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Cloud Computing : Evaluation, as a platform for Scania ArchitectureSiddiqui, Muhammad Anas January 2013 (has links)
Cloud computing has been given a great deal of attention during recent years. Almost all the technology market leaders and leading hosting service providers (like IBM, Microsoft and Verizon) have entered into the Cloud market as Cloud Providers. Cloud computing promises to provide highly available, secure, low cost, agile and highly scalable solution to the consumers. Scania is a global company and one of the world’s leading heavy vehicle manufacturers with 35,000+ employees. All the large organizations such as Scania, aim to constantly update themselves with the latest technology in order to meet their business requirements but, these organizations must always be convinced that there is a strong reason(s) to implement new technology. This research provides the method and criteria in relation to initiating Cloud computing. A number of Scania’s specific business requirements that it is possible to map to the Cloud are addressed in this thesis. The methodology of research is split in two parts. Firstly, the identification of business cases at Scania and their requirements with the Cloud and Secondly, the evaluation and comparison of the functionalities and capabilities of different vendors. The accumulated data is then compared and suitable vendors, according to those business requirements are suggested. This thesis also shares the experience of moving on premise applications to the Cloud. These are Scania specific applications which are currently being hosted in-house. The research also addresses the possibilities of portability between the Cloud providers. Although there is no standardization in relation to Cloud computing, some initiatives such as OpenStack are available and its current position and some application and data migration tools are also discussed. The thesis concludes with a general discussion, recommendations in relation to adapting Cloud computing and selecting the Cloud provider. This recommendation applies to every organization including Scania.
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Mobile Cloud Computing: Offloading Mobile Processing to the CloudZambrano, Jesus 01 January 2015 (has links)
The current proliferation of mobile systems, such as smart phones, PDA and tablets, has led to their adoption as the primary computing platforms for many users. This trend suggests that designers will continue to aim towards the convergence of functionality on a single mobile device. However, this convergence penalizes the mobile system in computational resources such as processor speed, memory consumption, disk capacity, as well as in weight, size, ergonomics and the user’s most important component, battery life. Therefore, this current trend aims towards the efficient and effective use of its hardware and software components. Hence, energy consumption and response time are major concerns when executing complex algorithms on mobile devices because they require significant resources to solve intricate problems.
Current cloud computing environments for performing complex and data intensive computation remotely are likely to be an excellent solution for off-loading computation and data processing from mobile devices restricted by reduced resources. In cloud computing, virtualization enables a logical abstraction of physical components in a scalable manner that can overcome the physical constraint of resources. This optimizes IT infrastructure and makes cloud computing a worthy cost effective solution.
The intent of this thesis is to determine the types of applications that are better suited to be off-loaded to the cloud from mobile devices. To this end, this thesis quantitatively and
qualitatively compares the performance of executing two different kinds of workloads locally on two different mobile devices and remotely on two different cloud computing providers. The results of this thesis are expected to provide valuable insight to developers and architects of mobile applications by providing information on the applications that can be performed remotely in order to save energy and get better response times while remaining transparent to users.
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