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Proceedings of PDSW-DISCS 2018: 3rd Joint international Workshop on Parallel Data Storage and Data Intensive Scalable computing Systems, Held in conjunction with SC 2018: The international conference for High Performance computing, networking, Storage and Analysis

Proceedings of PDSW-DISCS 2018: 3rd Joint International Work...

引用

3rd IEEE/ACM Joint international Workshop on Parallel Data Storage and Data Intensive Scalable computing Systems, PDSW-DISCS 2018

ISBN: (纸本)9781728101927

The proceedings contain 8 papers. The topics discussed include: integration of burst buffer in high-level parallel I/O library for exa-scale computing era;using a robust metadata management system to accelerate scientific discovery at extreme scales;evaluation of HPC application I/O on object storage systems;pufferbench: evaluating and optimizing malleability of distributed storage;understanding SSD reliability in large-scale cloud systems;characterizing deep-learning I/O workloads in TensorFlow;toward understanding I/O behavior in HPC workflows;and methodology for the rapid development of scalable HPC data services.

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A Novel Rate Control Method for Free-viewpoint Video in MV-HEVC

A Novel Rate Control Method for Free-viewpoint Video in MV-H...

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international conference on computing, networking and Communications (ICNC)

作者： Abolfathi, Roxana Roodaki, Hoda Shirmohammadi, Shervin KN Toosi Univ Technol Comp Fac Tehran Iran Univ Ottawa Distributed & Collaborat Virtual Environm Res Lab DISCOVER Lab Ottawa ON Canada

ISBN: (纸本)9781538692233

In free-viewpoint video streaming, the available camera views and any virtual viewpoint between the camera views can be chosen by users. Since the amount of data that has to be stored or transmitted increases proportionally with the number of cameras, efficient compression of views is crucial. The Multiview extension of the High Efficiency Video Coding standard, called MV-HEVC, uses the well-known disparity-compensated prediction and advanced techniques for inter-view and inter-component prediction in order to reduce the high bandwidth requirement. But, even with the compression offered by MV-HEVC, this huge amount of data are currently beyond the capabilities of most mass consumers. In addition, the quality perception in free-viewpoint videos is different from regular videos. In free-viewpoint videos, the user should be able to see the scene from numerous different directions to cover the entire view. Hence, the higher coverage of Field of View (FOV) is more important than the quality of each view, the latter an important factor in regular videos. In this paper, we present a novel method based on MV-HEVC for rate assignment in free-viewpoint videos to overcome the discussed challenges. We use the distance between the various view directions to assign the proper rate to each view in order to provide a broader coverage of FOV for viewers. Simulation results with the Ballet and Break-dancer video sequences indicate that our proposed approach achieves a 27.06 reduction in bandwidth and 1.17 improvement in video quality in the Bjontegaard-Bitrate and Bjontegaard-PSNR scales, respectively, compared to standard MV-HEVC using the lambda-domain rate control algorithm.

关键词： MV-HEVC free-viewpoint video lambda-domain rate control field of view rate assignment

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Self-Adjusting Share-Based Countermeasure to Interest Flooding Attack in Named Data networking 12

Self-Adjusting Share-Based Countermeasure to Interest Floodi...

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IEEE Int Congr on Cybermat / 12th IEEE Int Conf on Cyber, Phys and Social Comp (CPSCom) / 15th IEEE Int Conf on Green computing and Communications (GreenCom) / 12th IEEE Int Conf on Internet of Things (iThings) / 5th IEEE Int Conf on Smart Data

作者： Pu, Cong Payne, Nathaniel Brown, Jacqueline Marshall Univ Weisberg Div Comp Sci Huntington WV 25755 USA

ISBN: (纸本)9781728129808

Due to the rapid growth of Internet traffic, increasing mobility, and stronger security requirements, today's Internet shows signs of aging. To keep pace with changes and move the Internet into the future, Named Data networking (NDN), a future Internet architecture, was proposed and has been demonstrated as a viable architecture for content distribution and widely recognized as a promising architecture for future Internet. However, NDN is not originally designed to consider the security requirement for all potential attacks, thus, NDN is vulnerable to a well-known distributed Denial-of-Service (DDoS) attack that primarily targets service availability by flooding the network and obstructing the service received by legitimate users. In this paper, we propose a self-adjusting share-based countermeasure, also referred to as SSC, against Interest flooding attack in NDN, where the attacker issues an excessive number of non-satisfiable Interest packets to drop legitimate Interest packets by overwhelming Pending Interest Table in NDN routers. In the SSC, each router maintains an Interest unsatisfaction ratio and dynamically adjusts the share of forwarded Interest packets for each incoming interface accordingly. In addition, the Interest packets that pass the assigned share of forwarded Interest packets are used as scouts to investigate unknown paths to complement routing information. We conduct extensive simulation experiments for performance evaluation and comparison with the existing constant share based approach. The simulation results show that the proposed countermeasure can not only improve the Pending Interest Table utilization ratio of legitimate Interest packets, but also reduce the number of accepted malicious Interest packets, indicating a viable approach against Interest flooding attack in NDN.

关键词： Network Security Named Data networking Interest Flooding Attack distributed Denial-of-Service Attack

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A Blockchain Based Framework Secured by ECDSA to Curb Drug Counterfeiting 10

A Blockchain Based Framework Secured by ECDSA to Curb Drug C...

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10th international conference on computing, Communication and networking Technologies (ICCCNT)

作者： Sahoo, Monalisa Singhar, Sunil Samanta Nayak, Biswojit Mohanta, Bhabendu Kumar UTKAL UNIV Bhubaneswar 751004 Odisha India IIIT Bhubaneswar Bhubaneswar 751003 Odisha India

ISBN: (纸本)9781538659069

Drug counterfeit has become a global issue. The counterfeit problem has become so huge that it has drawn a significant attention among researchers and policy makers. The fake drug industry is worth of 10 billion dollar per year as estimated by 'ASSOCHAM' in 2017. Also estimated by WHO about a million die per year due to fake drugs. The dispensation of fake drugs is the pivotal concern, specially in developing countries like India. One of main reason in drug counterfeiting is imperfect supply chain. There are many loop holes in our current policy of drug supply chain management system. In the present scenario of supply chain, either the information is not shared between the parties during the hand off process at all or a little or irrelevant information is shared. Once a party transfer the drug to another party, the first party doesn't know what happens to the drugs there after. The counterfeit drug not only affect the health condition of patient or the financial loss of genuine manufacturer but also it is posing serious threat to the socio-economic status of the society. In this paper, we explain details of the drug counterfeit along with a little history of the pharmacy industry and its impact on different areas and also to counter the counterfeits using Blockchain technology. Using Blockchain technology we explained here how to add traceability, visibility, and security to the drug supply chain. This proposed system will track the drugs from its origin from the manufacturer to the end the consumer.

关键词： distributed Architecture Drugs Supply chain Security Traceability Blockchain Drug Counterfeit

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AID: Efficient Prediction of Aggregated Intensity of Dependency in Large-scale Cloud Systems 21

AID: Efficient Prediction of Aggregated Intensity of Depende...

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IEEE international conference on Automated Software Engineering (ASE)

作者： Tianyi Yang Jiacheng Shen Yuxin Su Xiao Ling Yongqiang Yang Michael R. Lyu The Chinese University of Hong Kong Hong Kong China Computing and Networking Innovation Lab Cloud BU Huawei

ISBN: (纸本)9781665447843

Service reliability is one of the key challenges that cloud providers have to deal with. In cloud systems, unplanned service failures may cause severe cascading impacts on their dependent services, deteriorating customer satisfaction. Predicting the cascading impacts accurately and efficiently is critical to the operation and maintenance of cloud systems. Existing approaches identify whether one service depends on another via distributed tracing but no prior work focused on discriminating to what extent the dependency between cloud services is. In this paper, we survey the outages and the procedure for failure diagnosis in two cloud providers to motivate the definition of the intensity of dependency. We define the intensity of dependency between two services as how much the status of the callee service influences the caller service. Then we propose AID, the first approach to predict the intensity of dependencies between cloud services. AID first generates a set of candidate dependency pairs from the spans. AID then represents the status of each cloud service with a multivariate time series aggregated from the spans. With the representation of services, AID calculates the similarities between the statuses of the caller and the callee of each candidate pair. Finally, AID aggregates the similarities to produce a unified value as the intensity of the dependency. We evaluate AID on the data collected from an open-source microservice benchmark and a cloud system in production. The experimental results show that AID can efficiently and accurately predict the intensity of dependencies. We further demonstrate the usefulness of our method in a large-scale commercial cloud system.

关键词： Aggregates Time series analysis Microservice architectures Production Maintenance engineering Benchmark testing Reliability engineering

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INEC: Fast and Coherent In-Network Erasure Coding 20

INEC: Fast and Coherent In-Network Erasure Coding

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Supercomputing conference

作者： Haiyang Shi Xiaoyi Lu The Ohio State University

ISBN: (数字)9781728199986

ISBN: (纸本)9781728199993

Erasure coding (EC) is a promising fault tolerance scheme that has been applied to many well-known distributed storage systems. The capability of Coherent EC Calculation and networking on modern SmartNICs has demonstrated that EC will be an essential feature of in-network computing. In this paper, we propose a set of coherent in-network EC primitives, named INEC. Our analyses based on the proposed α-β performance model demonstrate that INEC primitives can enable different kinds of EC schemes to fully leverage the EC offload capability on modern SmartNICs. We implement INEC on commodity RDMA NICs and integrate it into five state-of-the-art EC schemes. Our experiments show that INEC primitives significantly reduce 50 th , 95 th , and 99 th percentile latencies, and accelerate the end-to-end throughput, write, and degraded read performance of the key-value store co-designed with INEC by up to 99.57%, 47.30%, and 49.55%, respectively.

关键词： Fault tolerance High performance computing Computational modeling Fault tolerant systems Throughput Encoding Next generation networking

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Solving PDEs in Space-Time: 4D Tree-Based Adaptivity, Mesh-Free and Matrix-Free Approaches 19

Solving PDEs in Space-Time: 4D Tree-Based Adaptivity, Mesh-F...

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international conference for High Performance computing, networking, Storage and Analysis (SC)

作者： Ishii, Masado Fernando, Milinda Saurabh, Kumar Khara, Biswajit Ganapathysubramanian, Baskar Sundar, Hari Univ Utah Salt Lake City UT 84112 USA Iowa State Univ Ames IA USA

ISBN: (数字)9781450362290

ISBN: (纸本)9781450362290

Numerically solving partial differential equations (PDEs) remains a compelling application of supercomputing resources. The next generation of computing resources - exhibiting increased parallelism and deep memory hierarchies- provide an opportunity to rethink how to solve PDEs, especially time dependent PDEs. Here, we consider time as an additional dimension and simultaneously solve for the unknown in large blocks of time (i.e. in 4D space-time), instead of the standard approach of sequential time-stepping. We discretize the 4D space-time domain using a mesh-free kD tree construction that enables good parallel performance as well as on-the-fly construction of adaptive 4D meshes. To best use the 4D space-time mesh adaptivity, we invoke concepts from PDE analysis to establish rigorous a posteriori error estimates for a general class of PDEs. We solve canonical linear as well as non-linear PDEs (heat diffusion, advection-diffusion, and Allen-Cahn) in space-time, and illustrate the following advantages: (a) sustained scaling behavior across a larger processor count compared to sequential time-stepping approaches, (b) the ability to capture "localized" behavior in space and time using the adaptive space-time mesh, and (c) removal of any time-stepping constraints like the Courant-Friedrichs-Lewy (CFL) condition, as well as the ability to utilize spatially varying time-steps. We believe that the algorithmic and mathematical developments along with efficient deployment on modern architectures shown in this work constitute an important step towards improving the scalability of PDE solvers on the next generation of supercomputers.

关键词： 4D space-time adaptive sedectree mesh-free matrix-free finite element method distributed memory parallel

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Proceedings of ESPM2 2018: 4th international Workshop on Extreme Scale Programming Models and Middleware, Held in conjunction with SC 2018: The international conference for High Performance computing, networking, Storage and Analysis

Proceedings of ESPM2 2018: 4th International Workshop on Ext...

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4th IEEE/ACM international Workshop on Extreme Scale Programming Models and Middleware, ESPM2 2018

ISBN: (纸本)9781728101781

The proceedings contain 8 papers. The topics discussed include: distributed memory futures for compile-time, deterministic-by-default concurrency in distributed C++ applications;design of data management for multi SPMD workflow programming model;integration of CUDA processing within the C++ library for parallelism and concurrency (HPX);automatic generation of high-order finite-difference code with temporal blocking for extreme-scale many-core systems;asynchronous execution of python code on task-based runtime systems;a unified runtime for PGAS and event-driven programming;portable and reusable deep learning infrastructure with containers to accelerate cancer studies;and analysis of explicit vs. implicit tasking in OpenMP using Kripke.

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CrowdLearn: A Crowd-AI Hybrid System for Deep Learning-based Damage Assessment Applications 39

CrowdLearn: A Crowd-AI Hybrid System for Deep Learning-based...

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39th IEEE international conference on distributed computing Systems (ICDCS)

作者： Zhang, Daniel (Yue) Zhang, Yang Li, Qi Plummer, Thomas Wang, Dong Univ Notre Dame Dept Comp Sci & Engn Notre Dame IN 46556 USA

ISBN: (纸本)9781728125190

Artificial Intelligence (AI) has been widely adopted in many important application domains such as speech recognition, computer vision, autonomous driving, and AI for social good. In this paper, we focus on the AI-based damage assessment applications where deep neural network approaches are used to automatically identify damage severity of impacted areas from imagery reports in the aftermath of a disaster (e.g., earthquake, hurricane, landslides). While AI algorithms often significantly reduce the detection time and labor cost in such applications, their performance sometimes falls short of the desired accuracy and is considered to be less reliable than domain experts. To exacerbate the problem, the black-box nature of the AI algorithms also makes it difficult to troubleshoot the system when their performance is unsatisfactory. The emergence of crowdsourcing platforms (e.g., Amazon Mechanic Turk, Waze) brings about the opportunity to incorporate human intelligence into AI algorithms. However, the crowdsourcing platform is also black-box in terms of the uncertain response delay and crowd worker quality. In this work, we propose the CrowdLearn, a crowd-AI hybrid system that leverages the crowdsourcing platform to troubleshoot, tune, and eventually improve the black-box AI algorithms by welding crowd intelligence with machine intelligence. The system is specifically designed for deep learning-based damage assessment (DDA) applications where the crowd tend to be more accurate but less responsive than machines. Our evaluation results on a real-world case study on Amazon Mechanic Turk demonstrate that CrowdLearn can provide timely and more accurate assessments to natural disaster events than the state-of-the-art AI-only and human-AI integrated systems.

关键词： Artificial intelligence Crowdsourcing Reliability Task analysis Delays Social networking (online) Training data

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Differentiated Service Mechanism According to Vehicle Environment in Vehicular Edge Network 15

Differentiated Service Mechanism According to Vehicle Enviro...

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15th IEEE international Wireless Communications and Mobile computing conference (IEEE IWCMC)

作者： Tan, Zuoyan Rui, LanLan Li, Wenjing Qiu, Xuesong Guo, Shaoyong Yu, Xiuzhi Beijing Univ Posts & Telecommun State Key Lab Networking & Switching Technol Beijing Peoples R China China Elect Standardizat Inst Beijing Peoples R China

ISBN: (纸本)9781538677476

With the rapid development of communication technologies such as 5G, vehicular information and applications are exploding. Mobile edge computing (MEC) as a new technology can transfer the information more quickly and accurately. Providing differentiated services for the information can affect the performance of the applications. In this study, based on 802.11p EDCA protocol, we propose a new differentiated service scheme called DD-EDCA (Differentiating Density Enhanced distributed Channel Access). Firstly, we use MEC Server to estimate the road density. Secondly, different solutions have been designed according to different vehicle density environment requirements. For example, the displacement trend is considered at a low density, and the multi-hop broadcast information is pre-processed at a high density. And the schemes for dynamically adjusting EDCA parameters are designed. Simulation results show that our method reduces latency and packet loss rate, and improves the throughput.

关键词： vehicular edge network transmission information differentiated services QoS

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