousbaa Abderrahmane Lakas Aboubakeur Elseddik Rezigat Hadj Saad Benguettache Nasreddine Lagraa Chaker Abdelaziz Kerrache Abdou El Karim Tahari Université de Laghouat Laghouat Algeria UAE University UAE

ISBN: (纸本)9781665433266

Unmanned Aerial Vehicles (UAVs) cloud have attracted wide attentions from both industrial and academic communities as a new paradigm offering flexible services. This new concept utilizes the recent technologies of mobile cloud computing. The collaboration between these technologies represents a fantastic vision of the future, where everything is connected to the Internet, thereby offering intelligent services and facilitating decision-making between cooperative UAVs. In this work, we study the UAVs clouds computing services selection strategies. Our objectives are to (1) provide a detailed review of the existing services' selection methods and to (2) propose a new Game Theoretic approach for Selection of Services in UAV Clouds (GTSS-UC) aiming to enable normal users to select the most suitable UAV-Service-Provider. Given that every service' provider is characterized by specific features, limitations, and prices, a user must select the most suitable provider. The technique of selection is based on the Game Theory (GT) method and takes into account the user requirements and the UAVs provider qualities to find the most adequate provider. The results of the simulation conducted using NS-2 simulator advocate for the efficiency of our method in both network Quality-of-Service and Service gain.

关键词： services' selection game theory method cloud computing UAVs GTSS-UC

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Evaluation of large scale RoI mining applications in edge computing environments 21

Evaluation of large scale RoI mining applications in edge co...

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

作者： Loris Belcastro Alberto Falcone Alfredo Garro Fabrizio Marozzo University of Calabria Italy

ISBN: (纸本)9781665433266

Researchers and leading IT companies are increasingly proposing hybrid cloud/edge solutions, which allow to move part of the workload from the cloud to the edge nodes, by reducing the network traffic and energy consumption, but also getting low latency responses near to real time. This paper proposes a novel hybrid cloud/edge architecture for efficiently extracting Regions-of-Interest (RoI) in a large scale urban computing environment, where a huge amount of geotagged data are generated and collected through users's mobile devices. The proposal is organized in two parts: (i) a modeling part that defines the hybrid cloud/edge architecture capable of managing a large number of devices; (ii) a simulation part in which different design choices are evaluated to improve the performance of RoI mining algorithms in terms of processing time, network delay, task failure and computing resource utilization. Several experiments have been carried out to evaluate the performance of the proposed architecture starting from different configurations and orchestration policies. The achieved results showed that the proposed hybrid cloud/edge architecture, with the use of two novel orchestration policies (network- and utilization-based), permits to improve the exploitation of resources, also granting low network latency and task failure rate in comparison with other standard scenarios (only-edge or only-cloud).

关键词： RoI mining orchestration policies IoT platforms cloud/edge architecture modeling and simulation

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2020 IEEE/acm 28th International symposium on Quality of Service, IWQoS 2020

2020 IEEE/ACM 28th International Symposium on Quality of Ser...

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28th IEEE/acm International symposium on Quality of Service, IWQoS 2020

ISBN: (纸本)9781728168876

The proceedings contain 49 papers. The topics discussed include: PE-HEALTH: enabling fully encrypted CNN for health monitor with optimized communication;decode-and-compare: an efficient verification scheme for coded edge computing;network-based malware detection with a two-tier architecture for online incremental update;incentive assignment in PoW and PoS hybrid blockchain in pervasive edge environments;private deep neural network models publishing for machine learning as a service;supporting multi-dimensional and arbitrary numbers of ranks for software packet scheduling;BioDraw: reliable multi-factor user authentication with one single finger swipe;and GeoClone: online task replication and scheduling for geo-distributed analytics under uncertainties.

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Online scheduling of heterogeneous distributed machine learning jobs 20

Online scheduling of heterogeneous distributed machine learn...

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21st acm International symposium on Mobile Ad Hoc Networking and computing, MobiHoc 2020

作者： Zhang, Qin Zhou, Ruiting Wu, Chuan Jiao, Lei Li, Zongpeng Wuhan University China Chinese University of Hong Kong Hong Kong Hong Kong University of Hong Kong Hong Kong Hong Kong University of Oregon United States

ISBN: (纸本)9781450380157

distributed machine learning (ML) has played a key role in today's proliferation of AI services. A typical model of distributed ML is to partition training datasets over multiple worker nodes to update model parameters in parallel, adopting a parameter server architecture. ML training jobs are typically resource elastic, completed using various time lengths with different resource configurations. A fundamental problem in a distributed ML cluster is how to explore the demand elasticity of ML jobs and schedule them with different resource configurations, such that the utilization of resources is maximized and average job completion time is minimized. To address it, we propose an online scheduling algorithm to decide the execution time window, the number and the type of concurrent workers and parameter servers for each job upon its arrival, with a goal of minimizing the weighted average completion time. Our online algorithm consists of (i) an online scheduling framework that groups unprocessed ML training jobs into a batch iteratively, and (ii) a batch scheduling algorithm that configures each ML job to maximize the total weight of scheduled jobs in the current iteration. Our online algorithm guarantees a good parameterized competitive ratio with polynomial time complexity. Extensive evaluations using real-world data demonstrate that it outperforms state-of-the-art schedulers in today's AI cloud systems. © 2020 acm.

关键词： Machine learning

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AR-Chat: an AR-based instant messaging system

AR-Chat: an AR-based instant messaging system

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19th IEEE International symposium on Mixed and Augmented Reality (ISMAR)

作者： Jouet, Pierrick Alleaume, Vincent Laurent, Anthony Fradet, Matthieu Luo, Tao Baillard, Caroline InterDigital Rennes France

ISBN: (纸本)9781728176758

We describe a multi-user system enabling instant messaging in Augmented Reality. A user can get in contact with another one without requiring his/her identification number and can easily localize the person initiating the contact. It is also possible to exchange various types of personal information in a private manner. This innovative type of social interaction can significantly increase consumer interest for AR experiences.

关键词： Human-centered computing Human computer interaction (HCI) Interaction paradigms Mixed / augmented reality Computer systems organization Architectures distributed architectures Client-server architectures

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