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Journal of Grid Computing
Springer-Verlag
 
   
 
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  1-10 of 12 reviews Date Reviewed 
  iMapReduce: a distributed computing framework for iterative computation
Zhang Y., Gao Q., Gao L., Wang C.  Journal of Grid Computing 10(1): 47-68, 2020. Type: Article

MapReduce is one of the most popular standard algorithms in distributed processing. This paper contributes to performance improvement in MapReduce, which otherwise performs low on social networking and web-based data due to iterative processing. T...

Sep 28 2021
  An evaluation of the cost and performance of scientific workflows on Amazon EC2
Juve G., Deelman E., Berriman G., Berman B., Maechling P.  Journal of Grid Computing 10(1): 5-21, 2020. Type: Article

Cloud computing is becoming popular for computing that requires large processing power and massive data volume. The work reported here aims to study scientific workflows on Amazon Elastic Compute Cloud (EC2). The principal goal is to study runtime...

Sep 23 2021
  iCanCloud: a flexible and scalable cloud infrastructure simulator
Núñez A., Vázquez-Poletti J., Caminero A., Castañé G., Carretero J., Llorente I.  Journal of Grid Computing 10(1): 185-209, 2020. Type: Article

Cloud computing is a flexible and scalable solution for delivering information technology (IT) services. However, as the processing power used must be paid for, accurately right-sizing the cloud resources for particular end user applications is im...

Jul 26 2021
  Orchestrating complex application architectures in heterogeneous clouds
Caballer M., Zala S., García Á., Moltó G., Fernández P., Velten M.  Journal of Grid Computing 16(1): 3-18, 2018. Type: Article

The authors present INDIGO-DataCloud for deploying cloud applications across multiple cloud management platforms (CMPs) that require complex topologies and operational requirements, such as auto scaling resources according to dynamic application n...

Aug 19 2019
  PERSIST: policy-based data management middleware for multi-tenant SaaS leveraging federated cloud storage
Rafique A., Van Landuyt D., Joosen W.  Journal of Grid Computing 16(2): 165-194, 2018. Type: Article

NoSQL application data stores often combine on-premise and public cloud resources. As a consequence, they may deal with heterogeneous technologies, flexible but less structured storage architectures, and dynamic changes. In this paper, the authors...

Jan 9 2019
  Dataset popularity prediction for caching of CMS big data
Meoni M., Perego R., Tonellotto N.  Journal of Grid Computing 16(2): 211-228, 2018. Type: Article

The Compact Muon Solenoid (CMS) experiment at the European Organization for Nuclear Research (CERN) is a collaboration between thousands of physicists using a distributed computing and storage infrastructure consisting of 70 sites. Historical usag...

Dec 24 2018
  DCDedupe: selective deduplication and delta compression with effective routing for distributed storage
Zhang B., Wang C., Zhou B., Yuan D., Zomaya A.  Journal of Grid Computing 16(2): 195-209, 2018. Type: Article

In big data scenarios, data is often duplicated for system response time, efficiency, and network issues and then eliminated through deduplication. Data is compressed for storage efficiency and further abstraction or regression. The authors propos...

Nov 2 2018
  A survey on resource scheduling in cloud computing: issues and challenges
Singh S., Chana I.  Journal of Grid Computing 14(2): 217-264, 2016. Type: Article, Reviews: (2 of 2)

This is one of the best survey papers I have ever come across. It provides a thorough review of resource scheduling algorithms (RSAs) with a particular focus on cloud computing. While the paper does not excel as a survey of RSAs, it does excel in ...

Jun 14 2017
  A survey on resource scheduling in cloud computing: issues and challenges
Singh S., Chana I.  Journal of Grid Computing 14(2): 217-264, 2016. Type: Article, Reviews: (1 of 2)

When a cloud provider doesn’t properly schedule workloads, performance usually degrades. If the degradation is not caught in time, a cloud outage can occur. A couple of minutes of downtime is too long for many enterprise users to wait for th...

May 9 2017
  Big data 2.0 processing systems: taxonomy and open challenges
Bajaber F., Elshawi R., Batarfi O., Altalhi A., Barnawi A., Sakr S.  Journal of Grid Computing 14(3): 379-405, 2016. Type: Article

The digital universe is growing in size rapidly and will reach 40 zettabytes in 2020. There are many reasons for this growth, including the Internet of Things (IoT), and new users buying smartphones, tablets, and personal computers (PCs). This hug...

Nov 11 2016
 
 
 
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