Mobile Data Management

The management of data in the mobile computing environment offers new challenging problems. Existing software needs to be upgraded to accommodate this environment. To do so, the critical parameters need to be understood and defined. We have surveyed some problems and existing solution

Data management in cloud environments: NoSQL and NewSQL data stores

: Advances in Web technology and the proliferation of mobile devices and sensors connected to the Internet have resulted in immense processing and storage requirements. Cloud computing has emerged as a paradigm that promises to meet these requirements. This work focuses on the storage aspect of cloud computing, specifically on data management in cloud environments. Traditional relational databases were designed in a different hardware and software era and are facing challenges in meeting the performance and scale requirements of Big Data. NoSQL and NewSQL data stores present themselves as alternatives that can handle huge volume of data. Because of the large number and diversity of existing NoSQL and NewSQL solutions, it is difficult to comprehend the domain and even more challenging to choose an appropriate solution for a specific task. Therefore, this paper reviews NoSQL and NewSQL solutions with the objective of: (1) providing a perspective in the field, (2) providing guidance to practitioners and researchers to choose the appropriate data store, and (3) identifying challenges and opportunities in the field. Specifically, the most prominent solutions are compared focusing on data models, querying, scaling, and security related capabilities. Features driving the ability to scale read requests and write requests, or scaling data storage are investigated, in particular partitioning, replication, consistency, and concurrency control. Furthermore, use cases and scenarios in which NoSQL and NewSQL data stores have been used are discussed and the suitability of various solutions for different sets of applications is examined. Consequently, this study has identified challenges in the field, including the immense diversity and inconsistency of terminologies, limited documentation, sparse comparison and benchmarking criteria, and nonexistence of standardized query languages

Mobile web resource tracking during a disaster or crisis situation

This paper proposes a prototype solution for a mobile web resource tracking system using mobile devices during an emergency situation. The system provides real time data to a decision maker so that he/she can effectively and efficiently monitor resources and assess the situation accordingly. Mobile devices (i.e., smart phones) support the ease of use for any location and at anytime. The Internet technology is selected to enable multiple or cross platform technology solutions for different mobile devices. Resources in the scope of this project are human resources (e.g., a doctor, a police officer) and a chemical list in a room. With the use of a GPS-enabled device or a wireless-enabled device, the system is used to provide the current location of the human resources. Transferring data between system databases and mobile devices is one of the important areas to address in this project. Since location data of a user is sensitive data, data should be protected via an encrypted protected network. In addition, because of the urgency of any crisis situation, it is critical that data from the system be able to be retrieved in a reasonable time frame. The investigation includes the exploration of database and data transfer solutions to meet the data availability during emergency conditions on mobile devices. This document includes a description of the system design, a review of current technologies, proposed methodology, and the implementation. Review of the literature section provides background information on current available technologies that were studied (section 3). Four identified factors are suggested in the system design – usability, security, availability, and performance. The discussion of which technology is selected for each feature can be found in the implementation section 4. Proposed future research areas can be found in the conclusion section and recommendations for future work section