Autonomic care platform for optimizing query performance

Background: As the amount of information in electronic health care systems increases, data operations get more complicated and time-consuming. Intensive Care platforms require a timely processing of data retrievals to guarantee the continuous display of recent data of patients. Physicians and nurses rely on this data for their decision making. Manual optimization of query executions has become difficult to handle due to the increased amount of queries across multiple sources. Hence, a more automated management is necessary to increase the performance of database queries. The autonomic computing paradigm promises an approach in which the system adapts itself and acts as self-managing entity, thereby limiting human interventions and taking actions. Despite the usage of autonomic control loops in network and software systems, this approach has not been applied so far for health information systems. Methods: We extend the COSARA architecture, an infection surveillance and antibiotic management service platform for the Intensive Care Unit (ICU), with self-managed components to increase the performance of data retrievals. We used real-life ICU COSARA queries to analyse slow performance and measure the impact of optimizations. Each day more than 2 million COSARA queries are executed. Three control loops, which monitor the executions and take action, have been proposed: reactive, deliberative and reflective control loops. We focus on improvements of the execution time of microbiology queries directly related to the visual displays of patients' data on the bedside screens. Results: The results show that autonomic control loops are beneficial for the optimizations in the data executions in the ICU. The application of reactive control loop results in a reduction of 8.61% of the average execution time of microbiology results. The combined application of the reactive and deliberative control loop results in an average query time reduction of 10.92% and the combination of reactive, deliberative and reflective control loops provides a reduction of 13.04%. Conclusions: We found that by controlled reduction of queries' executions the performance for the end-user can be improved. The implementation of autonomic control loops in an existing health platform, COSARA, has a positive effect on the timely data visualization for the physician and nurse

Towards Real-time Wireless Sensor Networks

Wireless sensor networks are poised to change the way computer systems interact with the physical world. We plan on entrusting sensor systems to collect medical data from patients, monitor the safety of our infrastructure, and control manufacturing processes in our factories. To date, the focus of the sensor network community has been on developing best-effort services. This approach is insufficient for many applications since it does not enable developers to determine if a system\u27s requirements in terms of communication latency, bandwidth utilization, reliability, or energy consumption are met. The focus of this thesis is to develop real-time network support for such critical applications. The first part of the thesis focuses on developing a power management solution for the radio subsystem which addresses both the problem of idle-listening and power control. In contrast to traditional power management solutions which focus solely on reducing energy consumption, the distinguishing feature of our approach is that it achieves both energy efficiency and real-time communication. A solution to the idle-listening problem is proposed in Energy Efficient Sleep Scheduling based on Application Semantics: ESSAT). The novelty of ESSAT lies in that it takes advantage of the common features of data collection applications to determine when to turn on and off a node\u27s radio without affecting real-time performance. A solution to the power control problem is proposed in Real-time Power Aware-Routing: RPAR). RPAR tunes the transmission power for each packet based on its deadline such that energy is saved without missing packet deadlines. The main theoretical contribution of this thesis is the development of novel transmission scheduling techniques optimized for data collection applications. This work bridges the gap between wireless sensor networks and real-time scheduling theory, which have traditionally been applied to processor scheduling. The proposed approach has significant advantages over existing design methodologies:: 1) it provides predictable performance allowing for the performance of a system to be estimated upon its deployment,: 2) it is possible to detect and handle overload conditions through simple rate control mechanisms, and: 3) it easily accommodates workload changes. I developed this framework under a realistic interference model by coordinating the activities at the MAC, link, and routing layers. The last component of this thesis focuses on the development of a real-time patient monitoring system for general hospital units. The system is designed to facilitate the detection of clinical deterioration, which is a key factor in saving lives and reducing healthcare costs. Since patients in general hospital wards are often ambulatory, a key challenge is to achieve high reliability even in the presence of mobility. To support patient mobility, I developed the Dynamic Relay Association Protocol -- a simple and effective mechanism for dynamically discovering the right relays for forwarding patient data -- and a Radio Mapping Tool -- a practical tool for ensuring network coverage in 802.15.4 networks. We show that it is feasible to use low-power and low-cost wireless sensor networks for clinical monitoring through an in-depth clinical study. The study was performed in a step-down cardiac care unit at Barnes-Jewish Hospital. This is the first long-term study of such a patient monitoring system

Pervasive Data Access in Wireless and Mobile Computing Environments

The rapid advance of wireless and portable computing technology has brought a lot of research interests and momentum to the area of mobile computing. One of the research focus is on pervasive data access. with wireless connections, users can access information at any place at any time. However, various constraints such as limited client capability, limited bandwidth, weak connectivity, and client mobility impose many challenging technical issues. In the past years, tremendous research efforts have been put forth to address the issues related to pervasive data access. A number of interesting research results were reported in the literature. This survey paper reviews important works in two important dimensions of pervasive data access: data broadcast and client caching. In addition, data access techniques aiming at various application requirements (such as time, location, semantics and reliability) are covered

Dynamic Routing Framework for Wireless Sensor Networks

Numerous routing protocols have been proposed for wireless sensor networks. Each such protocol carries with it a set of assumptions about the trafï¬c type that it caters to, and hence has limited interoperability. Also, most protocols are validated over workloads which only form a fraction of an actual deployment’s requirement. Most real world and commercial deployments, however, would generate multiple trafï¬c types simultaneously throughout the lifetime of the network. For example, most deployments would want all of the following to happen concurrently from the network: periodic reliable sense and disseminate, real time streams, patched updates, network reprogramming, query-response dialogs, mission critical alerts and so on. Naturally, no one routing protocol can completely cater to all of a deployments requirements. This chapter presents a routing framework that captures the communication intent of an application by using just three bits. The traditional routing layer is replaced with a collection of routing components that can cater to various communication patterns. The framework dynamically switches routing component for every packet in question. Data structure requirements of component protocols are regularized, and core protocol features are distilled to build a highly composable collection of routing modules. This creates a framework for developing, testing, integrating, and validating protocols that are highly portable from one deployment to another. Communication patterns can be easily described to lower layer protocols using this framework. One such real world application scenario is also investigated: that of predictive maintenance (PdM). The requirements of a large scale PdM are used to generate a fairly complete and realistic trafï¬c workload to drive an evaluation of such a framework

Efficient Power Management based on Application Timing Semantics for Wireless Sensor Networks

This paper proposes Efficient Sleep Scheduling based on Application Timing (ESSAT), a novel power manage-ment scheme that aggressively exploits the timing seman-tics of wireless sensor network applications. We present three ESSAT protocols each of which integrates (1) a light-weight traffic shaper that actively shapes the workload inside the network to achieve predictable timing proper-ties over multiple hops, and (2) a local scheduling algorithm that wakes up nodes just-in-time based on the tim-ing properties of shaped workloads. Our ESSAT protocols have several distinguishing features. First, they can save significant energy with minimal delay penalties. Second, they do not maintain TDMA schedules or communication backbones; as such, they are highly efficient and suitable for resource constrained sensor platforms. Moreover, the protocols are robust in highly dynamic network environ-ments, i.e., they can handle variable multi-hop communication delays and aggregate workloads involving multiple queries, and can adapt to varying workload and network topologies. Our simulations showed that DTS-SS, an ES-SAT protocol, achieved an average node duty cycle 38-87% lower than SPAN, and query latencies 36-98% lower than PSM and SYNC

DeMMon Decentralized Management and Monitoring Framework

The centralized model proposed by the Cloud computing paradigm mismatches the decentralized nature of mobile and IoT applications, given the fact that most of the data production and consumption is performed by end-user devices outside of the Data Center (DC). As the number of these devices grows, and given the need to transport data to and from DCs for computation, application providers incur additional infrastructure costs, and end-users incur delays when performing operations. These reasons have led us into a post-cloud era, where a new computing paradigm arose: Edge Computing. Edge Computing takes into account the broad spectrum of devices residing outside of the DC, closer to the clients, as potential targets for computations, potentially reducing infrastructure costs, improving the quality of service (QoS) for end-users and allowing new interaction paradigms between users and applications. Managing and monitoring the execution of these devices raises new challenges previously unaddressed by Cloud computing, given the scale of these systems and the devices’ (potentially) unreliable data connections and heterogenous computational power. The study of the state-of-the-art has revealed that existing resource monitoring and management solutions require manual configuration and have centralized components, which we believe do not scale for larger-scale systems. In this work, we address these limitations by presenting a novel Decentralized Management and Monitoring (“DeMMon”) system, targeted for edge settings. DeMMon provides primitives to ease the development of tools that manage computational resources that support edge-enabled applications, decomposed in components, through decentralized actions, taking advantage of partial knowledge of the system. Our solution was evaluated to amount to its benefits regarding information dissemination and monitoring capabilities across a set of realistic emulated scenarios of up to 750 nodes with variable failure rates. The results show the validity of our approach and that it can outperform state-of-the-art solutions regarding scalability and reliabilityO modelo centralizado de computação utilizado no paradigma da Computação na Nuvem apresenta limitações no contexto de aplicações no domínio da Internet das Coisas e aplicações móveis. Neste tipo de aplicações, os dados são produzidos e consumidos maioritariamente por dispositivos que se encontram na periferia da rede. Desta forma, transportar estes dados de e para os centros de dados impõe uma carga excessiva nas infraestruturas de rede que ligam os dispositivos aos centros de dados, aumentando a latência de respostas e diminuindo a qualidade de serviço para os utilizadores. Para combater estas limitações, surgiu o paradigma da Computação na Periferia, este paradigma propõe a execução de computações, e potencialmente armazenamento de dados, em dispositivos fora dos centros de dados, mais perto dos clientes, reduzindo custos e criando um novo leque de possibilidades para efetuar computações distribuídas mais próximas dos dispositivos que produzem e consomem os dados. Contudo, gerir e supervisionar a execução desses dispositivos levanta obstáculos não equacionados pela Computação na Nuvem, como a escala destes sistemas, ou a variabilidade na conectividade e na capacidade de computação dos dispositivos que os compõem. O estudo da literatura revela que ferramentas populares para gerir e supervisionar aplicações e dispositivos possuem limitações para a sua escalabilidade, como por exemplo, pontos de falha centralizados, ou requerem a configuração manual de cada dispositivo. Nesta dissertação, propõem-se uma nova solução de monitorização e disseminação de informação descentralizada. Esta solução oferece operações que permitem recolher informação sobre o estado do sistema, de modo a ser utilizada por soluções (também descentralizadas) que gerem aplicações especializadas para executar na periferia da rede. A nossa solução foi avaliada em redes emuladas de várias dimensões com um máximo de 750 nós, no contexto de disseminação e de monitorização de informação. Os nossos resultados mostram que o nosso sistema consegue ser mais robusto ao mesmo tempo que é mais escalável quando comparado com o estado da arte

Strengths and Weaknesses of Prominent Data Dissemination Techniques in Wireless Sensor Networks

Data dissemination is the most significant task in a Wireless Sensor Network (WSN). From the bootstrapping stage to the full functioning stage, a WSN must disseminate data in various patterns like from the sink to node, from node to sink, from node to node, or the like. This is what a WSN is deployed for. Hence, this issue comes with various data routing models and often there are different types of network settings that influence the way of data collection and/or distribution. Considering the importance of this issue, in this paper, we present a survey on various prominent data dissemination techniques in such network. Our classification of the existing works is based on two main parameters: the number of sink (single or multiple) and the nature of its movement (static or mobile). Under these categories, we have analyzed various previous works for their relative strengths and weaknesses. A comparison is also made based on the operational methods of various data dissemination schemes

Educational affairs plan: A five-year strategy

A five-year plan is presented to guide the use of NASA resources in administering a focused and consistent set of aeronautics and space science education programs. Major initiatives outlined in this plan fall into two categories: programmatic priorities and institutional priorities. Programmatic priorities for this plan include elementary education, teacher education, underrepresented minority participation, educational technology and the Aerospace Education Services Project (AESP). Institutional priorities highlighted in this plan include university programs, educational publications and their distribution, educational partnerships with public and private organizations, educational research and evaluation, and activities of the educational affairs administration. The plan's aim is to directly and indirectly help to ensure an adequate pool of talented scientists, engineers and technical personnel to keep NASA at the forefront of advancements for the 21st century