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Balanced and Swap-Robust Trades for Dynamical distributed Storage

Balanced and Swap-Robust Trades for Dynamical Distributed St...

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IEEE international symposium on Information Theory

作者： Chao Pan Ryan Gabrys Xujun Liu Charles Colbourn Olgica Milenkovic ECE Department University of Illinois Calit2 University of California-San Diego Foundational Mathematics Department Xi&#x2019 an Jiaotong-Liverpool University School of CAI Arizona State University

ISBN: (数字)9781665421591

ISBN: (纸本)9781665421607

Trades, introduced by Hedayat [9], are two sets of blocks of elements which may be exchanged (traded) without altering the counts of certain subcollections of elements within their constituent blocks. They are of importance in applications where certain combinations of elements dynamically become prohibited from being placed in the same group of elements, since in this case one can trade the offending blocks with allowed ones. This is particularly the case in distributed storage systems, where due to privacy and other constraints, data of some groups of users cannot be stored together on the same server. We introduce a new class of balanced trades, important for access balancing of servers, and perturbation resilient balanced trades, important for studying the stability of server access frequencies with respect to changes in data popularity. The constructions and bounds on our new trade schemes rely on specialized selections of defining sets in minimal trades and number-theoretic analyses.

关键词： Data privacy Perturbation methods distributed databases Stability analysis Servers Information theory

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Efficient parallel and Adaptive Partitioning for Load-balancing in Spatial Join 34

Efficient Parallel and Adaptive Partitioning for Load-balanc...

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34th IEEE international parallel and distributed Processing symposium (IPDPS)

作者： Yang, Jie Puri, Satish Marquette Univ Dept Comp Sci Milwaukee WI 53233 USA

ISBN: (纸本)9781728168760

Due to the developments of topographic techniques, clear satellite imagery, and various means for collecting information, geospatial datasets are growing in volume, complexity, and heterogeneity. For efficient execution of spatial computations and analytics on large spatial data sets, parallel processing is required. To exploit fine-grained parallel processing in large scale compute clusters, partitioning in a load-balanced way is necessary for skewed datasets. In this work, we focus on spatial join operation where the inputs are two layers of geospatial data. Our partitioning method for spatial join uses Adaptive Partitioning (ADP) technique, which is based on Quadtree partitioning. Unlike existing partitioning techniques, ADP partitions the spatial join workload instead of partitioning the individual datasets separately to provide better load-balancing. Based on our experimental evaluation, ADP partitions spatial data in a more balanced way than Quadtree partitioning and Uniform grid partitioning. ADP uses an output-sensitive duplication avoidance technique which minimizes duplication of geometries that are not part of spatial join output. In a distributed memory environment, this technique can reduce data communication and storage requirements compared to traditional methods. To improve the performance of ADP, an MPI+Threads based parallelization is presented. With ParADP, a pair of real world datasets, one with 717 million polylines and another with 10 million polygons, is partitioned into 65,536 grid cells within 7 seconds. ParADP performs well with both good weak scaling up to 4,032 CPU cores and good strong scaling up to 4,032 CPU cores.

关键词： spatial join spatial data partitioning load-balancing Adaptive Partitioning parallel Partitioning MPI-GIS HPC

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Efficient parallel execution of block transactions in blockchain 21

Efficient parallel execution of block transactions in blockc...

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22nd international Middleware Conference, Middleware 2021

作者： Anjana, Parwat Singh Indian Institute of Technology Hyderabad Telangana India

ISBN: (纸本)9781450391559

Miners and validators in current blockchains serially execute block transactions. Such serial execution cannot efficiently utilize modern multi-core resources, consequently hampering system throughput. We propose three approaches to improve blockchain throughput by introducing parallel execution of block transactions. We present a static analysis-based DiPETrans approach that groups the block transactions into independent shards and executes them parallelly in a distributed fashion using a leader-follower method. DiPETrans is empirically evaluated with 5 million actual transactions from the Ethereum blockchain. Since static analysis fails to identify the conflicts precisely, we introduce OptSmart to exploit multi-processing on a multi-core system to improve throughput further. Miners and validators use multiple threads to parallelly execute smart contract transactions (SCTs) in a block. A miner concurrently executes SCTs using optimistic read-write software transactional memory systems (RWSTMs) and saves the non-conflicting SCTs in the concurrent bin and conflicting SCTs in the block graph (BG). Later, validators re-execute SCTs deterministically in parallel to validate the block by using information appended by the concurrent miner. In terms of throughput, optimistic object-based STMs (OSTMs) with higher-level objects are known to outperform RWSTMs. We propose ObjSC approach based on optimistic OSTM, and a counter-based smart multi-threaded validator (SMV) that efficiently detects and rejects malicious blocks proposed by the malicious miners. The simulation result shows that the proposed approaches outperform existing approaches. © 2021 ACM.

关键词： Smart contract

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An O(log2 N) SMC2 Algorithm on distributed Memory with an Approx. Optimal L-Kernel

An O(log2 N) SMC2 Algorithm on Distributed Memory with an Ap...

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international Conference on Multisensor Fusion and Integration for Intelligent systems (MFI)

作者： Conor Rosato Alessandro Varsi Joshua Murphy Simon Maskell Department of Pharmacology and Therapeutics University of Liverpool United Kingdom Department of Electrical Engineering and Electronics University of Liverpool United Kingdom

Calibrating statistical models using Bayesian inference often requires both accurate and timely estimates of parameters of interest. Particle Markov Chain Monte Carlo (p-MCMC) and Sequential Monte Carlo Squared (SMC 2 ) are two methods that use an unbiased estimate of the log-likelihood obtained from a particle filter (PF) to evaluate the target distribution. P-MCMC constructs a single Markov chain which is sequential by nature so cannot be readily parallelized using distributed Memory (DM) architectures. This is in contrast to SMC 2 which includes processes, such as importance sampling, that are described as embarrassingly parallel. However, difficulties arise when attempting to parallelize resampling. None-the-less, the choice of backward kernel, recycling scheme and compatibility with DM architectures makes SMC 2 an attractive option when compared with p-MCMC. In this paper, we present an SMC 2 framework that includes the following features: an optimal (in terms of time complexity) $\mathcal{O}(\log_2 N)$ parallelization for DM architectures, an approximately optimal (in terms of accuracy) backward kernel, and an efficient recycling scheme. On a cluster of 128 DM processors, the results on a biomedical application show that SMC 2 achieves up to a 70× speed-up vs its sequential implementation. It is also more accurate and roughly 54× faster than p-MCMC. A GitHub link is given which provides access to the code.

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Optimizing Non-commutative Allreduce Over Virtualized, Migratable MPI Ranks

Optimizing Non-commutative Allreduce Over Virtualized, Migra...

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IEEE international symposium on parallel and distributed Processing Workshops and Phd Forum (IPDPSW)

作者： Sam White Laxmikant V. Kale Department of Computer Science University of Illinois at Urbana-Champaign Urbana Illinois USA

ISBN: (数字)9781665497473

ISBN: (纸本)9781665497480

Dynamic load balancing can be difficult for MPI-based applications. Application logic and algorithms are often rewritten to enable dynamic repartitioning of the domain. An alternative approach is to virtualize the MPI ranks as threads-instead of operating system processes- and to migrate threads around the system to balance the computational load. Adaptive MPI is one such implementation. It supports virtualization of MPI ranks as migratable user-level threads. However, this migratability itself can introduce new performance overheads to applications. In this paper, we identify non-commutative reduction operations as problematic for any runtime supporting either user-defined initial mapping of ranks or dynamic migration of ranks among the cores or nodes of a machine. We investigate the challenges associated with supporting efficient non-commutative reduction operations, and explore algorithmic alternatives such as recursive doubling and halving in combination with a novel adaptive message combining technique. We explore tradeoffs in the different algorithms for various message sizes and mappings of ranks to cores, demonstrating our performance improvements using microbenchmarks.

关键词： Degradation distributed processing Runtime Heuristic algorithms Operating systems Load management Hardware

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DNA-based Secret Sharing and Hiding in Dispersed Computing

DNA-based Secret Sharing and Hiding in Dispersed Computing

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IEEE international Conference on Software Reliability Engineering Workshops (ISSRE Wksp)

作者： Marek R. Ogiela Urszula Ogiela AGH University of Science and Technology Cryptography and Cognitive Informatics Laboratory Krakow Poland

ISBN: (数字)9781665476799

ISBN: (纸本)9781665476805

In this paper will be described a new security protocol for secret sharing and hiding, which use selected personal features. Such technique allows to create human-oriented personalized security protocols dedicated for particular users. Proposed method may be applied in dispersed computing systems, where secret data should be divided into particular number of parts.

关键词： Steganography Conferences Software algorithms distributed databases DNA Software reliability Nitrogen

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Performance Analysis of Multi-Containerized MD Simulations for Low-Level Resource Allocation

Performance Analysis of Multi-Containerized MD Simulations f...

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IEEE international symposium on parallel and distributed Processing Workshops and Phd Forum (IPDPSW)

作者： Shingo Okuno Akira Hirai Naoto Fukumoto ICT Systems Laboratory FUJITSU LIMITED

ISBN: (数字)9781665497473

ISBN: (纸本)9781665497480

This study discusses scheduling strategies to maximize ensemble throughput, which is the total throughput of multiple containers running simultaneously. Such a strategy is useful, for example, in ensemble runs of molecular dynamics (MD) simulations. To design the strategies, we need to tackle two major challenges: (1) how many containers and how many threads per container we should allocate, and (2) which low-level resources we should allocate to reflect workload characteristics. In particular, the latter challenge is important and inevitable for performance-sensitive applications because they effectively utilize low-level hardware such as simultaneous multi-threading (SMT) to maximize performance, while most container platforms do not handle the challenge. In this paper, as a preliminary experiment to implement scheduling strategies related to SMT, we examined whether ensemble throughput of MD simulations can be improved by deploying containers on separate logical cores even when they share the same physical cores. As a result, we obtained a 2.22-fold ensemble throughput compared with a one-container execution with 10 physical cores.

关键词： Analytical models distributed processing Instruction sets Conferences Containers Throughput Hardware

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Quantifying the Cost of Privately Storing Data in distributed Storage systems

Quantifying the Cost of Privately Storing Data in Distribute...

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IEEE international symposium on Information Theory

作者： Ré mi A. Chou Department of Electrical Engineering &#x0026 Computer Science Wichita State University Wichita KS

ISBN: (数字)9781665421591

ISBN: (纸本)9781665421607

Consider a user who wishes to store a file in multiple servers such that at least t servers are needed to reconstruct the files, and z colluding servers cannot learn any information about the file. Unlike traditional models, where perfectly secure channels are assumed to be available at no cost between the user and each server, we assume that the user can only send data to the servers via public channels, and that the user and each server share an individual secret key with length n. For a given n, we determine the maximal length of the file that the user can store, and thus quantify the necessary cost to store a file with a certain length, in terms of the length of the secret that the user needs to share with the servers. Additionally, for this maximal file length, we determine (i) the optimal amount of local randomness needed at the user, (ii) the optimal amount of public communication from the user to the servers, and (iii) the optimal amount of storage requirement at the servers.

关键词： Costs distributed databases Data models Servers Information theory

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24th international Conference on Information Integration and Web Intelligence, iiWAS 2022, held in conjunction with the 20th international Conference on Advances in Mobile Computing and Multimedia Intelligence, MoMM 2022

24th International Conference on Information Integration and...

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24th international Conference on Information Integration and Web Intelligence, iiWAS 2022, held in conjunction with the 20th international Conference on Advances in Mobile Computing and Multimedia Intelligence, MoMM 2022

ISBN: (纸本)9783031210464

The proceedings contain 53 papers. The special focus in this conference is on Information Integration and Web Intelligence. The topics include: GPU Accelerated parallel Implementation of Linear Programming Algorithms;Towards Explaining DL Non-entailments by Utilizing Subtree Isomorphisms;Query Optimization in NoSQL databases Using an Enhanced Localized R-tree Index;handling Exit Node Vulnerability in Onion Routing with a Zero-Knowledge Proof;an Accurate, Flexible and Private Trajectory-Based Contact Tracing System on Untrusted Servers;bilateral Bargaining for Healthcare Data Sharing;modifying Neo4j’s Object Graph Mapper Queries for Access Control;a Recommendation Method for Recipes Containing Unskillful Elements Using Naïve Bayes Classifier to Improve Cooking Skills;extraction of Complementary Topics Based on Phrase Importance and Co-occurrence in Technical Blogs;sharing Semantic Knowledge for Autonomous Robots: Cooperation for Social Robotic systems;feature Relevance Analysis of Product Reviews to Support Online Shopping;annotation System for Dialogue Datasets of Older Adult’s with Photos and Storytelling;evaluation Axes for Automatically Generated Product Descriptions;CISQA: Corporate Smart Insights Question Answering System;symmetry Metrics for Pairwise Entity Similarities;a New Method to Measure Similarity of Words in Japanese Twitter Based on Related Images;Hybrid Phishing URL Detection Using Segmented Word Embedding;a Scheme for News Article Classification in a Low-Resource Language;expertise Computation for Automatic Reviewer Assignment;detection of Hot Topics Using Multi-view Text Clustering;exploiting Named Entity Recognition for Information Extraction from Italian Procurement Documents: A Case Study;interactive Visualization of Comic Character Correlation Diagrams for Understanding Character Relationships and Personalities;two Case Studies on Guiding Human Behavior Using Virtualization Technologies in distributed Virtual Shopping Malls;central Figures in t

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An Efficient Block Validation Mechanism for UTXO-based Blockchains

An Efficient Block Validation Mechanism for UTXO-based Block...

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international symposium on parallel and distributed Processing (IPDPS)

作者： Xiaohai Dai Bin Xiao Jiang Xiao Hai Jin National Engineering Research Center for Big Data Technology and System Services Computing Technology and System Lab Cluster and Grid Computing Lab School of Computer Science and Technology Huazhong University of Science and Technology China Department of Computing The Hong Kong Polytechnic University Hong Kong

It has been recognized that one of the bottlenecks in the UTXO-based blockchain systems is the slow block validation - the process of validating a newly-received block by a node before locally storing it and further broadcasting it. As a block contains multiple inputs, the block validation mainly involves checking the inputs against the status data, which is also known as the Unspent Transaction Outputs (UTXO) set. As time goes by, the UTXO set becomes more and more expansive, most of which can only be stored on disks. This considerably slows down the input checking and thus block validation, which can potentially compromise system security. To deal with the above problem, we disassemble the function of input checking into three parts: existence validation (EV), unspent validation (UV), and script validation (SV). Based on the disassembly, we propose EBV, an efficient block validation mechanism to speed up EV, UV, and SV individually. First, EBV changes the representation of status data, from UTXO set to a bit-vector set, which drastically reduces its size. The smaller status data can be entirely maintained in memory, thereby accelerating UV and also block validation. Second, EBV requires each transaction to carry the proof data, which enables EV and SV without accessing the disks. Furthermore, we also cope with two challenges in the design of EBV, namely transaction inflation and fake positions. To evaluate the EBV mechanism, we implement a prototype on top of Bitcoin, the most widely known UTXO-based blockchain, and conduct extensive experiments to compare EBV and Bitcoin. The experimental results demonstrate that EBV successfully reduces the memory requirement by 93.1 % and the block validation time by up to 93.5%.

关键词： distributed processing Memory management Prototypes Bitcoin Broadcasting Blockchains Delays

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