In the era of mobile cloud computing, the consumption of virtualized software and Web-based services from super-back-end infrastructure using smartphones and tablets is gaining much research attention from both the industry and academia. Nowadays, these mobile devices generate and access multimedia data hosted in social media and other sources in order to enhance the users’ multimedia experience. However, multimedia data is unstructured which can lead to challenges with data synchronization between these mobile devices and the cloud computing back-end. The issue with data synchronization is further fueled by the fact that mobile devices can experience intermittent connectivity losses due to unstable wireless bandwidths. While previous works proposed Simple Object Access Protocol (SOAP) -based middleware for the Web services’ synchronization, this approach is not efficient in a mobile environment because the SOAP protocol is verbose. Thus, the Representational State Transfer (REST) standard has been proposed recently to model the Web services since it is lightweight. This thesis proposes a novel approach for implementing a REST-based mobile Web Service for multimedia file sharing that utilizes a channel-based publish/subscribe communication scheme to synchronize smartphone or tablet-hosted NoSQL databases with a cloud-hosted NoSQL database. This thesis evaluates the synchronicity and the scalability of a prototype system that was implemented according to this approach. Also, this thesis assesses the overhead of the middleware component of the system.

NoSQL databases are widely used for many applications as a technology for data storage, and their usage and popularity rises. The first aim of the thesis is to research the existing approaches and technologies for schema evolution in NoSQL databases. Next, we introduce an approach for schema evolution in multi-model databases with a unified interface for the most common data models. The proposed approach is easy to use and covers the common migration scenarios. We have also implemented a prototype, optimized its read/write operations, and demonstrated its properties on real-world data. 1

Context. Apache Cassandra is an open-source, scalable, NoSQL database that distributes the data over many commodity servers. It provides no single point of failure by copying and storing the data in different locations. Cassandra uses a ring design rather than the traditional master-slave design. Virtualization is the technique using which physical resources of a machine are divided and utilized by various virtual machines. It is the fundamental technology, which allows cloud computing to provide resource sharing among the users.  Objectives. Through this research, the effects of virtualization on Cassandra are observed by comparing the virtual machine arrangement to physical machine arrangement along with the overhead caused by virtualization.  Methods. An experiment is conducted in this study to identify the aforementioned effects of virtualization on Cassandra compared to the physical machines. Cassandra runs on physical machines with Ubuntu 14.04 LTS arranged in a multi node cluster. Results are obtained by executing the mixed, read only and write only operations in the Cassandra stress tool on the data populated in this cluster. This procedure is repeated for 100% and 66% workload. The same procedure is repeated in virtual machines cluster and the results are compared.  Results. Virtualization overhead has been identified in terms of CPU utilization and the effects of virtualization on Cassandra are found out in terms of Disk utilization, throughput and latency.  Conclusions. The overhead caused due to virtualization is observed and the effect of this overhead on the performance of Cassandra has been identified. The consequence of the virtualization overhead has been related to the change in performance of Cassandra.

Speed is a very important factor in websites and other types of applications and almost all applications stores some type of data, normally in a database. For an example a blog typically saves users, posts and comments. There’s a high risk that as the amount of data in the database grows, the time for inserting and requesting specific data increases. If it takes more than some seconds to view a specific page, a user will normally leave the site. However, it’s a fact that the database will grow while the application will become more popular but it’s possible to save a lot of time if using right database, and structure. In this thesis MongoDB and MySQL will be compared with focus on time consumption. SQL (Structured Query Language) is the language which most databases use. This kind of database stores data in structured tables and noting can be added to them if the type of data is incorrect. SQL also support relations between tables. MySQL is a very popular relational database management system (RDBMS) which for example websites frequently makes use of. NoSQL is a new type of databases where the data is stored in collections without any kind of structure, unlike the well known SQL databases where the data is stored in structured tables. Because of the non-structure, these types of databases are designed to be fast and scalable over multiple machines. Mongodb is a such kind of NoSql-database. Tests has been done both on inserting and processing when handling up to 4 millions entities, MongoDB performs better in almost every test. Results shows that the processing time is shorter using MongoDb in the cases that this thesis is covering, and that it’s possible to implement a much fast application when using MongoDb instead of Mysql as database.

Data storage is essential in many Internet services today. As the amountof generated data increases every day a way to store is needed. Relationaldatabases do not handle continuous growing data well. An option to it is touse NoSQL. XDIN Link¨ping is interested in developing an Internet serviceowhich uses non-relational type of data storage to store structured data. Thedata should be accessible to members of the service. The data storage doesnot make any assumption on what type of data is stored. Instead tags thatare attached to each entity are used to verify what type of data it is stored.This thesis provides a description of what NoSQL is and along with it theproposed database designs. Further it aims to investigate if it is reasonableto create a web service which uses NoSQL as the backend storage.

This thesis deals with the complex event processing problem. In theoretical part you can find explanation of basic terms and description of used technologies. Reader also becomes fammiliar with basics of work with esper. Practical part is about building administrative interface, which after connecting to server part of application enables user to use basic functionality of esper engine without previous programming knowledge. Part of this chapter is about system set-up, installation and launching the application as it is not considered to be a trivial task.

With the rapid growth of crime data, overwhelming amounts of electronic evidence need to be stored and shared with the relevant agencies. Without addressing this challenge, the sharing of crime data and electronic evidence will be highly inefficient, and the resource requirements for this task will continue to increase. Relational database solutions face size limitations in storing larger amounts of crime data where each instance has unique attributes with unstructured nature. In this thesis, the Electronic Evidence Locker (EEL) was proposed and developed to address such problems. The EEL was built using a NoSQL database and a C# website for querying stored data. Baseline results were collected to measure the growth of required machine resources (in memory and time) using various test cases and larger datasets. The results showed that search time is more impacted by the search direction in the data than the addition of the query search conditions.

In this diploma thesis an analysis is carried out and on the basis of it a design of a suitable data repository for the SMART faculty project is made. For the storage acces a REST interface is implemented, which is being tested at the last stage of the work.

This thesis deals with methods and technologies for storing and processing big data. Thesis contains design of tools for data storing and creation of system for processing and visualization of big data recorded from airplane data bus.

More than 800 Zettabytes of data is predicted to be generated per year by the Internet of Things by 2021. Storing this data necessitates highly scalable databases. Many different data storage solutions exist that specialize in specific use cases, and designing a system to accept arbitrary sensor data while remaining scalable presents a challenge.The problem was approached through a comparative study of six common databases, inspecting documented features and evaluations, followed by the construction of a prototype system. Elasticsearch was found to be the best suited data storage system for the specific use case presented in this report, and a flexible prototype system was designed. No single database was determined to be best suited for sensor data in general, but with more specific requirements and knowledge of future use, a decision could be made. / Över 800 Zettabytes av data är förutspått att genereras av Sakernas Internet vid år 2021. Lagring av denna data gör det nödvändigt med synnerligen skalbara databaser. Det finns många olika datalagringslösningar som specialiserar sig på specifika användningsområden, och att designa ett system som ska kunna ta emot godtycklig sensordata och samtidigt vara skalbar är en utmaning. Problemet angreps genom en jämförande studie av sex populära databaser som jämfördes utifrån dokumenterad funktionalitet och fristående utvärderingar. Detta följdes av utvecklingen ut av ett prototypsystem. Elasticsearch bedömdes vara bäst lämpad för det specifika användningsområde som presenteras i denna rapport, och ett flexibelt prototypsystem utvecklades. Inte en enda databas bedömdes vara bäst lämpad för att hantera sensordata i allmänhet, men med mer specifika krav och vetskap om framtida användning kan en databas väljas ut.