الفهرس 
Overview
ObjectiveOnly 14 pages are availabe for public view
Abstract
Cloud computing is a promising computing model that provides a
combination of parallel and distributed computing paradigms. It has the
characteristics of on demand provisioning of a shared pool of configurable
computing resources as a service. It provides a cost effective paradigm of
computational, storage and database resources to users over the internet.
Cloud storage is an important service that is provided by the cloud computing
system. It provides the data owners with high accessibility, availability and
scalability in respect to increasing the amount of their data in cloud repositories. The
increasing number of user’s requesting data from deployed virtual instances can lead
to increased loads on the cloud data management system.
Multiple queries compete for hardware resources causing resource contention
with rapidly changing computational properties and efficient concurrent query
executions on especially structured data has become an important challenge.
Moreover, it offers numerous benefits regarding better utilization of virtual instances
by exploiting parallel executions.
This thesis proposes an optimized concurrent queries execution to reduce
node contention and handle the degradation in the query processing performance.
Our proposed approach combines efficient query optimization and scheduling
techniques. Furthermore, it considers the virtual instances load control based on
database replication to improve the query processing performance and in addition, it
involves a feedback loop comprising of observing, planning and responding to any
overloaded node during the query execution.
The evaluation of the proposed query processing approach is conducted over
a real world cloud using the Amazon EC2 infrastructure provisioning service. The
results prove a significant benefit with regards to the overall query processing
performance