Title :
Resource management in data-intensive clouds: Opportunities and challenges
Author :
Irwin, David ; Shenoy, Prashant ; Cecchet, Emmanuel ; Zink, Michael
Author_Institution :
Comput. Sci. Dept., Univ. of Massachusetts, Amherst, Amherst, MA, USA
Abstract :
Today´s cloud computing platforms have seen much success in running compute-bound applications with time-varying or one-time needs. In this position paper, we will argue that the cloud paradigm is also well suited for handling data-intensive applications, characterized by the processing and storage of data produced by high-bandwidth sensors or streaming applications. The data rates and the processing demands vary over time for many such applications, making the on-demand cloud paradigm a good match for their needs. However, today´s cloud platforms need to evolve to meet the storage, communication, and processing demands of data-intensive applications. We present an ongoing GENI project to connect high-bandwidth radar sensor networks with computational and storage resources in the cloud and use this example to highlight the opportunities and challenges in designing end-to-end data-intensive cloud systems.
Keywords :
Internet; data handling; resource allocation; GENI project; cloud computing; data-intensive application; high-bandwidth sensor; radar sensor network; resource management; Cloud computing; Computer architecture; Cost function; IP networks; Jacobian matrices; Local area networks; Logic; Resource management; Web and internet services; Wide area networks;
Conference_Titel :
Local and Metropolitan Area Networks (LANMAN), 2010 17th IEEE Workshop on
Conference_Location :
Long Branch, NJ
Print_ISBN :
978-1-4244-6067-0
DOI :
10.1109/LANMAN.2010.5507156