The Design and Use of a Smartphone Data Collection Tool and Accompanying Configuration Language

Understanding human behaviour is key to understanding the spread of epidemics, habit dispersion, and the efficacy of health interventions. Investigation into the patterns of and drivers for human behaviour has often been facilitated by paper tools such as surveys, journals, and diaries. These tools have drawbacks in that they can be forgotten, go unfilled, and depend on often unreliable human memories. Researcher-driven data collection mechanisms, such as interviews and direct observation, alleviate some of these problems while introducing others, such as bias and observer effects. In response to this, technological means such as special-purpose data collection hardware, wireless sensor networks, and apps for smart devices have been built to collect behavioural data. These technologies further reduce the problems experienced by more traditional behavioural research tools, but often experience problems of reliability, generality, extensibility, and ease of configuration. This document details the construction of a smartphone-based app designed to collect data on human behaviour such that the difficulties of traditional tools are alleviated while still addressing the problems faced by modern supplemental technology. I describe the app's main data collection engine and its construction, architecture, reliability, generality, and extensibility, as well as the programming language developed to configure it and its feature set. To demonstrate the utility of the tool and its configuration language, I describe how they have been used to collect data in the field. Specifically, eleven case studies are presented in which the tool's architecture, flexibility, generality, extensibility, modularity, and ease of configuration have been exploited to facilitate a variety of behavioural monitoring endeavours. I further explain how the engine performs data collection, the major abstractions it employs, how its design and the development techniques used ensure ongoing reliability, and how the engine and its configuration language could be extended in the future to facilitate a greater range of experiments that require behavioural data to be collected. Finally, features and modules of the engine's encompassing system, iEpi, are presented that have not otherwise been documented to give the reader an understanding of where the work fits into the larger data collection and processing endeavour that spawned it

Developing IoT applications in the Fog:a distributed dataflow approach

In this paper we examine the development of IoT applications from the perspective of the Fog Computing paradigm, where computing infrastructure at the network edge in devices and gateways is leverage for efficiency and timeliness. Due to the intrinsic nature of the IoT: heterogeneous devices/resources, a tightly coupled perception-action cycle and widely distributed devices and processing, application development in the Fog can be challenging. To address these challenges, we propose a Distributed Dataflow (DDF) programming model for the IoT that utilises computing infrastructures across the Fog and the Cloud. We evaluate our proposal by implementing a DDF framework based on Node-RED (Distributed Node-RED or D-NR), a visual programming tool that uses a flow-based model for building IoT applications. Via demonstrations, we show that our approach eases the development process and can be used to build a variety of IoT applications that work efficiently in the Fog

Conception et implémentation de systèmes résilients par une approche à composants

L'évolution des systèmes pendant leur vie opérationnelle est incontournable. Les systèmes sûrs de fonctionnement doivent évoluer pour s'adapter à des changements comme la confrontation à de nouveaux types de fautes ou la perte de ressources. L'ajout de cette dimension évolutive à la fiabilité conduit à la notion de résilience informatique. Parmi les différents aspects de la résilience, nous nous concentrons sur l'adaptativité. La sûreté de fonctionnement informatique est basée sur plusieurs moyens, dont la tolérance aux fautes à l'exécution, où l'on attache des mécanismes spécifiques (Fault Tolerance Mechanisms, FTMs) à l'application. A ce titre, l'adaptation des FTMs à l'exécution s'avère un défi pour développer des systèmes résilients. Dans la plupart des travaux de recherche existants, l'adaptation des FTMs à l'exécution est réalisée de manière préprogrammée ou se limite à faire varier quelques paramètres. Tous les FTMs envisageables doivent être connus dès le design du système et déployés et attachés à l'application dès le début. Pourtant, les changements ont des origines variées et, donc, vouloir équiper un système pour le pire scénario est impossible. Selon les observations pendant la vie opérationnelle, de nouveaux FTMs peuvent être développés hors-ligne, mais intégrés pendant l'exécution. On dénote cette capacité comme adaptation agile, par opposition à l'adaptation préprogrammée. Dans cette thèse, nous présentons une approche pour développer des systèmes sûrs de fonctionnement flexibles dont les FTMs peuvent s'adapter à l'exécution de manière agile par des modifications à grain fin pour minimiser l'impact sur l'architecture initiale. D'abord, nous proposons une classification d'un ensemble de FTMs existants basée sur des critères comme le modèle de faute, les caractéristiques de l'application et les ressources nécessaires. Ensuite, nous analysons ces FTMs et extrayons un schéma d'exécution générique identifiant leurs parties communes et leurs points de variabilité. Après, nous démontrons les bénéfices apportés par les outils et les concepts issus du domaine du génie logiciel, comme les intergiciels réflexifs à base de composants, pour développer une librairie de FTMs adaptatifs à grain fin. Nous évaluons l'agilité de l'approche et illustrons son utilité à travers deux exemples d'intégration : premièrement, dans un processus de développement dirigé par le design pour les systèmes ubiquitaires et, deuxièmement, dans un environnement pour le développement d'applications pour des réseaux de capteurs. ABSTRACT : Evolution during service life is mandatory, particularly for long-lived systems. Dependable systems, which continuously deliver trustworthy services, must evolve to accommodate changes e.g., new fault tolerance requirements or variations in available resources. The addition of this evolutionary dimension to dependability leads to the notion of resilient computing. Among the various aspects of resilience, we focus on adaptivity. Dependability relies on fault tolerant computing at runtime, applications being augmented with fault tolerance mechanisms (FTMs). As such, on-line adaptation of FTMs is a key challenge towards resilience. In related work, on-line adaption of FTMs is most often performed in a preprogrammed manner or consists in tuning some parameters. Besides, FTMs are replaced monolithically. All the envisaged FTMs must be known at design time and deployed from the beginning. However, dynamics occurs along multiple dimensions and developing a system for the worst-case scenario is impossible. According to runtime observations, new FTMs can be developed off-line but integrated on-line. We denote this ability as agile adaption, as opposed to the preprogrammed one. In this thesis, we present an approach for developing flexible fault-tolerant systems in which FTMs can be adapted at runtime in an agile manner through fine-grained modifications for minimizing impact on the initial architecture. We first propose a classification of a set of existing FTMs based on criteria such as fault model, application characteristics and necessary resources. Next, we analyze these FTMs and extract a generic execution scheme which pinpoints the common parts and the variable features between them. Then, we demonstrate the use of state-of-the-art tools and concepts from the field of software engineering, such as component-based software engineering and reflective component-based middleware, for developing a library of fine-grained adaptive FTMs. We evaluate the agility of the approach and illustrate its usability throughout two examples of integration of the library: first, in a design-driven development process for applications in pervasive computing and, second, in a toolkit for developing applications for WSNs

Language design for distributed stream processing

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2009.This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.Includes bibliographical references (p. 149-152).Applications that combine live data streams with embedded, parallel, and distributed processing are becoming more commonplace. WaveScript is a domain-specific language that brings high-level, type-safe, garbage-collected programming to these domains. This is made possible by three primary implementation techniques, each of which leverages characteristics of the streaming domain. First, WaveScript employs an evaluation strategy that uses a combination of interpretation and reification to partially evaluate programs into stream dataflow graphs. Second, we use profile-driven compilation to enable many optimizations that are normally only available in the synchronous (rather than asynchronous) dataflow domain. Finally, an empirical, profile-driven approach also allows us to compute practical partitions of dataflow graphs, spreading them across embedded nodes and more powerful servers. We have used our language to build and deploy applications, including a sensor-network for the acoustic localization of wild animals such as the Yellow-Bellied marmot. We evaluate WaveScript's performance on this application, showing that it yields good performance on both embedded and desktop-class machines. Our language allowed us to implement the application rapidly, while outperforming a previous C implementation by over 35%, using fewer than half the lines of code. We evaluate the contribution of our optimizations to this success. We also evaluate WaveScript's ability to extract parallelism from this and other applications.by Ryan Rhodes Newton.Ph.D

Efficient Passive Clustering and Gateways selection MANETs

Passive clustering does not employ control packets to collect topological information in ad hoc networks. In our proposal, we avoid making frequent changes in cluster architecture due to repeated election and re-election of cluster heads and gateways. Our primary objective has been to make Passive Clustering more practical by employing optimal number of gateways and reduce the number of rebroadcast packets

Abstract Macroprogramming Heterogeneous Sensor Networks Using COSMOS

In this paper, we present COSMOS, a novel architecture for macroprogramming heterogeneous sensor network systems. Macroprogramming entails aggregate system behavior specification, as opposed to device-specific applications that indirectly express distributed behavior through explicit messaging between nodes. COS-MOS is comprised of a macroprogramming language, mPL, and an operating system, mOS. mPL macroprograms specify distributed system behavior using statically verifiable compositions of reusable user-provided, or system supported functional components. mOS provides component management and a lean execution environment for mPL in heterogeneous resource-constrained sensor networks. COSMOS facilitates composition of complex real-world applications that are robust, scalable and adaptive in dynamic datadriven sensor network environments. The mOS architecture allows runtime application instantiation, with over-the-air reprogramming of the network. An important and novel aspect of COSMOS is the ability to easily extend its component basis library to add rich macroprogramming abstractions to mPL, tailored to domain and resource constraints, without modifications to the OS. A fully functional version of COSMOS is currently in use at the Bowen Labs for Structural Engineering, at Purdue University, for highfidelity structural dynamics measurements. We present comprehensive experimental evaluation using macro- and micro- benchmarks to demonstrate performance characteristics of COSMOS. 1