'NoSQL' and electronic patient record systems: opportunities and challenges

(c) 2014 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works.Research into electronic health record systems can be traced back over four decades however the penetration of records which incorporate more than simply basic information into healthcare organizations is relatively limited. There is a great (and largely unsatisfied) demand for effective health record systems, such systems are very difficult to build with data generally stored in highly distributed states in a diverse range of formats as unstructured data with access and updating achieved over online systems. Internet application design must reflect three trends in the computing landscape: (1) growing numbers of users applications must support (along with growing user performance expectations), (2) growth in the volume and range and diversity in the data that developers accommodate, and (3) and the rise of Cloud Computing (which relies on a distributed three-tier Internet architecture). The traditional approach to data storage has generally employed Relational Database Systems however to address the evolving paradigm interest has been shown in alternative database systems including 'NoSQL' technologies which are gaining traction in Internet based enterprise systems. This paper considers the requirements of distributed health record systems in online applications and database systems. The analysis supports the conclusion that 'NoSQL' database systems provide a potentially useful approach to the implementation of HR systems in online applications.Peer ReviewedPostprint (author's final draft

Harmony: Towards automated self-adaptive consistency in cloud storage

In just a few years cloud computing has become a very popular paradigm and a business success story, with storage being one of the key features. To achieve high data availability, cloud storage services rely on replication. In this context, one major challenge is data consistency. In contrast to traditional approaches that are mostly based on strong consistency, many cloud storage services opt for weaker consistency models in order to achieve better availability and performance. This comes at the cost of a high probability of stale data being read, as the replicas involved in the reads may not always have the most recent write. In this paper, we propose a novel approach, named Harmony, which adaptively tunes the consistency level at run-time according to the application requirements. The key idea behind Harmony is an intelligent estimation model of stale reads, allowing to elastically scale up or down the number of replicas involved in read operations to maintain a low (possibly zero) tolerable fraction of stale reads. As a result, Harmony can meet the desired consistency of the applications while achieving good performance. We have implemented Harmony and performed extensive evaluations with the Cassandra cloud storage on Grid?5000 testbed and on Amazon EC2. The results show that Harmony can achieve good performance without exceeding the tolerated number of stale reads. For instance, in contrast to the static eventual consistency used in Cassandra, Harmony reduces the stale data being read by almost 80% while adding only minimal latency. Meanwhile, it improves the throughput of the system by 45% while maintaining the desired consistency requirements of the applications when compared to the strong consistency model in Cassandra

Real time analytics for characterizing the computer user's state

In the last years, the amount of devices that can be connected to a network grew significantly allowing to, among other tasks, collect data about the environment or the people in it in a non-intrusive way. This generated nowadays well-known topics such as Big Data or the Internet of Things. This also opened the door to the development of novel and interesting applications. In this paper we propose a distributed system for acquiring data about the users of technological devices in a non-intrusive way. We describe how this data can be collected and transformed to produce meaningful interaction features, that reveal the state of the individuals. We analyse the requirements of such a system, namely in terms of storage and speed, and describe three prototypes currently being used in three different domains of application.- This work has been supported by COMPETE: POCI-01-0145-FEDER-007043 and FCT - Fundacao para a Ciencia e Tecnologia within the Project Scope: UID/CEC/00319/2013.info:eu-repo/semantics/publishedVersio