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Abhishek Chandra


Research

My areas of interest span Operating Systems, Distributed Systems, and Computer Networks. Within these disciplines, I work mainly in the areas of resource management, scheduling, and performance analysis. I am interested in performance issues in a variety of distributed systems: Clouds, Volunteer Grids, Data centers, and Mobile platforms. The key focus of my work has been
(i) to provide system support for data- and compute-intensive applications, and
(ii) making these systems self-managing and reliable.

My research involves developing resource management techniques geared towards achieving the following goals in these platforms:

  • Scalability over large scales and heterogeneous components.
  • Reliability and fault tolerance in the face of frequent and diverse failures.
  • Adaptability to changing workloads and resource availability.
  • QoS guarantees and service differentiation for hosted applications and services.
  • Energy efficiency for battery-constrained devices as well as data centers.

Publications

A complete list of my publications is available here. Please note that this list is generally more up-to-date than the list of projects below.

Projects

Currently, I am working on a number of projects involving issues in data-intensive computing (e.g., Hadoop/MapReduce), user-cloud interactions (e.g., via mobile devices and edge hosts), and virtualization. Some of my current projects include:
  • Mobilizing the Cloud: Cloud-based Mobile Outsourcing
  • Data-intensive Computing in Non-traditional Environments: Executing data-intensive applications (e.g., MapReduce) in virtualized and highly distributed (wide-area) environments
  • Nebula: Using Distributed Edge Resources to build Decentralized Clouds
  • Virtual Putty: Reshaping Virtual Machine Footprints in Shared Virtualized Environments
Some earlier projects that I worked on:
  • Cloud Proxies: Using Proxies to Accelerate Multi-Cloud Data-Intensive Applications
  • RADAR: Resource Aggregation for the Discovery and Allocation of Wide-Area Resources
  • FAILSafe: Failure Analysis and Inference in Large-Scale Systems
  • RIDGE: Reliable Service Infrastructure in Donation-based Grid Environments
  • COSMOS: Cluster-of-Servers based Multimedia Operating System
  • QLinux: QoS-enhanced Linux Kernel for supporting multimedia applications

The views and opinions expressed in this page are strictly those of the page author.
The contents of this page have not been reviewed or approved by the University of Minnesota.