To reduce the time required to complete the regeneration process of erasure codes, we propose a Tree-structured parallel Regeneration (TPR) scheme for multiple data losses in distributed storage systems. Under the sch...
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To reduce the time required to complete the regeneration process of erasure codes, we propose a Tree-structured parallel Regeneration (TPR) scheme for multiple data losses in distributed storage systems. Under the scheme, two algorithms are proposed for the construction of multiple regeneration trees, namely the edge-disjoint algorithm and edge-sharing algorithm. The edge-disjoint algorithm constructs multiple independent trees, and is simple and appropriate for environments where newcomers and their providers are distributed over a large area and have few intersections. The edge-sharing algorithm constructs multiple trees that compete to utilize the bandwidth, and make a better utilization of the bandwidth, although it needs to measure the available band-width and deal with the bandwidth changes; it is therefore difficult to implement in practical systems. The parallel regeneration for multiple data losses of TPR primarily includes two optimizations: firstly, transferring the data through the bandwidth optimized-paths in a pipe-line manner; secondly, executing data regeneration over multiple trees in parallel. To evaluate the proposal, we implement an event-based simulator and make a detailed comparison with some popular regeneration methods. The quantitative comparison results show that the use of TPR employing either the edge-disjoint algorithm or edge-sharing algorithm reduces the regeneration time significantly.
There are well known anomalies permitted by snapshot isolation that can lead to violations of data consistency by interleaving transactions that individually maintain consistency. Until now, there are some ways to pre...
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Wireless sensor networks (WSN) is a key technology extensively applied in many fields, such as transportation, health-care and environment monitoring. Despite rapid development, the exponentially increasing data emana...
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User request trace-oriented monitoring is an effective method to improve the reliability of cloud systems. However, there are some difficulties in getting traces in practice, which hinder the development of trace-orie...
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User request trace-oriented monitoring is an effective method to improve the reliability of cloud systems. However, there are some difficulties in getting traces in practice, which hinder the development of trace-oriented monitoring research. In this paper, we release a fine-grained user request-centric open trace data set, called Trace Bench, collected on a real world cloud storage system deployed in a real environment. During collecting, many aspects are considered to simulate different scenarios, including cluster size, request type, workload speed, etc. Besides recording the traces when the monitored system is running normally, we also collect the traces under the situation with faults injected. With a mature injection tool, 14 faults are introduced, including function faults and performance faults. The traces in Trace Bench are clustered in different files, where each file corresponds to a certain scenario. The whole collection work lasted for more than half a year, resulting in more than 360, 000 traces in 361 files. In addition, we also employ several applications based on Trace Bench, which validate the helpfulness of Trace Bench for the field of trace-oriented monitoring.
In this paper, we consider novel anycast-based integrated routing protocol (AIRP) to reduce the cost in delay performance of communications in multihop WSNs. Without tight time synchronization or known geographic info...
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The resource allocation problem in data centre networks refers to a map of the workloads provided by the cloud users/tenants to the Substrate Network(SN)which are provided by the cloud *** studies consider the dynamic...
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The resource allocation problem in data centre networks refers to a map of the workloads provided by the cloud users/tenants to the Substrate Network(SN)which are provided by the cloud *** studies consider the dynamic arrival and departure of the workloads,while the dynamics of the substrate are *** this paper,we first propose the resource allocation with the dynamic SN,and denote it as ***,we propose an efficient mapping algorithm for *** performance of the proposed algorithm is evaluated by performing simulation *** results show that the proposed algorithm can effectively solve the GraphMap-DS.
Non-negative matrix factorization (NMF) is an efficient dimension reduction method and plays an important role in many pattern recognition and computer vision tasks. However, conventional NMF methods are not robust si...
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Non-negative matrix factorization (NMF) is an efficient dimension reduction method and plays an important role in many pattern recognition and computer vision tasks. However, conventional NMF methods are not robust since the objective functions are sensitive to outliers and do not consider the geometric structure in datasets. In this paper, we proposed a correntropy graph regularized NMF (CGNMF) to overcome the aforementioned problems. CGNMF maximizes the correntropy between data matrix and its reconstruction to filter out the noises of large magnitudes, and expects the coefficients to preserve the intrinsic geometric structure of data. We also proposed a modified version of our CGNMF which construct the adjacent graph by using sparse representation to enhance its reliability. Experimental results on popular image datasets confirm the effectiveness of CGNMF.
Regarding the non-negativity property of the magnitude spectrogram of speech signals, nonnegative matrix factorization (NMF) has obtained promising performance for speech separation by independently learning a diction...
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ISBN:
(纸本)9781479928941
Regarding the non-negativity property of the magnitude spectrogram of speech signals, nonnegative matrix factorization (NMF) has obtained promising performance for speech separation by independently learning a dictionary on the speech signals of each known speaker. However, traditional NM-F fails to represent the mixture signals accurately because the dictionaries for speakers are learned in the absence of mixture signals. In this paper, we propose a new transductive NMF algorithm (TNMF) to jointly learn a dictionary on both speech signals of each speaker and the mixture signals to be separated. Since TNMF learns a more descriptive dictionary by encoding the mixture signals than that learned by NMF, it significantly boosts the separation performance. Experiments results on a popular TIMIT dataset show that the proposed TNMF-based methods outperform traditional NMF-based methods for separating the monophonic mixtures of speech signals of known speakers.
High-performance computing (HPC) clusters are currently faced with two major challenges - namely, the dynamic nature of new generation of applications and the heterogeneity of platforms - if they are going to be usefu...
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Both three dimensional (3D) and multi-view video technologies have made noticeable progress and become more popular in recent years. 3D video expands the user's experience beyond the conventional 2D video by addin...
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ISBN:
(纸本)9781450318938
Both three dimensional (3D) and multi-view video technologies have made noticeable progress and become more popular in recent years. 3D video expands the user's experience beyond the conventional 2D video by adding the sensation of depth, while multi-view video shows the same scenery from different viewpoints. In both cases, huge amount of data need to be compressed and transmitted, making it challenging to support heterogeneous mobile devices with limited bandwidth and processmg power. Scalable Multi-view Video Coding is one of the main techniques that addresses this challenge by scaling down the video. However, in addition to conventional scalable modalities of temporal, spatial, quality, and complexity in 2D video, SMVC has many more modalities, adding a much higher dimension to the difficult decision making process in the video scalability engine. In this paper, we use Grounded Theory to systematically extract various scalable modalities in multi-view 3D video and we find, in addition to some known modalities, some new modalities specifically for mobile multi-view 3D video. The usefulness of these scalable modalities in applications specific to mobile multi-view 3D video are also shown. Copyright 2013 ACM.
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