Int. J. Networked Distributed Comput.最新文献_第2页

High Performance Hadoop Distributed File System 高性能Hadoop分布式文件系统

Int. J. Networked Distributed Comput. Pub Date : 2020-05-01 DOI: 10.2991/ijndc.k.200515.007

Mohamed Elkawkagy, Heba Elbeh

引用次数: 6

A Traffic Tracking Analysis Model for the Effective Management of E-commerce Transactions 面向电子商务交易有效管理的流量跟踪分析模型

Int. J. Networked Distributed Comput. Pub Date : 2020-05-01 DOI: 10.2991/ijndc.k.200515.006

Sylvanus A. Ehikioya, Shenghong Lu

引用次数: 1

Towards a Task and Resource Aware Task Scheduling in Cloud Computing: An Experimental Comparative Evaluation 面向云计算中任务感知和资源感知的任务调度:实验对比评价

Int. J. Networked Distributed Comput. Pub Date : 2020-05-01 DOI: 10.2991/ijndc.k.200515.003

Muhammad Ibrahim, S. Nabi, A. Baz, Nasir Naveed, H. Alhakami

{"title":"Towards a Task and Resource Aware Task Scheduling in Cloud Computing: An Experimental Comparative Evaluation","authors":"Muhammad Ibrahim, S. Nabi, A. Baz, Nasir Naveed, H. Alhakami","doi":"10.2991/ijndc.k.200515.003","DOIUrl":"https://doi.org/10.2991/ijndc.k.200515.003","url":null,"abstract":"Cloud computing has been considered as one of the large-scale platforms that support various types of services including compute, storage, compute, and analytic to the users and organizations with high agility, scalability, and resiliency intact. The users of the Cloud are increasing at an enormous rate which also resulted in issues related to handling and scheduling the users’ requested workload effectively and efficiently on the available Cloud resources. The aim of the Cloud service providers is to maximize resource utilization and in turn increased revenue generation. In the last few years, Cloud Task scheduling has been considered as an important area of research for the researchers. As different scheduling heuristics are associated with different underlying assumptions; thus, performing a precise comparison cannot be guaranteed. This work empirically compares and provides an insight into the performance of some renown state-of-the-art task scheduling heuristics concerning the Makespan, average resource utilization ratio, Throughput. Those approaches include task-aware, resource-aware, and some hybrid approaches. The experiments were then extended by evaluating the performance using average response time for all the compared approaches. The simulation experiments are conducted by utilizing HCSP and GOCJ benchmark datasets using CloudSim a renowned simulation tool for Cloud. Based on the findings of the comparative analysis and results discussion, we have highlighted some important aspects of the underlying approaches and for future work we will propose a task-cum-resource aware task scheduling approach.","PeriodicalId":318936,"journal":{"name":"Int. J. Networked Distributed Comput.","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126976261","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 12

Solving MTU Mismatch and Broadcast Overhead of NDN over Link-layer Networks 解决链路层网络中NDN的MTU失配和广播开销

Int. J. Networked Distributed Comput. Pub Date : 2020-03-01 DOI: 10.2991/ijndc.k.200213.001

Thongchai Chuachan, K. Djemame, S. Puangpronpitag

引用次数: 2

Comparative Study of Basic Time Domain Time-Delay Estimators for Locating Leaks in Pipelines 基本时域时延估计在管道泄漏定位中的比较研究

Int. J. Networked Distributed Comput. Pub Date : 2020-03-01 DOI: 10.2991/ijndc.k.200129.001

V. Faerman, V. S. Avramchuk

引用次数: 6

Multimedia Analysis and Fusion via Wasserstein Barycenter Wasserstein Barycenter的多媒体分析与融合

Int. J. Networked Distributed Comput. Pub Date : 2020-02-01 DOI: 10.2991/ijndc.k.200217.001

Cong Jin, Junhao Wang, Jin Wei, Lifeng Tan, Shouxun Liu, Wei Zhao, Shan Liu, Xin Lv

{"title":"Multimedia Analysis and Fusion via Wasserstein Barycenter","authors":"Cong Jin, Junhao Wang, Jin Wei, Lifeng Tan, Shouxun Liu, Wei Zhao, Shan Liu, Xin Lv","doi":"10.2991/ijndc.k.200217.001","DOIUrl":"https://doi.org/10.2991/ijndc.k.200217.001","url":null,"abstract":"Many multimedia analysis algorithms rely on probability distributions that characterize audio or image features as generally high dimensions. For example, music analysis methods, such as automatic music transcription (AMT) [1] and music classification [2], in these applications, having sufficient similarity (or equivalent difference) between distributions becomes crucial. The classical distance or difference of probability density includes Kullback Leibler divergence, Kolmogorov distance, Bhattacharyya distance (also known as Hellinger distance), etc. Recently, the framework of optimal transportation and Wasserstein distance [3] are also called earth mover’s distance (EMD) [4], which has aroused great interest in computer vision [5], machine learning [6] and data fusion. Wasserstein distance calculates the best warped starter to map the measure m to the second n for a given input probability. Optimality corresponds to a loss function that measures the predicted value of the displacement in the warped starter. Generally, considering the accumulation of m and n, Wasserstein distance calculates the definition of the displacement of every particle from traces of its mass to the displacement of m to n.","PeriodicalId":318936,"journal":{"name":"Int. J. Networked Distributed Comput.","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114973192","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 2

Empirical Research on the Growth Path of China's Industrial Economy under the Background of Supply-side Reform 供给侧改革背景下中国工业经济增长路径实证研究

Int. J. Networked Distributed Comput. Pub Date : 2020-02-01 DOI: 10.2991/ijndc.k.200217.002

Xianhong Xu

引用次数: 0

Multi-Dimensional Indexing System Considering Distributions of Sub-indexes and Data 考虑子索引和数据分布的多维索引系统

Int. J. Networked Distributed Comput. Pub Date : 2019-12-01 DOI: 10.2991/ijndc.k.191118.002

Kazuto Nakanishi, T. Hochin, Hiroki Nomiya, Hiroaki Hirata

引用次数: 0

Enhancement of Copper Wire Lengthening Automatic System using Contactless Heater 非接触式加热器对铜线加长自动系统的改进

Int. J. Networked Distributed Comput. Pub Date : 2019-12-01 DOI: 10.2991/ijndc.k.191115.002

H. Lin, J. Hu, Chung-Hao Cheng

引用次数: 0

Performance Evaluation of Data Migration Policies for a Distributed Storage System with Dynamic Tiering 基于动态分级的分布式存储系统数据迁移策略性能评估

Int. J. Networked Distributed Comput. Pub Date : 2019-11-01 DOI: 10.2991/ijndc.k.191115.001

Atsushi Nunome, Hiroaki Hirata

{"title":"Performance Evaluation of Data Migration Policies for a Distributed Storage System with Dynamic Tiering","authors":"Atsushi Nunome, Hiroaki Hirata","doi":"10.2991/ijndc.k.191115.001","DOIUrl":"https://doi.org/10.2991/ijndc.k.191115.001","url":null,"abstract":"Recent years, even client nodes can easily have enough storage area owing to the spread of inexpensive storage devices. In many cases, the large amount of an unused storage area is left on storage devices over the network. It is important to utilize such fragmented unused storage area. Hence, we have for our object to build an environment which not only file servers but also client nodes can provide their surplus storage area as public storage. However, such computing environment has essentially heterogeneity. The heterogeneity of the system causes difficulty for properly allocating data blocks onto the storage devices. We consider that system heterogeneity is brought by even a dynamic aspect. It means that both a static aspect (e.g. differences of hardware configuration) and a dynamic aspect (e.g. imbalance of I/O workload) make such heterogeneity. This dynamic heterogeneity is not able to be solved statically. Therefore, data blocks should be located on a suitable storage device according to their access patterns at runtime. For example, frequently accessed data blocks are better to locate on high-performance storage, and it may cause no inconvenience when rarely accessed data blocks are located on low-performance storage. However, such location optimization in accordance with access patterns of data blocks makes the burden too heavy for system administrators.","PeriodicalId":318936,"journal":{"name":"Int. J. Networked Distributed Comput.","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126962560","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 2