A comparison of resource allocation process in grid and cloud technologies

Grid Computing and Cloud Computing are two different technologies that have emerged to validate the long-held dream of computing as utilities which led to an important revolution in IT industry. These technologies came with several challenges in terms of middleware, programming model, resources management and business models. These challenges are seriously considered by Distributed System research. Resources allocation is a key challenge in both technologies as it causes the possible resource wastage and service degradation. This paper is addressing a comprehensive study of the resources allocation processes in both technologies. It provides the researchers with an in-depth understanding of all resources allocation related aspects and associative challenges, including: load balancing, performance, energy consumption, scheduling algorithms, resources consolidation and migration. The comparison also contributes an informal definition of the Cloud resource allocation process. Resources in the Cloud are being shared by all users in a time and space sharing manner, in contrast to dedicated resources that governed by a queuing system in Grid resource management. Cloud Resource allocation suffers from extra challenges abbreviated by achieving good load balancing and making right consolidation decision

Deploying application modules over multiple clouds

Deploying and managing, in an efficient and adaptive way, complex multi-service applications over technologically dissimilar cloud environments is one of the problems that have emerged with the cloud revolution. In this work, we have studied suitable techniques to determine the distribution of application modules onto multiple available clouds while respecting QoS (Quality of Service) properties and technology requirements specified for individual application modules. For this purpose, we have proposed parametric allocation algorithm based on three selection criteria, i.e., Cost, QoS and Hybrid (Cost and QoS). In order to maximize the performance of the whole application—when the performance of the whole application is dominated by the performance of communicating modules—we have proposed the allocation of intensively communicating modules on a single provider using the same selection criteria (Cost, QoS and Hybrid)