The Experts below are selected from a list of 15 Experts worldwide ranked by ideXlab platform
John P. Russo - One of the best experts on this subject based on the ideXlab platform.
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Using Amazon web services to teach web-enabled database and networking concepts
Journal of Computing Sciences in Colleges, 2013Co-Authors: John P. Russo, Magdy EllabidyAbstract:Amazon offers cloud infrastructure through its Amazon Web Services(AWS). The authors taught a cloud computing course using AWS. Besides offering a general introduction to cloud computing, the course also enabled students to build a fault-tolerant web site with a database backend. Students were able to further hone their database skills by initially designing a database which would then be used by the web site to store information such as a shopping cart or payment information. The database itself was initially hosted on AWS using an instance running MySQL. Towards the end of the course, the students migrated their databases to the Relational Data Service (RDS) provided by Amazon. Additionally, students setup a virtual web server on several instances with S3 storage for all static content. Students also deployed an Elastic Load Balancer which directs traffic to instances of the Web server. Figure 1 shows the initial design.
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Using Amazon web services to teach web-enabled database concepts
Journal of Computing Sciences in Colleges, 2013Co-Authors: David Rilett, John P. RussoAbstract:Amazon offers cloud infrastructure through its Amazon Web Services(AWS). The authors taught a cloud computing course using AWS. Besides offering a general introduction to cloud computing, the course also enabled students to build a fault-tolerant web site with a database backend. Students were able to further hone their database skills by initially designing a database which would then be used by the web site to store information such as a shopping cart or payment information. The database itself was initially hosted on AWS using an instance running MySQL. Towards the end of the course, the students migrated their databases to the Relational Data Service (RDS) provided by Amazon. Additionally, students setup a virtual web server on several instances with S3 storage for all static content. Students also deployed an Elastic Load Balancer which directs traffic to instances of the Web server. Figure 1 shows the initial design.
Jairam K Naik - One of the best experts on this subject based on the ideXlab platform.
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a dynamic aco based Elastic Load Balancer for cloud computing d acoelb
2020Co-Authors: Jairam K NaikAbstract:Cloud computing is for the delivery of computational service like servers, software, databases, storage, networks, intelligence, analytics, and more via the Internet (“the cloud”) for tendering faster innovation, economies of scale, and flexible resources. The workLoad in cloud computing is defined as the amount of computational work at a given time that the computer has been given to do. This computational workLoad comprises of some number of users connected to and interacting with the computer’s applications additionally to the computer’s application programs running in the system. This workLoad may alter dynamically based on the available resources and the end-users. Hence, the key challenging duty in the cloud computing is balancing the workLoad among the Virtual Machines (VM’s) of the systems. So, there is a need for introducing an Elastic dynamic Load Balancer for distributing the workLoads efficiently in the cloud. A Load Balancer can distribute the Loads among the VM’s of multiple servers or compute resources. The utilization of such Elastic and dynamic Load Balancer can enhance the fault tolerance capability of applications and the availability of cloud resources. As your needs change, adding or removing of computing resources without disrupting the overall flow of requests is made possible utilizing this Elastic and dynamic Load Balancer. Generally, an Elastic Load balancing task chains three types of Balancers, they are Application Load Balancers, Classic Load Balancers, and Network Load Balancers. The Application Load Balancer can be chosen based on the need of applications. In this chapter, it proposed a dynamic and Elasticity approach (D-ACOELB) for workLoad balancing in cloud data centers based on Ant Colony Optimization (ACO).
Magdy Ellabidy - One of the best experts on this subject based on the ideXlab platform.
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Using Amazon web services to teach web-enabled database and networking concepts
Journal of Computing Sciences in Colleges, 2013Co-Authors: John P. Russo, Magdy EllabidyAbstract:Amazon offers cloud infrastructure through its Amazon Web Services(AWS). The authors taught a cloud computing course using AWS. Besides offering a general introduction to cloud computing, the course also enabled students to build a fault-tolerant web site with a database backend. Students were able to further hone their database skills by initially designing a database which would then be used by the web site to store information such as a shopping cart or payment information. The database itself was initially hosted on AWS using an instance running MySQL. Towards the end of the course, the students migrated their databases to the Relational Data Service (RDS) provided by Amazon. Additionally, students setup a virtual web server on several instances with S3 storage for all static content. Students also deployed an Elastic Load Balancer which directs traffic to instances of the Web server. Figure 1 shows the initial design.
David Rilett - One of the best experts on this subject based on the ideXlab platform.
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Using Amazon web services to teach web-enabled database concepts
Journal of Computing Sciences in Colleges, 2013Co-Authors: David Rilett, John P. RussoAbstract:Amazon offers cloud infrastructure through its Amazon Web Services(AWS). The authors taught a cloud computing course using AWS. Besides offering a general introduction to cloud computing, the course also enabled students to build a fault-tolerant web site with a database backend. Students were able to further hone their database skills by initially designing a database which would then be used by the web site to store information such as a shopping cart or payment information. The database itself was initially hosted on AWS using an instance running MySQL. Towards the end of the course, the students migrated their databases to the Relational Data Service (RDS) provided by Amazon. Additionally, students setup a virtual web server on several instances with S3 storage for all static content. Students also deployed an Elastic Load Balancer which directs traffic to instances of the Web server. Figure 1 shows the initial design.
Fethi A. Rabhi - One of the best experts on this subject based on the ideXlab platform.
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A workLoad-driven approach to database query processing in the cloud
The Journal of Supercomputing, 2013Co-Authors: Adnene Guabtni, Rajiv Ranjan, Fethi A. RabhiAbstract:This paper is concerned with data provisioning services (information search, retrieval, storage, etc.) dealing with a large and heterogeneous information repository. Increasingly, this class of services is being hosted and delivered through Cloud infrastructures. Although such systems are becoming popular, existing resource management methods (e.g. Load-balancing techniques) do not consider workLoad patterns nor do they perform well when subjected to non-uniformly distributed datasets. If these problems can be solved, this class of services can be made to operate in more a scalable, efficient, and reliable manner. The main contribution of this paper is a approach that combines proprietary cloud-based Load balancing techniques and density-based partitioning for efficient range query processing across relational database-as-a-service in cloud computing environments. The study is conducted over a real-world data provisioning service that manages a large historical news database from Thomson Reuters . The proposed approach has been implemented and tested as a multi-tier web application suite consisting of Load-balancing, application, and database layers. We have validated our approach by conducting a set of rigorous performance evaluation experiments using the Amazon EC2 infrastructure. The results prove that augmenting a cloud-based Load-balancing service (e.g. Amazon Elastic Load Balancer) with workLoad characterization intelligence (density and distribution of data; composition of queries) offers significant benefits with regards to the overall system’s performance (i.e. query latency and database service throughput).