Co-clustering is a powerful data mining tool for co-occurrence and dyadic data. As data sets become increasingly large, the scalability of co-clustering becomes more and more important. In this paper, we propose two a...
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Co-clustering is a powerful data mining tool for co-occurrence and dyadic data. As data sets become increasingly large, the scalability of co-clustering becomes more and more important. In this paper, we propose two approaches to parallelize co-clustering with sequential updates in a distributed environment. Based on these two approaches, we present a new distributed framework, Co-ClusterD, that supports efficient implementations of co-clustering algorithms with sequential updates. We design and implement Co-ClusterD, and show its efficiency through two co-clustering algorithms: fast non-negative matrix tri-factorization (FNMTF) and information theoretic co-clustering (ITCC). We evaluate our framework on both a local cluster of machines and the Amazon EC2 cloud. Our evaluation shows that co-clustering algorithms implemented in Co-ClusterD can achieve better results and run faster than their traditional concurrent counterparts.
While the deployment of social software has become widespread in private enterprises in the past years, the usage in military institutions is not common practice yet. this paper documents the implementation and usage ...
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Parallel and distributedcomputing has been under many years of development, having played a central role in shaping different research and application trends such as grid computing, cloud computing, green computing, ...
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Parallel and distributedcomputing has been under many years of development, having played a central role in shaping different research and application trends such as grid computing, cloud computing, green computing, etc. the broad applications of parallel and distributedcomputing have also made the relevant research field interdisciplinary, cross boundaries among architectures, communications, computing, algorithms and programming. the objective of this special issue is to address some recent developments in this interdisciplinary area. the special issue is based on the presentations made at the 13thinternationalconference on Parallel and distributedcomputing, Applications and Technologies (PDCAT 2012) held in Beijing, 14-16 December 2012.
Mobile device users can now easily capture and socially share video clips in a timely manner by uploading them wirelessly to a server. When attending crowded events, however, timely sharing of videos becomes difficult...
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the 13thinternationalconference on Software Engineering, Artificial Intelligence, networking, and Parallel/distributedcomputing (SNPD 2012) is being held in Kyoto, Japan. the conference is sponsored by the Internat...
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Today's large scale distributed systems are characterized by strong dynamics caused by the inherent unreliability of their constituting elements (e.g. process and link failures, processes joining or leaving the sy...
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Proxy signatures allow a proxy signer to sign messages on behalf of an original signer within a given context. they are widely used in distributed systems, grid computing, mobile agent applications, distributed shared...
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Searching frequent patterns in transactional databases is considered as one of the most important data mining problems and Apriori is one of the typical algorithms for this task. Developing fast and efficient algorith...
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the key infrastructure of Cloud computing is data center which is shared by many tenants. Each tenant's application competes for acquiring more network bandwidth in order to maximize its utility. However, this may...
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ISBN:
(纸本)9780769548791
the key infrastructure of Cloud computing is data center which is shared by many tenants. Each tenant's application competes for acquiring more network bandwidth in order to maximize its utility. However, this may cause interference among these diverse applications. Malicious competition not only degrades its performance, but also makes the overall performance of the data center poor and ineffective. To ensure the Quality of Services (QoS) and achieve high network utilization, in this paper, we propose a bandwidth allocation scheme for data center networks (DCNs), which is based on an application utility-based model. In our scheme, multi-path feature of DCN is leveraged to improve the network utilization, and utility functions are constructed to differentiate the throughput and delay sensibilities of different applications. Moreover, our scheme is suitable for arbitrary DCN topologies and without modification on current hardware. the numerical simulation shows that our scheme can provide bandwidth guarantee, fine-grained service differentiation and achieve high network utilization.
In this paper, we present a scalable implementation of a topic modeling (Adaptive Link-IPLSA) based method for online event analysis, which summarize the gist of massive amount of changing tweets and enable users to e...
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