Yehia El-khatib and Chris Edwards. "A Survey-based Study of Grid Traffic". In Proceedings of the International Conference on Networks for Grid Applications (GridNets 2007), Lyon, France, October 17-19 2007.

1. Diversity of Grid Traffic:
A Survey-based Study
Yehia El khatib, Christopher Edwards
Computing Department
Lancaster University

2. Outline
Introduction
Survey Goals
Survey Process
Survey Results
Traffic Behaviour
Future Work
Conclusion

3. Introduction
EC-GIN (Europe-China Grid InterNetworking) is
a Framework 6 STREP project.
EC-GIN aims at introduction a networking
interface that provides programming
abstractions to improve the performance of grid
applications.
The design of the interface requires an
understanding of the network characteristics of
grid applications.

4. Survey Goals
The survey is to highlight some of the
characteristics of current grid applications
Scale and composition of the grid
Dataset granularity
Data delivery requirements (time restrictions,
encryptions, one-to-many services)
Others: transport layer protocol, middleware, etc.
Special network services

5. Survey Process
Questionnaire Structure
2 pages, also an online version
11 MCQ's + 1 open-ended question.
Level of Detail
As simple as possible.
Target Audience
Developers, administrators, and advanced users.
Dissemination
Research projects that are employing or developing
a grid application.

6. Survey Results [outline]
1. Research Field
2. Scale
3. Composition
4. Dataset Granularity
5. Special Network Services

7. Survey Results [1/5]
Research Field
Software Visualization
Particle
Development 6%
Physics
6%
18%
Meteorology
6%
Medicine
6%
Astronomy
Environmental
13%
Sciences
6%
Engineering
13%
Social Sciences
Mathematical
13% Analysis
13%

8. Survey Results [2/5]
Scale
55 75
70
50
% o f t h e su r v e y e d a p p lica t io n s
65
% o f s u r v e y e d a p p lic a t io n s
45 60
40 55
50
35
45
30 40
25 35
30
20
25
15 20
15
10
10
5 5
0 0
< = 10 10-100 100-400 400-1000 > 1000 3 – 10 10 – 100 100 – 1000 > = 1000
Num ber of nodes Number of domains

9. Survey Results [3/5]
Composition
Overall Grid Com posit ion
Clusters
Desk top
Machines
Em bedded
Dev ices
Mobile
Dev ices

10. Survey Results [3/5]
Composition
Overall Grid Com posit ion
47% are deployed only on clusters
Image analysis applications
Simulation applications Clusters
Desk top
Machines
Em bedded
Dev ices
Mobile
7% are deployed only on desktop Dev ices
machines
Data management applications

11. Survey Results [4/5]
Dataset Granularity
30 100
80
20
60
40
10
20
0 0
10 kB 100 kB 1 MB 10 MB 100 MB 1 GB 10 GB 100 GB 1 TB 10 kB 100 kB 1 MB 10 MB 100 MB 1 GB 10 GB 100 GB 1 TB

12. Survey Results [4/5]
Dataset Granularity
30 100
80
20
60
40
10
20
0 0
10 kB 100 kB 1 MB 10 MB 100 MB 1 GB 10 GB 100 GB 1 TB 10 kB 100 kB 1 MB 10 MB 100 MB 1 GB 10 GB 100 GB 1 TB
Most common dataset size is 10 MB 23% of all datasets are ≤ 1 MB
12% of all datasets are 100 GB in size 50% of all datasets are ≤ 10 MB
25% of all datasets are ≥ 10 GB

13. Survey Results [5/5]
Special Network Services
100%
% of surveyed applicat ions
80%
60%
Not Sure
Unnecessary
40% Would Be Used
Used
20%
%
Tran sfer Ad van ced Net work
Delay Pre - Net work Top olog y
d ict ion Reservat ion In form at ion

14. Traffic Behaviour [1/2]
The results give an image of the traffic flow
sizes that is different from common belief.
We define five distinct classes of applications
according to dataset sizes:
Class A: less than 10 MB
Class B: 0.5 – 100 MB
Class C: 10 MB – 1 GB
Class D: 100 kB – 100 GB
Class E: 1 MB – 1 TB

15. Traffic Behaviour [2/2]
E
20%
The most common class is A,
A
where datasets are no larger
34% than 10 MB.
Only 33% of all applications
D
13%
have datasets over 1 GB in
size.
Only 20% of all applications
C
B
have datasets that stretch
13%
20% beyond 100 GB.
All class C applications are deployed on mostly desktop
machines.
All class B applications are Astronomy and Meteorology
applications, deployed over 100-300 nodes across 6-8
domains.

16. Future Work
We intend to monitor the traffic created by a
number of grid applications.
We aim to present mathematical models of grid
traffic that could be used to create artificial grid
traffic (in simulators).

17. Conclusion
We presented the outcome of a survey of grid
application requirements and network
behaviour.
The results reflect a list of real demands of grid
applications, which provides a solid starting
point to the design of our interface.
The suggested classification portrays the
diversity in the traffic footprint of grid
applications.