Grid Support
           
Event Type Start Time End Time Rm # Chair  

 

Paper 1:30PM 2:00PM 38-39 Xian-He Sun (Illinois Institute of Technology )
 
Title:

Synthesizing Realistic Computational Grids
  Speakers/Presenter:
Dong Lu (Northwestern University), Peter August Dinda (Northwestern university)

 

Paper 2:00PM 2:30PM 38-39 Xian-He Sun (Illinois Institute of Technology )
 
Title:

Traffic-based Load Balance for Scalable Network Emulation
  Speakers/Presenter:
Xin Liu (UCSD), Andrew A. Chien (UCSD)

 

Paper 2:30PM 3:00PM 38-39 Xian-He Sun (Illinois Institute of Technology )
 
Title:

A Self-Organizing Flock of Condors
  Speakers/Presenter:
Ali Raza Butt (Purdue University), Rongmei Zhang (Purdue University), Y. Charlie Hu (Purdue University)
             

 

     
  Session: Grid Support
  Title: Synthesizing Realistic Computational Grids
  Chair: Xian-He Sun (Illinois Institute of Technology )
  Time: Tuesday, November 18, 1:30PM - 2:00PM
  Rm #: 38-39
  Speaker(s)/Author(s):  
  Dong Lu (Northwestern University), Peter August Dinda (Northwestern university)
   
  Description:
  Realistic workloads are essential in evaluating middleware for computational grids. One important component is the raw grid itself: a network topology graph annotated with the hardware and software available on each node and link. This paper defines our requirements for grid generation and presents GridG, our extensible generator. We describe GridG in two steps: topology generation and annotation. For topology generation, we have both model and mechanism. We extend Tiers, an existing tool from the networking community, to produce graphs that obey recently discovered power laws of Internet topology. We also contribute to network topology theory by illustrating a contradiction between two laws and proposing a new version of one of them. For annotation, GridG captures intra- and inter-host correlations between attributes using conditional probability rules. We construct a set of rules, including one based on empirical evidence of OS concentration in subnets, that produce sensible host annotations.
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  Session: Grid Support
  Title: Traffic-based Load Balance for Scalable Network Emulation
  Chair: Xian-He Sun (Illinois Institute of Technology )
  Time: Tuesday, November 18, 2:00PM - 2:30PM
  Rm #: 38-39
  Speaker(s)/Author(s):  
  Xin Liu (UCSD), Andrew A. Chien (UCSD)
   
  Description:
  Load balance is critical to achieving scalability for large network emulation studies, which are of compelling interest for emerging Grid, Peer to Peer, and other distributed applications and middleware. Achieving load balance in emulation is difficult because of irregular network structure and unpredictable network traffic. We formulate load balance as a graph partitioning problem and apply classical graph partitioning algorithms to it. Using a large-scale network emulation system called MaSSF, we explore three approaches for partitioning, based on purely static topology information, combining topology and application placement information, and combining topology and application profile data. These studies show that exploiting topology and application placement information can achieve reasonable load balance, but a profile-based approach further improves load balance for even large scale network emulation. In our experiments, PROFILE improves load balance by 50% to 66% and emulation time is reduced up to 50% compared to purely static topology-based approaches.
  Link: Download PDF
   

 

     
  Session: Grid Support
  Title: A Self-Organizing Flock of Condors
  Chair: Xian-He Sun (Illinois Institute of Technology )
  Time: Tuesday, November 18, 2:30PM - 3:00PM
  Rm #: 38-39
  Speaker(s)/Author(s):  
  Ali Raza Butt (Purdue University), Rongmei Zhang (Purdue University), Y. Charlie Hu (Purdue University)
   
  Description:
  Condor provides high throughput computing by leveraging idle-cycles on off-the-shelf desktop machines. It also supports flocking, a mechanism for sharing resources among Condor pools. Since Condor pools distributed over a wide area can have dynamically changing availability and sharing preferences, the current flocking mechanism based on static configurations can limit the potential of sharing resources across Condor pools. This paper presents a technique for resource discovery in distributed Condor pools using peer-to-peer mechanisms that are self-organizing, fault-tolerant, scalable, and locality-aware. Locality-awareness guarantees that applications are not shipped across long distances when nearby resources are available. Measurements using a synthetic job trace show that self-organized flocking reduces the maximum job wait time in queue for a heavily loaded pool by a factor of 10 compared to without flocking. Simulations of 1000 Condor pools are also presented and the results confirm that our technique discovers and utilizes physically nearby resources.

This paper has been nominated for the Best Student Paper of SC2003 award.
  Link: Download PDF