A Framework for Divisible Load E-science Applications in Optical Grids

E-science applications require discovering, collecting, transferring and processing large volumes of scientific data. In divisible load e-science applications, data is generated and stored in geographically distributed repositories (e.g., instruments, sensors, cam- eras, satellites and storage facilities). The generated data can be divided into in- dependent subsets to be analysed distributed at many computing locations. Such applications usually require optical networking for fast and reliable data transfer. In this thesis, we propose a framework for divisible load applications in optical grids. Within this framework, schedulers are developed to co-schedule computational and optical network resources. Moreover, processes to handle divisible load applications in different architectures including centralized, hierarchical, peer-to-peer and super- peer are proposed. Fault management techniques are introduced to handle network faults by considering distinctive characteristics of e-science applications and optical grids. This research conducts a comprehensive study of different algorithms, tech- niques and processes that have been introduced within the framework. The results provide guidelines to build more efficient, scalable and reliable optical grid systems. The results can serve as a guide to the best choices in selecting the scheduling algo- rithms, fault management techniques and architectures according to different network and application parameters.

Name thesis:degree_name

Doctor of Philosophy (PhD)

Level thesis:degree_level

Doctoral -- first

Discipline thesis:degree_discipline

Engineering - Electronic Systems

Grantor dc:publisher

Faculty of Graduate Studies and Research, University of Regina

Year dc:date.issued

2013

Author dc:creator

• Abouelela, Mohamed Moustafa Mohamed

Advisor dc:contributor.advisor

• El-Darieby, Mohamed

Committee members dc:contributor.committeemember

• Gelowitz, Craig M.
• Mouhoub, Malek
• Mehrandezh, Mehran

Language dc:language.iso

en

DOI

https://doi.org/10.82465/4981

OAI identifier oai:identifier

oai:uregina.scholaris.ca:10294/3834