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Global Stabilization for Causally Consistent Partial Replication 20

Global Stabilization for Causally Consistent Partial Replica...

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21st international conference on distributed computing and networking (ICDCN)

作者： Xiang, Zhuolun Vaidya, Nitin H. Univ Illinois Dept Comp Sci Champaign IL 61820 USA Georgetown Univ Dept Comp Sci Washington DC 20057 USA

ISBN: (纸本)9781450377515

Causally consistent distributed storage systems have received significant attention due to the potential for providing high throughput. Global stabilization is a technique established for achieving causal consistency in distributed multi-version key-value store systems, adopted by previous works such as GentleRain [6] and Cure [1]. However, previous designs with global stabilization assume full replication, where the set of the data is split into partitions with each partition replicated at all data centers, and each client is restricted to access servers within only one data center. In this paper, we propose a theoretical framework of global stabilization to support general partial replication with causal consistency, where each server can store an arbitrary subset of the data, and each client is allowed to communicate with any subset of the servers and migrate among them without extra delays. We propose an algorithm that implements causal consistency for distributed multi-version key-value stores with general partial replication, and our algorithm is optimal in terms of the remote update visibility latency, i.e. how fast update from a remote server is visible to the client, under general partial replication. Simulation results on the performance of our algorithm compared to the previous work are also provided.

关键词： distributed shared memory causal consistency partial replication

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Cloud Secure Storage Mechanism Based on Data Dispersion and Encryption 22

Cloud Secure Storage Mechanism Based on Data Dispersion and ...

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Proceedings of the 4th international conference on Information Management & Machine Intelligence

作者： EZHIL Vijayarangan V S Metilda Florence Computer Science SRM university India Deptartment of Networking and Communications Srm university India

ISBN: (纸本)9781450399937

The widespread use and significant capability of the cloud storage service have demonstrated how important it is to the quick growth of cloud computing. However, there are still important security incidents that happen as a result of management negligence and malicious attack, resulting in the release of sizable amounts of sensitive data in the cloud storage tier. This paper proposes a CSSM, or secure cloud storage mechanism, to guarantee the confidentiality of data saved in the cloud. A technique to prevent data leakage at the storage layer was added by CSSM. Encrypted, scattered, and distributed storage is carried out via data dispersion and dispersed storage. In order to avoid the leaking of cryptographic materials, CSSM also adopted a hierarchical management strategy and coupled the user password with the exchange of secrets. The experimental findings suggest that the suggested mechanism. It can store a lot of cloud data efficiently without adding a lot of overhead, making it excellent for protecting data security in the storage layer against leaking. Users find it acceptable that it only takes 646 seconds to upload or download a 5G-size file with CSSM.

关键词： Data displacement

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Big Data Solutions Proposed for Cluster computing Systems Challenges: A survey 2020

Big Data Solutions Proposed for Cluster Computing Systems Ch...

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3rd international conference on networking, Information System and Security (NISS)

作者： Es-Sabery, Fatima Hair, Abdellatif Sultan Moulay Slimane Univ LMACS Fac Sci & Technol BP 523 Beni Mellal Morocco

ISBN: (纸本)9781450376341

CCS (Cluster computing System) is coming to solve the problems of standard technology. Whose, objective is to improve the performance/power efficiency of a single processor for storing and mining the large data sets, using the parallel programming to read and process the massive data sets on multiple disks and CPUs. The thing which makes these systems somewhat performant than the standard technology is the physical organization of computing nodes in the cluster. Currently, this kind of cluster does not entirely solve the problem because it comes with its challenges, which are Node failures, Computations, Network Bottleneck, and distributed programming. All these problems are coming when we are mining and storing the massive volume of data using cluster computing. To solve these challenges, Google invented a new Big Data framework of data processing called MapReduce, to manage large scale data processing across large clusters of commodity servers. The paper outlines the running of CCS and presents its challenges in this era of Big Data. Moreover, it introduces the most popular Big Data solutions proposed to overcome the CCS challenges. Also, it shows how Big Data technologies solve CCS issues. Generally, the main goal of this work is to provide a better understanding of the challenges of CCS and identify the essential big data solutions in this increasingly important area.

关键词： CCS Challenges Big Data MapReduce distributed File System

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8th international Symposium on Security in computing and Communications, SSCC 2020

8th International Symposium on Security in Computing and Com...

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8th international Symposium on Security in computing and Communications, SSCC 2020

ISBN: (纸本)9789811604218

The proceedings contain 21 papers. The special focus in this conference is on Security in computing and Communications. The topics include: Benchmarking Behavior-Based Intrusion Detection Systems with Bio-inspired Algorithms;thermal Management in Large Data Centres: Security Threats and Mitigation;Anomaly Detection in CAN-BUS Using Pattern Matching Algorithm;conjunctive Keyword Forward Secure Ranked Dynamic Searchable Encryption Over Outsourced Encrypted Data;performance Study of Multi-target Tracking Using Kalman Filter and Hungarian Algorithm;saaS - Microservices-Based Scalable Smart Contract Architecture;GIDS: Anomaly Detection Using Generative Adversarial Networks;Audio Steganography Using Multi LSB and IGS Techniques;A Forensic Analysis on the Availability of MQTT Network Traffic;a Communication-Induced Checkpointing Algorithm for Consistent-Transaction in distributed Database Systems;the Concerns of Personal Data Privacy, on Calling and Messaging, networking Applications;analysis of Orthogonal Time Frequency Space Transceiver in Baseband Environment;evading Static and Dynamic Android Malware Detection Mechanisms;multilevel Secure Container Deployment Framework in Edge computing;deep Hierarchical App Recommendation with Dynamic Behaviors;New Security Architecture of Access Control in 5G MEC;a Fast Authentication Scheme for Cross-Network-Slicing Based on Multiple Operators in 5G Environments;A Survey of Security Attacks on Silicon Based Weak PUF Architectures;on the Feasibility of DoS Attack on Smart Door Lock IoT Network.

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Digital Cloud Platform of distributed Data Storage in Sphere of Higher Education 13

Digital Cloud Platform of Distributed Data Storage in Sphere...

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13th international ELEKTRO conference (ELEKTRO)

作者： Perepelkin, Dmitry Saprykin, Aleksey Ivanchikova, Maria Kosorukov, Sergey Ryazan State Radio Engn Univ Fac Comp Engn Ryazan Russia

ISBN: (纸本)9781728175423

Current trends, such as an increase in the number of devices connected to the Internet, an exponential increase in the volume of information, the development of network and cloud technologies, are changing all areas of activity. The global increase in network traffic dictates the need for business to configure large-scale computing systems and networks. To introduce new digital services in various fields, innovative approaches to building computing infrastructures meant for the processing, transmission and storage of large data arrays are needed. The aim of this work is to develop a software component for building a digital cloud platform for distributed data storage in higher education. Current work proposes an architecture and software tools for distributed processing and storage of user data on a digital cloud platform of a higher educational institution. The main class diagrams of the developed cloud platform and the principles of interaction of its main components are described in detail. The functioning process and the features of building a network infrastructure of the developed digital cloud platform for distributed data storage are considered. The developed digital cloud platform implements the capabilities of immediate connection and deployment of new digital services through the use of a wide range of software components and open APIs.

关键词： distributed computing distributed data storage cloud computing digital cloud platform software defined networking

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Dynamic Taxi Ride Sharing using Localized Communication 20

Dynamic Taxi Ride Sharing using Localized Communication

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21st international conference on distributed computing and networking (ICDCN)

作者： Yu, Haoxiang Raychoudhury, Vaskar Silwal, Shrawani Miami Univ Dept Comp Sc & SW Engn Oxford OH 45056 USA

ISBN: (纸本)9781450377515

With the rise of on-demand taxi services, like Uber, Lyft, etc., urban public transportation started to heavily depend on taxicabs. While increasing demand leads to passenger stranding, higher supply may result in traffic congestion. In order to strike a balance ride sharing plays an important role. However, scheduling a ride on-the-fly is extremely challenging and more so with increasing number of passengers. It is non-trivial to find a driving route for the taxi accommodating multiple passengers without extending their journey time beyond a pre-specified tolerance value. The spatio-temporal separation of passengers and high mobility of taxis even more complicates shared ride scheduling. Existing distributed ride sharing solutions failed to address the extremely dynamic nature of the underlying topology where taxis are continuously moving and hence, results in message loss. In this paper, we have proposed a purely distributed ride sharing algorithm aimed at addressing the dynamics of taxi topology using asynchronous localized communication between passengers and taxis. Empirical analysis using large scale single-user taxi ride records from Chicago, show that, our proposed algorithm, ensures a maximum of 76% success in ride sharing and a 97.5% taxi occupancy rate during peak operating hours.

关键词： Taxi ride sharing Smart Transportation distributed Coordination Data Analysis GPS traces

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WSN Data Collection and Routing Protocol with Time Synchronization in Low-cost IoT Environment 18

WSN Data Collection and Routing Protocol with Time Synchroni...

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18th international conference on Mobile Systems and Pervasive computing, MobiSPC 2021, The 16th international conference on Future Networks and Communications, FNC 2021 and the 11th international conference on Sustainable Energy Information Technology, SEIT 2021

作者： Co, Kimberly Jane Ong, Arlyn Verina Peradilla, Marnel Advanced Research Institute for Informatics Computing and Networking De la Salle University 2401 Taft Ave. Philippines Manila City1004 Philippines Computer Technology Department College of Computer Studies De la Salle University 2401 Taft Ave. Philippines Manila City1004 Philippines

The Internet of Things (IoT) is rapidly growing as a topic of research and conversation. IoT includes monitoring applications such as environment, healthcare, and military, requiring real-time gathering and data delivery. In dealing with time-sensitive applications, time synchronization is essential to collaborative wireless sensor network (WSN) nodes' data collection and routing information sharing. This paper proposes an ad hoc routing and data collection protocol with a time synchronization function. A hybrid packet-based time synchronization is introduced, wherein reference time is sourced from the sink node (centralized) and sourced from the adjacent nodes (distributed). The time synchronization process is integrated into the routing and data transmissions in the network as it lessens overheads and transmission exchanges, which would be beneficial for large-scale WSN. Finally, we evaluate the protocol's performance using a realistic low-cost WSN testbed. Our proposed protocol has achieved an averaged time offset of less than 100 milliseconds for a 15-minute test duration in multiple topology scenarios. © 2021 Elsevier B.V.. All rights reserved.

关键词： Internet of things

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HeAT - a distributed and GPU-accelerated Tensor Framework for Data Analytics 8

HeAT - a Distributed and GPU-accelerated Tensor Framework fo...

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8th IEEE international conference on Big Data (Big Data)

作者： Goetz, Markus Debus, Charlotte Coquelin, Daniel Krajsek, Kai Comito, Claudia Knechtges, Philipp Hagemeier, Bjorn Tarnawa, Michael Hanselmann, Simon Siggel, Martin Basermann, Achim Streit, Achim German Aerosp Ctr Inst Software Technol SC Cologne Germany Forschungszentrum Julich Inst Rio & Geosci Agrosphere IBG 3 Julich Germany Forschungszentrum Julich FZJ Julich Supercomp Ctr JSC Julich Germany Karlsruhe Inst Technol KIT Steinbuch Ctr Comp SCC Karlsruhe Germany

ISBN: (纸本)9781728162515

To cope with the rapid growth in available data, the efficiency of data analysis and machine learning libraries has recently received increased attention. Although great advancements have been made in traditional array-based computations, most are limited by the resources available on a single computation node. Consequently, novel approaches must be made to exploit distributed resources, e.g. distributed memory architectures. To this end, we introduce IleAT, an array-based numerical programming framework for large-scale parallel processing with an easy-to-use NumPy-like API. HeAT utilizes PyTorch as a node-local eager execution engine and distributes the workload on arbitrarily large high-performance computing systems via MPI. It provides both low-level array computations, as well as assorted higher-level algorithms. With HeAT, it is possible for a NumPy user to take full advantage of their available resources, significantly I owering the bartier to distributed data analysis. When compared to similar frameworks, HeAT achieves speedups of up to two orders of magnitude.

关键词： IleAT Tensor Framework High-performance computing PyTorch NumPy Message Passing Interface CPU Rig Data Analytics Machine Learning Dask Model Parallelism Parallel Application Frameworks

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RDMP-KV: Designing Remote Direct Memory Persistence based Key-Value Stores with PMEM

RDMP-KV: Designing Remote Direct Memory Persistence based Ke...

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

作者： Li, Tianxi Shankar, Dipti Gugnani, Shashank Lu, Xiaoyi Ohio State Univ Dept Comp Sci & Engn Columbus OH 43210 USA

ISBN: (纸本)9781728199986

Byte-addressable persistent memory (PMEM) can be directly manipulated by Remote Direct Memory Access (RDMA) capable networks. However, existing studies to combine RDMA and PMEM can not deliver the desired performance due to their PMEM-oblivious communication protocols. In this paper, we propose novel PMEM-aware RDMA-based communication protocols for persistent key-value stores, referred to as Remote Direct Memory Persistence based Key-Value stores (RDMP-KV). RDMP-KV employs a hybrid 'server-reply/server-bypass' approach to 'durably' store individual key-value objects on PMEM-equipped servers. RDMP-KV's runtime can easily adapt to existing (server-assisted durability) and emerging (appliance durability) RDMA-capable interconnects, while ensuring server scalability through a lightweight consistency scheme. Performance evaluations show that RDMP-KV can improve the server-side performance with different persistent key-value storage architectures by up to 22x, as compared with PMEM-oblivious RDMA-'Server-Reply' protocols. Our evaluations also show that RDMP-KV outperforms a distributed PMEM-based filesystem by up to 65% and a recent RDMA-to-PMEM framework b:s up to 71%.

关键词： Next Generation networking RDMA Data storage systems Key-value Stores Persistent Memory

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Alternate distributed Beamforming for Decode-and-Forward Multi-Relay Systems Using Buffers

Alternate Distributed Beamforming for Decode-and-Forward Mul...

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2020 international conference on computing, networking and Communications, ICNC 2020

作者： Zhou, Jiayu Qiao, Deli School of Information Science and Technology East China Normal University Shanghai China

ISBN: (纸本)9781728149059

In this paper, link selection for half-duplex buffer-aided relay systems is revisited. A new fixed scheduling policy referred as alternate distributed beamforming (ADB) is proposed, in which the relays are divided into two groups, with one group receiving the same information broadcast from the source and the other group transmitting the common messages to the destination via distributed beamforming in each time slot. It is worth noting that the relays used for reception and transmission are determined without the need of instantaneous channel state information (CSI). Theoretical analysis of the achievable throughput of the proposed scheme in Rayleigh fading is provided and the approximate closed-form expressions are derived. Through numerical results, it is shown that compared with existing link selection policies, the proposed fixed scheduling ADB achieves a significant improvement in achievable throughput. © 2020 IEEE.

关键词： Rayleigh fading

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