7 research outputs found
A Novel Technique for Task Re-Allocation in Distributed Computing System
A distributed computing is software system in which components are located on different attached computers can communicate and organize their actions by transferring messages. A task applied on the distributed system must be reliable and feasible. The distributed system for instance grid networks, robotics, air traffic control systems, etc. exceedingly depends on time. If not detected accurately and recovered at the proper time, a single error in real time distributed system can cause a whole system failure. Fault-tolerance is the key method which is mostly used to provide continuous reliability in these systems. There are some challenges in distributed computing system such as resource sharing, transparency, dependability, Complex mappings, concurrency, Fault tolerance etc. In this paper, we focus on fault tolerance which is responsible for the degradation of the system. A novel technique is proposed based upon reliability to overcome fault tolerance problem and re-allocate the task.
DOI: 10.17762/ijritcc2321-8169.15080
Partitioning workflow applications over federated clouds to meet non-functional requirements
PhD ThesisWith cloud computing, users can acquire computer resources when they need them
on a pay-as-you-go business model. Because of this, many applications are now being
deployed in the cloud, and there are many di erent cloud providers worldwide. Importantly,
all these various infrastructure providers o er services with di erent levels
of quality. For example, cloud data centres are governed by the privacy and security
policies of the country where the centre is located, while many organisations have
created their own internal \private cloud" to meet security needs.
With all this varieties and uncertainties, application developers who decide to host their
system in the cloud face the issue of which cloud to choose to get the best operational
conditions in terms of price, reliability and security. And the decision becomes even
more complicated if their application consists of a number of distributed components,
each with slightly di erent requirements.
Rather than trying to identify the single best cloud for an application, this thesis
considers an alternative approach, that is, combining di erent clouds to meet users'
non-functional requirements. Cloud federation o ers the ability to distribute a single
application across two or more clouds, so that the application can bene t from the
advantages of each one of them. The key challenge for this approach is how to nd the
distribution (or deployment) of application components, which can yield the greatest
bene ts. In this thesis, we tackle this problem and propose a set of algorithms, and a
framework, to partition a work
ow-based application over federated clouds in order to
exploit the strengths of each cloud. The speci c goal is to split a distributed application
structured as a work
ow such that the security and reliability requirements of each
component are met, whilst the overall cost of execution is minimised.
To achieve this, we propose and evaluate a cloud broker for partitioning a work
ow
application over federated clouds. The broker integrates with the e-Science Central
cloud platform to automatically deploy a work
ow over public and private clouds.
We developed a deployment planning algorithm to partition a large work
ow appli-
- i -
cation across federated clouds so as to meet security requirements and minimise the
monetary cost.
A more generic framework is then proposed to model, quantify and guide the partitioning
and deployment of work
ows over federated clouds. This framework considers
the situation where changes in cloud availability (including cloud failure) arise during
work
ow execution
Improving reliability of service oriented systems with consideration of cost and time constraints in clouds
Web service technology is more and more popular for the implementation of service oriented systems. Additionally, cloud computing platforms, as an efficient and available environment, can provide the computing, networking and storage resources in order to decrease the budget of companies to deploy and manage their systems. Therefore, more service oriented systems are migrated and deployed in clouds. However, these applications need to be improved in terms of reliability, for certain components have low reliability. Fault tolerance approaches can improve software reliability. However, more redundant units are required, which increases the cost and the execution time of the entire system. Therefore, a migration and deployment framework with fault tolerance approaches with the consideration of global constraints in terms of cost and execution time may be needed.
This work proposes a migration and deployment framework to guide the designers of service oriented systems in order to improve the reliability under global constraints in clouds. A multilevel redundancy allocation model is adopted for the framework to assign redundant units to the structure of systems with fault tolerance approaches. An improved genetic algorithm is utilised for the generation of the migration plan that takes the execution time of systems and the cost constraints into consideration. Fault tolerant approaches (such as NVP, RB and Parallel) can be integrated into the framework so as to improve the reliability of the components at the bottom level. Additionally, a new encoding mechanism based on linked lists is proposed to improve the performance of the genetic algorithm in order to reduce the movement of redundant units in the model.
The experiments compare the performance of encoding mechanisms and the model integrated with different fault tolerance approaches. The empirical studies show that the proposed framework, with a multilevel redundancy allocation model integrated with the fault tolerance approaches, can generate migration plans for service oriented systems in clouds with the consideration of cost and execution time