Envirosuite: An Environmentally-Immersive Programming Framework for Wireless Sensor Networks

Networked, embedded sensors allow for an instrumentation of the physical world at unprecedented granularities and from unimagined perspectives. The advent of a ubiquitous sensing era is evident. Yet, sensor network techniques are still far from entering mainstream adoption due to multiple unresolved research challenges, especially due to the high development cost of sensor network applications. Therefore, in this dissertation, we propose to design, implement, and evaluate an environmentally-immersive programming framework, called EnviroSuite, to reduce sensor network software development cost. The goal of our research is to create reusable sensor network development support for the community and reduce the adoption barriers for a broader category of users, ultimately leading to a transition of sensor networks from a research concept to a general-purpose technology available for use for a wide variety of research, government, industry, and everyday purposes. Current sensor network programming practice remains very cumbersome and inefficient for several reasons. First, most existing programming abstractions for sensor networks are either too low-level (thus too tedious and error-prone) or too high-level (unable to support the diversity of sensor network applications). Second, there is no clear separation between application-level programming and system-level programming. A significant concern is the lack of a general middleware library to isolate application developers from low-level details. Finally, testing sensor network systems is particularly challenging. Sensor systems interact heavily with a (non-repeatable) physical environment, making lab experiments not representative and on-site experiments very costly. This dissertation is targeted for a comprehensive solution that addresses all the above-mentioned problems. The EnviroSuite framework consists of (i) a new programming paradigm that exports environment-based abstractions, (ii) critical middleware services that support the abstractions and separate application programmers from tedious, low-level details, and (iii) testing tools geared for in-situ experimenting, debugging, and troubleshooting. First, we introduce a new programming paradigm, called environmentally-immersive programming (EIP), to capture the common characteristics of sensor network applications, the rich, distributed interactions with the physical environment. EIP refers to an object-based programming model in which individual objects represent physical elements in the external environment. It allows the programmer to think directly in terms of physical objects or events of interest. We provide language primitives for programmers to easily implement their environmental tracking and monitoring applications in EIP. A preprocessor translates such EIP code transparently into a library of support middleware services, central to which are object management algorithms, responsible for maintaining a unique mapping between physical and logical objects. The major outcome of sensor networks is observations of the instrumented environment, in other words, sensory data. Implementing an application mainly involves encoding how to generate, store, and collect such data. EIP object abstractions provide simple means for programmers to define how observations of the environment should be made via distributed coordination among multiple nodes, thus simplifying data generation. Yet, the next steps, namely, data storage and collection, remain complicated and fastidious. To isolate programmers from such concerns, we also include in the support library a set of data management services, comprising both network protocols and storage systems to allow data to be collected either in real-time or in a delay-tolerant manner. The final phase in sensor network software development life-cycle is testing, typically performed in-field, where the effects of environmental realities can be studied. However, physical events from the dynamic environment are normally asynchronous and non-repeatable. This lack of repeatability makes the last phase particularly difficult and costly. Hence, it is essential to have the capability to capture and replay sensing events, providing a basis not only for software testing, but also for realistic protocol comparison and parameter tuning. To achieve that, EnviroSuite also provides testing and debugging facilities that enable controllable and repeatable in-field experiments. Finally, to demonstrate the benefits of our framework, we build multiple representative applications upon EnviroSuite, drawn from both tracking systems such as military surveillance, and monitoring systems such as environmental acoustic monitoring. We install these applications into off-the-shelf hardware platforms and physically deploy the hardware into realistic environments. Empirical results collected from such deployments demonstrate the efficacy of EnviroSuite

EnviroSuite: An Environmentally-Immersive Programming Framework for Wireless Sensor Networks

130 p.Thesis (Ph.D.)--University of Illinois at Urbana-Champaign, 2007.To demonstrate the benefits of our framework, we build multiple representative applications upon EnviroSuite, drawn from both tracking systems such as military surveillance, and monitoring systems such as environmental acoustic monitoring. We install these applications into off-the-shelf hardware platforms and physically deploy the hardware into realistic environments. Empirical results collected from such deployments demonstrate the efficacy of EnviroSuite.U of I OnlyRestricted to the U of I community idenfinitely during batch ingest of legacy ETD

Envirostore: A cooperative storage system for disconnected operation in sensor networks

Abstract — This paper presents a new cooperative storage system for sensor networks geared for disconnected operation (where sensor nodes do not have a connected path to a basestation). The goal of the system is to maximize its data storage capacity by appropriately distributing storage utilization and opportunistically offloading data to external devices when possible. The system is motivated by the observation that a larg

Growth in syphilis-exposed and -unexposed uninfected children from birth to 18 months of age in China: a longitudinal study.

Early infant growth and development has attracted worldwide attention. Although numerous studies have demonstrated that maternal syphilis increases the risk of adverse pregnancy outcomes and congenital syphilis, the subsequent growth pattern and morbidity of syphilis-exposed uninfected infants are less understood. We conducted a longitudinal study to compare the growth pattern and disease distribution of syphilis-exposed and syphilis-unexposed uninfected children, and World Health Organization (WHO) reference standards from birth to 18 months of age. We obtained data from a prospective cohort study in three representative regions of Zhejiang Province in China. A total of 333 syphilis-uninfected children born to women with syphilis were recruited at birth and matched with 333 syphilis-uninfected children born to women without syphilis during pregnancy. Children were followed-up by medical staff every 3 months until 18 months of age. The mixed-effects model was used to compare changes in growth patterns and influencing factors between the two groups. Mean weight, length, and head circumference of children, as well as disease prevalence, were similar between the groups. Multilevel analysis indicated that, after controlling confounders, growth velocities were comparable in both weight and length measures from birth to 18 months old between the two groups; however, low birth weight had a negative impact on weight gain in both groups. There was no significant negative association between syphilis exposure and early growth and health in children, under 18 months in a setting with universal coverage of therapeutic interventions for maternal syphilis. These findings may contribute to improving prevention efforts for mother-to-child transmission of syphilis, such as early screening for syphilis in pregnant women, universal coverage of treatment, and interventions for exposed children. Children with low birth weight should be given priority as this is a risk factor for weight gain

EnviroSuite: An Environmentally Immersive Programming Framework for Sensor Networks

Sensor networks open a new frontier for embedded distributed computing. Paradigms for sensor network programming in the large have been identified as a significant challenge towards developing large-scale applications. Classical programming languages are too low-level. This paper presents the design, implementation, and evaluation of EnviroSuite, a programming framework that introduces a new paradigm, called environmentally immersive programming, to abstract distributed interactions with the environment. Environmentally immersive programming refers to an object-based programming model in which individual objects represent physical elements in the external environment. It allows the programmer to think directly in terms of environmental abstractions. EnviroSuite provides language primitives for environmentally immersive programming that map transparently into a support library of distributed algorithms for tracking and environmental monitoring. We show how nesC code of realistic applications is significantly simplified using EnviroSuite, and demonstrate the resulting system performance on Mica2 and XSM platforms