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SCALE: a scalable framework for efficiently clustering transactional data
2009
Data mining and knowledge discovery
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Second, we develop the weighted coverage density measure based clustering algorithm, a fast, memory-efficient, and scalable clustering algorithm for analyzing transactional data. ...
This paper presents SCALE, a fully automated transactional clustering framework. The SCALE design highlights three unique features. ...
Acknowledgments The first author is partly supported by China Scholarship Council for her one year visit at Georgia Institute of Technology. ...
doi:10.1007/s10618-009-0134-5
fatcat:xr3iicgtovfw7frrjbnzdlgbvi
Computing at Massive Scale: Scalability and Dependability Challenges
2016
2016 IEEE Symposium on Service-Oriented System Engineering (SOSE)
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Large-scale Cloud systems and big data analytics frameworks are now widely used for practical services and applications. ...
We first introduce a data-driven analysis methodology for characterizing the resource and workload patterns and tracing performance bottlenecks in a massive-scale distributed computing environment. ...
Peter Garraghan from University of Leeds and Jin Ouyang from Alibaba Cloud Inc. for discussions. ...
doi:10.1109/sose.2016.73
dblp:conf/sose/YangX16
fatcat:bsbdpnfzpnf5jbl2d3hobd7adu
Scale-Out vs. Scale-Up Techniques for Cloud Performance and Productivity
2014
2014 IEEE 6th International Conference on Cloud Computing Technology and Science
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Scale-out to a larger cluster of small nodes demonstrated high scalability. (2). ...
Scaling up and mixed scaling have high performance in using smaller clusters with a few powerful machine instances. (3). ...
The scale-up cluster shows very high efficiency for WordCount. ...
doi:10.1109/cloudcom.2014.66
dblp:conf/cloudcom/HwangSB14
fatcat:fnmnjmen2ngw5c5eushwyrs2jy
Scaling Reliably
2017
ACM Transactions on Programming Languages and Systems
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While we report measurements on a range of NUMA and cluster architectures, the key scalability experiments are conducted on the Athos cluster with 256 hosts (6144 cores). ...
We exceed the established scalability limits of distributed Erlang, and do not reach the limits of SD Erlang for these benchmarks at this scale (256 hosts, 6144 cores). ...
This work has been supported by the European Union grant RII3-CT-2005-026133 "SCIEnce: Symbolic Computing Infrastructure in Europe", IST-2011-287510 "RELEASE: A High-Level Paradigm for Reliable Large-scale ...
doi:10.1145/3107937
fatcat:3l3v5solvvfvdj4y47et3gba3y
Towards Scaling Blockchain Systems via Sharding
[article]
2019
arXiv
pre-print
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In this work, we take a principled approach to apply sharding, which is a well-studied and proven technique to scale out databases, to blockchain systems in order to improve their transaction throughput ...
Finally, we conduct an extensive evaluation of our design both on a local cluster and on Google Cloud Platform. ...
This protocol relies on a trusted randomness beacon implemented inside a TEE for efficiency. ...
arXiv:1804.00399v4
fatcat:cyulzlarwfgyris4l2bty6yczi
Architecture Of Large-Scale Systems
2013
Zenodo
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Finally, examples of large-scale systems are presented. ...
In this paper various techniques in relation to large-scale systems are presented. At first, explanation of large-scale systems and differences from traditional systems are given. ...
The hardware requirements for a social network like Facebook compared to a large-scale-scientific-cluster for calculating weather data are different. ...
doi:10.5281/zenodo.1089019
fatcat:bvlz4bgpdzanhaxud7la4jxzeu
Large-scale e-learning recommender system based on Spark and Hadoop
2019
Journal of Big Data
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In this article, we develop a distributed courses recommender system for the e-learning platform. ...
Next, we deploy our recommender system using big data technologies and techniques. Especially, we implement parallel FP-growth algorithm provided by Spark Framework and Hadoop ecosystem. ...
Funding No funding has been received for the conduct of this work and preparation of this manuscript. ...
doi:10.1186/s40537-019-0169-4
fatcat:odz2ffldxbb3neync6uy7uhs7e
Managing data retention policies at scale
2011
12th IFIP/IEEE International Symposium on Integrated Network Management (IM 2011) and Workshops
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A prototype deployed in a 16-machine Linux cluster currently supports 56 MB/sec for encryption, 76 MB/sec for decryption, 31, 000 retention policies/sec read and 15,000 retention policies/sec write. ...
A prototype deployed in a 16-machine Linux cluster currently supports 56 MB/sec for encryption, 76 MB/sec for decryption, 31,000 retention policies/sec read and 15,000 retention policies/sec write. ...
Managing data policies at scale poses various challenges, including the following two that we believe are key challenges to managing data retention policies: Scalable Policy Enforcement: A scalable engine ...
doi:10.1109/inm.2011.5990674
dblp:conf/im/LiSSK11
fatcat:w65v5lzp7jec5oebgvp5grrjd4
Effective Scaling of Blockchain Beyond Consensus Innovations and Moore's Law
[article]
2020
arXiv
pre-print
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We achieve this by developing an open-source benchmarking tool, called Prism, for investigating the key factors causing low resource efficiency and then discuss various topology and hardware innovations ...
This makes blockchain suffer from insufficient performance and poor scalability. ...
TPC, Transactions per CPU; TPMS, Transactions per Memory Second; TPDIO, Transactions per I/O Disk; TPND, Transactions per Network Data. Data obtained by Prism. ...
arXiv:2001.01865v2
fatcat:yhjx2yxtdnaapgj7xleuyqjeri
Survey of Large-Scale Data Management Systems for Big Data Applications
2015
Journal of Computer Science and Technology
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high throughput of transaction processing, but lack the capacity of scale-out. ...
The pursuit for tackling the challenges posed by the big data trend has given rise to a plethora of data management systems characterized by high scalability. ...
To conclude, this work delves deeper to lay
down a comprehensive taxonomy framework
that, not only serves as a direction of analyz-
ing the large-scale data management systems
for the big data application ...
doi:10.1007/s11390-015-1511-8
fatcat:tzdpu6jdive6dooandmaepiko4
Large-scale circuit placement
2005
ACM Transactions on Design Automation of Electronic Systems
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The second part of the tutorial highlights the recent progress on large-scale circuit placement, including techniques for wirelength minimization, routability optimization, and performance optimization ...
The first part of this tutorial summarizes results from recent optimality and scalability studies of existing placement tools. ...
INTRODUCTION The exponential growth of on-chip complexity has dramatically increased the demand for scalable optimization algorithms for large-scale physical design. ...
doi:10.1145/1059876.1059886
fatcat:ji7ameibx5cqrefa5fmewiojci
Efficient and Scalable Metadata Management in EB-Scale File Systems
2014
IEEE Transactions on Parallel and Distributed Systems
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Efficient and scalable distributed metadata management is critically important to overall system performance in large-scale distributed file systems, especially in the EB-scale era. ...
By conducting performance evaluation through extensive trace-driven simulations and a prototype implementation, experimental results demonstrate the efficiency and scalability of DROP. ...
This work is supported by A * STAR Thematic Strategic Research Programme (TSRP) Grant No. 1121720013. ...
doi:10.1109/tpds.2013.293
fatcat:sltd4blg2bdj5p6mqlgodin2gq
Software transactional memory for large scale clusters
2008
Proceedings of the 13th ACM SIGPLAN Symposium on Principles and practice of parallel programming - PPoPP '08
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In this work, we present Cluster-STM, an STM designed for high performance on large-scale commodity clusters. ...
While there has been extensive work on the design of software transactional memory (STM) for cache coherent shared memory systems, there has been no work on the design of an STM system for very large scale ...
We also wish to thank the National Center for Supercomputing Applications (NCSA) at the University of Illinois for granting time and support on the Tungsten cluster. ...
doi:10.1145/1345206.1345242
dblp:conf/ppopp/BocchinoAC08
fatcat:44dfhcxbqnem7fqou476gsdsm4
Mining Profitable and Concise Patterns in Large-Scale Internet of Things Environments
2021
Wireless Communications and Mobile Computing
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First, a GA-based MapReduce model is presented in this work known as GMR-Miner for mining closed patterns with high utilization in large-scale databases. ...
A genetic algorithm (GA) is utilized in the developed MapReduce framework that can be used to explore the potential and possible candidates in a limited time. ...
Acknowledgments Western Norway University of Applied Sciences, Norway, provides partial funding support for the work carried out in this paper. ...
doi:10.1155/2021/6653816
fatcat:wc7yzldruffohjkf3b4qedgi6y
A Scalable Framework for Provisioning Large-Scale IoT Deployments
2016
ACM Transactions on Internet Technology
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To improve scalability and reduce generated network traffic between cloud and edge infrastructure, we present a distributed provisioning approach that deploys LEONORE local nodes within the deployment ...
This is especially important in the context of large-scale IoT systems, such as in the smart city domain. ...
The IoT gateway has the following components: (i) a container, A Scalable Framework for Provisioning Large-scale IoT Deployments A:5 hosting application packages, (ii) a profiler, monitoring the current ...
doi:10.1145/2850416
fatcat:qydaemcvrzhb3p4edy5denaymi
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