Dispersed Data-driven Computing

September 25, 2017 - 11:15am to 12:15pm
Affiliation: 
University of Minnesota
Location: 
Keller Hall 3-180
Host: 
Faculty
ABSTRACT: Recent years have seen large quantities of data being generated across multiple geographic locations and from disparate sources such as users, servers, devices, and sensors dispersed around the globe. There is a growing demand to extract meaningful and timely knowledge from such diffuse data. At the same time, there has been a dramatic increase in the pervasiveness and heterogeneity of computing infrastructure: ranging from multiple data centers to computing resources on the edge of the network. These trends have resulted in the need for dispersed data-driven computing: computing with data originating at disparate locations, utilizing computational resources that are themselves highly distributed. In this talk, I will discuss the challenges of dispersed data-driven computing, and present some of our work on optimizing computation for such highly-distributed environments. I will present new scheduling algorithms we have developed to optimize data-intensive computing across data centers and the edge. In addition, I will describe new edge computing and storage infrastructures we are building to enable efficient dispersed data-intensive computing. 

BIO: Abhishek Chandra is an Associate Professor in the Department of Computer Science and Engineering at the University of Minnesota. His research interests are in the areas of Operating Systems and Distributed Systems, with current focus on performance and resource management in Cloud computing, Data-intensive computing, and Mobile computing platforms. He received his B.Tech. in Computer Science and Engineering from IIT Kanpur, India, and M.S. and PhD in Computer Science from the University of Massachusetts Amherst. He is a recipient of the NSF CAREER Award and IBM Faculty Award, an ACM Dissertation Award nominee, and a co-author on multiple Best Paper/Poster Awards.