dc.contributor.author |
Goteng, Gokop |
- |
dc.contributor.author |
Tiwari, Ashutosh |
- |
dc.contributor.author |
Roy, Rajkumar |
- |
dc.contributor.editor |
Editor |
- |
dc.date.accessioned |
2011-10-11T08:02:28Z |
|
dc.date.available |
2011-10-11T08:02:28Z |
|
dc.date.issued |
2007-03-01T00:00:00Z |
- |
dc.identifier.citation |
Gokop Goteng, Ashutosh Tiwari and Rajkumar Roy, Grid computing for engineering design optimisation: Evolution and future trends, Decision Engineering Report Series, March 2007, Cranfield University. |
- |
dc.identifier.uri |
http://dspace.lib.cranfield.ac.uk/handle/1826/4326 |
|
dc.description.abstract |
Grid Computing is fast gaining ground both within academia and the commercial
sectors. It has shifted from its traditional scientific-based applications to
serviceoriented problem solving environments for commerce and business.
Engineering design optimisation (EDO) is characteristically computationally and
data intensive. EDO is also a multidisciplinary field which requires the
collaboration of different domain experts to work on a design to yield improved
versions. Grid Computing offers a suitable platform for design engineers to
collaboratively work together and share knowledge and expertise in addition to
the computational and data facility that can be combined to bear on complex
designs. In this paper, the trend of Grid Computing evolution shows a clear
emergence of application areas, starting from computational grid, data grid,
visualisation grid and semantic grid to service-oriented problem solving
environments (SO-PSE). This evolution is classified as first, second and third
generation of Grid Computing for the purpose of understanding how researchers
have tried to provide solutions to the problems and challenges in implementing
Grid applications. The future of Grid Computing research areas such as autonomic
computing, ubiquitous computing and economic Grid models as well as concurrent
engineering design problem solving environments feature in the report. Autonomic
computing enables grid services and resources to have self-management, self
adjustable and adaptability to changing and dynamic situations using agent-based
technology while ubiquitous computing allows computers to perceive the
environment and act accordingly. |
en_UK |
dc.subject |
Engineering design optimisation |
en_UK |
dc.subject |
Grid computing |
en_UK |
dc.subject |
Problem solving environments |
en_UK |
dc.subject |
Service-oriented architecture |
en_UK |
dc.title |
Grid computing for engineering design optimisation: Evolution and future trends |
en_UK |
dc.type |
Report |
- |