Assistant Research Professor
Rutgers Discovery Informatics Institute (RDI2)
NSF Center for Cloud and Autonomic Computing (CAC)
Rutgers, The State University of New Jersey
96 Frelinghuysen Road, Piscataway, NJ 08854
Javier Diaz-Montes is currently Assistant Research Professor at Rutgers University and a member of the Rutgers Discovery Informatics Institute (RDI2) and Cloud and Autonomic Computing Center (CAC). He received his PhD degree in Computer Science from the Universidad de Castilla-La Mancha (UCLM), Spain ("Doctor Europeus", Feb. 2010). Before joining Rutgers, he was Postdoctoral Fellow of the Pervasive Technology Institute at Indiana University and member of the Community Grid Lab .
His research interests are in the area of parallel and distributed computing and include autonomic computing, cloud computing, grid computing, virtualization, middleware, and scheduling. Currently, his research is focused on providing novel ways of orchestrating geographically distributed resources - including supercomputers, storage systems, IoT devices, computational grids, and clouds - to enable the execution of large-scale scientific and business workflows. Specifically, he is looking at how to combine cloud abstractions with software-defined environments techniques to provision the appropriate computational environment at the right time and adapt this environment to changes in users’ requirements or resources capabilities and capacities. This includes understanding how to provision network paths, e.g., using software-defined networks (SDN), to enable in-network processing of data while it is migrated across the network. In the past, he worked at the infrastructure level defining and managing the whole life cycle of OS images for IaaS and bare-metal, and exploring ways of dynamically provisioning customized environments, such as virtual clusters, Hadoop clusters, or IaaS frameworks, onto cloud and bare-metal infrastructures.
Currently, I am leading the research effort around the CometCloud Project. CometCloud is an autonomic framework for enabling real-world applications on dynamically federated, hybrid infrastructures integrating (public & private) clouds, HPC data-centers and Grids.
Previously I worked in the FutureGrid Project leading the development of FutureGrid Rain. Rain is a tool that will allow users to place customized environments like virtual clusters or IaaS frameworks onto resources. The process of raining goes beyond the services offered by existing scheduling tools due to its higher-level toolset targeting virtualized and non-virtualized resources. Rain will be able to move resources from one infrastructure to another, compare the execution of an experiment in the different supported infrastructures, and easily deploy full environments like Hadoop on different infrastructures using user's customized images.
Rain is supported by a flexible image management framework, which defines the full life cycle of the images in FutureGrid. It involves the process of creating, customizing, storing, sharing and registering images for different FutureGrid environments. To this end, we have develop several components to perform the different tasks involved. First, we have an Image Generation tool that creates and customizes images according to user requirements. The second component is the Image Repository, which is in charge of storing, cataloging and sharing images. The last component is an Image Registration tool, which prepares, uploads and registers images for specific environments, like HPC or cloud frameworks. It also decides if an image is secure enough to be registered or if it needs additional security tests.