Award Abstract # 1409426
CSR: Medium: Collaborative Research: Towards Finer-grained Cloud Computing

NSF Org: CNS
Division Of Computer and Network Systems
Recipient: DUKE UNIVERSITY
Initial Amendment Date: July 31, 2014
Latest Amendment Date: August 9, 2017
Award Number: 1409426
Award Instrument: Continuing Grant
Program Manager: Marilyn McClure
mmcclure@nsf.gov
 (703)292-5197
CNS
 Division Of Computer and Network Systems
CSE
 Directorate for Computer and Information Science and Engineering
Start Date: August 1, 2014
End Date: February 28, 2018 (Estimated)
Total Intended Award Amount: $361,716.00
Total Awarded Amount to Date: $361,716.00
Funds Obligated to Date: FY 2014 = $159,557.00
FY 2016 = $0.00

FY 2017 = $0.00
History of Investigator:
  • Theophilus Benson (Principal Investigator)
    theophilus@cmu.edu
Recipient Sponsored Research Office: Duke University
2200 W MAIN ST
DURHAM
NC  US  27705-4640
(919)684-3030
Sponsor Congressional District: 04
Primary Place of Performance: Duke University
NC  US  27705-4010
Primary Place of Performance
Congressional District:
04
Unique Entity Identifier (UEI): TP7EK8DZV6N5
Parent UEI:
NSF Program(s): Special Projects - CNS,
CSR-Computer Systems Research
Primary Program Source: 01001415DB NSF RESEARCH & RELATED ACTIVIT
01001617DB NSF RESEARCH & RELATED ACTIVIT

01001718DB NSF RESEARCH & RELATED ACTIVIT
Program Reference Code(s): 7924
Program Element Code(s): 171400, 735400
Award Agency Code: 4900
Fund Agency Code: 4900
Assistance Listing Number(s): 47.070

ABSTRACT

Over the past few years, cloud computing services like Amazon's EC2 have commoditized computing resources. Despite this success, cloud computing primarily targets users whose virtual machines (VMs) are rarely idle, as cloud users are typically billed for the amount of time the VM is awake, not how much work it does. Thus, services that are long-lived but mostly idle a significant fraction of the time are prohibitively expensive for many potential users of cloud computing. In this project, the PIs are developing a finer-grained model of cloud computation based around lightweight instances. Lightweight instances are more akin to processes than virtual machines; they allow clients to only pay for their actual usage of cloud resources, and to not have the complexity and overhead of running an entire operating system. The lightweight instance approach has the potential to bring the benefits of cloud computing to a variety of users for whom it is a poor fit today. The PIs are exploring a new, finer-granularity model for cloud computing, wherein the cloud makes it appear that all client instances are running all the time, but may actually swap them out while idle to permit statistical multiplexing. Compared to today's VM-based model and container-based model, the proposed process-based model provides a much higher level of abstraction, and lets clients run long-lived, mostly-idle services much more cheaply than is possible today. If successful, the research would open up a wide variety of new applications and architectures: processes could cheaply be run in the cloud on behalf of end users, providing them with the ability to run long-lived services cheaply.

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