This thesis discusses design and implementation of a cloud computer system which processes end-user monitoring data. Using a defined web service interface, the system is receiving raw monitoring data and then it processes them. Finally, it presents the data to end-users. Entire application is written in C# and deployed to the Windows Azure Platform.

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.

With the advent of cloud computing, resizable scalable infrastructures for data processing is now available to everyone. Software platforms and frameworks that support data intensive distributed applications such as Amazon Web Services and Apache Hadoop enable users to the necessary tools and infrastructure to work with thousands of scalable computers and process terabytes of data. However writing scalable applications that are run on top of these distributed frameworks is still a demanding and challenging task. The thesis aimed to advance the core scientific and technological means of managing, analyzing, visualizing, and extracting useful information from large data sets, collectively known as “big data”. The term “big-data” in this thesis refers to large, diverse, complex, longitudinal and/or distributed data sets generated from instruments, sensors, internet transactions, email, social networks, twitter streams, and/or all digital sources available today and in the future. We introduced architectures and concepts for implementing a cloud-based infrastructure for analyzing large volume of semi-structured and unstructured data. We built and evaluated an application prototype for collecting, organizing, processing, visualizing and analyzing data from the retail industry gathered from indoor navigation systems and social networks (Twitter, Facebook etc). Our finding was that developing large scale data analysis platform is often quite complex when there is an expectation that the processed data will grow continuously in future. The architecture varies depend on requirements. If we want to make a data warehouse and analyze the data afterwards (batch processing) the best choices will be Hadoop clusters and Pig or Hive. This architecture has been proven in Facebook and Yahoo for years. On the other hand, if the application involves real-time data analytics then the recommendation will be Hadoop clusters with Storm which has been successfully used in Twitter. After evaluating the developed prototype we introduced a new architecture which will be able to handle large scale batch and real-time data. We also proposed an upgrade of the existing prototype to handle real-time indoor navigation data.

The main objective of this diploma thesis is to design and develop a cloud hosted service that allows developers of games for Windows Phone 7 platform to extend their products with social and competitive aspect using Platform as a Service solution Windows Azure for hosting the backend of this system. The first part of the thesis analyses systems that are available on the market and that are providing similar services for the target platform. Based on this analysis, functional and general requirements for the future application are specified in the second part. Based on these requirements, use case analysis is made. The third part of the thesis is dedicated to description of the most important features, APIs and specifics of the Windows Phone 7 software platform. The fourth part is dedicated to Windows Azure as a Cloud platform both in terms of most important services, their characteristics and APIs used to utilise them and in terms of their business and pricing conditions. The fifth part addresses the architecture and the most important implementation details of the application. The final part contains the user guide for both the Windows Phone 7 application and for developers interested in using the library containing the API during the development of their game. The output of this thesis is the designed and implemented application with client-server architecture ready to have its backend deployed in Windows Azure environment and to have its frontend deployed on Windows Phone 7 devices. The client part of the system is comprised of a library intended for developers of games, which encapsulates the API needed to access the backend on the Internet, and a graphic frontend intended for end users. The server part, which contains most of the application logic, has REST interface. The applications architecture allows future development in terms of new functionality and expansion on more client platforms.

This thesis deals with developing applications on Windows Phone 7. The application focuses on two main target groups; cyclists and individuals who are confined to wheelchairs. Application offers the possibility of navigating around the city and over difficult terrain, and is divided into two parts - the client side application, and server side application. Development of the server side application will be analyzed in the thesis Development of map application for tracking in cloud - Server side on Windows Azure, by Vojtech Ruzicka. The primary objective of this thesis is to offer new solutions for development on Windows Phone 7, with attention being given to the communication between client and server. The second objective is to provide the public with the free application, which will help cyclists and handicapped individuals to navigate through cities around the world. The primary goal of this thesis will be achieved by identifying any problems that may arise during development, whereby a simplified description of the problem will be formed and a solution provided. Realization of the second goal will be in the use of application by the public, by providing them with an efficient means of increasing their mobility throughout their surroundings.

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.

High Performance Computing (HPC) applications are data-intensive scientific software requiring significant CPU and data storage capabilities. Researchers have examined the performance of Amazon Elastic Compute Cloud (EC2) environment across several HPC benchmarks; however, an extensive HPC benchmark study and a comparison between Amazon EC2 and Windows Azure (Microsoft’s cloud computing platform), with metrics such as memory bandwidth, Input/Output (I/O) performance, and communication computational performance, are largely absent. The purpose of this study is to perform an exhaustive HPC benchmark comparison on EC2 and Windows Azure platforms. We implement existing benchmarks to evaluate and analyze performance of two public clouds spanning both IaaS and PaaS types. We use Amazon EC2 and Windows Azure as platforms for hosting HPC benchmarks with variations such as instance types, number of nodes, hardware and software. This is accomplished by running benchmarks including STREAM, IOR and NPB benchmarks on these platforms on varied number of nodes for small and medium instance types. These benchmarks measure the memory bandwidth, I/O performance, communication and computational performance. Benchmarking cloud platforms provides useful objective measures of their worthiness for HPC applications in addition to assessing their consistency and predictability in supporting them.

Práce se zabývá popisem tvorby mobilního systému pro monitoring zákaznické spokojenosti a sběr zpětné vazby od návštěvníků v restauracích s názvem Huerate. Komplexně jsou popsané všechny fáze vývoje systému. První část práce se zabývá analýzou existujících řešení a stavem na trhu. Následně jsou na základně komunikace s majiteli restaurací sestaveny požadavky na systém. Nakonec se práce věnuje samotnému návrhu systému, jeho implementaci a nasazení v restauracích. Systém Huerate běží jako webová aplikace a je dostupný na adrese http://huerate.cz.