Changes between Version 19 and Version 20 of GEC21Agenda/EveningDemoSession
- Timestamp:
- 10/17/14 16:03:46 (9 years ago)
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GEC21Agenda/EveningDemoSession
v19 v20 143 143 * Derek Meyer, dmeyer@cs.wisc.edu, Wisconsin Wireless and NetworkinG Systems (WiNGS) Laboratory 144 144 145 ==== Middleware for Hadoop-in-a-Hybrid-Cloud ==== 146 147 !MapReduce is a programming model for processing and generating large data sets, and Hadoop, a !MapReduce implementation, is a good tool to handle Big Data. Cloud computing with its ubiquitous characteristic, on demand and dynamic resource provisioning at low cost has potential to be the environment to treat big data. However, using Hadoop on the cloud spends time and requires technical knowledge from users. The hybrid cloud leverages these requirements, because it’s necessary to evaluate the resources in private cloud and, if necessary, obtain and prepare on-demand resources in the public cloud. Moreover, the simultaneous management of private and public domains requires an appropriate model that combines performance with minimal cost. We propose an architecture to make the orchestration of Hadoop applications in hybrid clouds. The core of the model consists of a web portal for submissions, an orchestration engine and an execution services factory. Through these three components it’s possible to automate the preparation of a cross-domain cluster, performing the provisioning of files involved, managing the execution of the application, and making the results available to the user. 148 149 Participants: 150 * Xuan Liu, xuan.liu@mail.umkc.edu, Univ. of Missouri-Kansas City 151 145 152 ==== Dynamic Virtual Router Failure Recovery ==== 146 153 147 154 Network virtualization allows flexibility to configure virtual networks in a dynamic manner. In such a setting, to provide resilient services to virtual networks, we consider the situation where the substrate network provider wants to have standby virtual routers ready to serve the virtual networks in the event of a failure. Such a failure can affect one or more virtual routers in multiple virtual networks. The goal of our work is to make the optimal selection of standby virtual routers so that virtual networks can be dynamically reconfigured back to their original topologies after a failure. We present an optimization formulation and a preliminary implementation on GENI testbed by applying the idea behind the model. The selection metrics considered are geographical location and the VM load on the standby virtual router's host machine. 148 149 155 150 156 Participants: