A File System Abstraction for Sense and Respond Systems

The heterogeneity and resource constraints of sense-and-respond systems pose significant challenges to system and application development. In this paper, we present a flexible, intuitive file system abstraction for organizing and managing sense-and-respond systems based on the Plan 9 design principles. A key feature of this abstraction is the ability to support multiple views of the system via filesystem namespaces. Constructed logical views present an application-specific representation of the network, thus enabling high-level programming of the network. Concurrently, structural views of the network enable resource-efficient planning and execution of tasks. We present and motivate the design using several examples, outline research challenges and our research plan to address them, and describe the current state of implementation.Comment: 6 pages, 3 figures Workshop on End-to-End, Sense-and-Respond Systems, Applications, and Services In conjunction with MobiSys '0

Dynamic Reconfiguration for Software and Hardware Heterogeneous Real-time WSN

International audienceWireless Sensor Network (WSN) technology has imposed itself in civilian and industrial applications as a promising technology for wireless monitoring due to its wireless connectivity, removing many hardware constraints. Initially used in low frequency sampling applications, the increasing performances of electronic circuits has driven WSNs to integrate more powerful computation units, paving the way for a new generation of applications based on distributed computation. These new applications (process control, active control, visual surveillance, multimedia streaming) involving medium to heavy computation present real-time requirements at node level where reactivity becomes a primary concern as well as at the network level where latency must be bounded. In this paper, we present the implementation of a high-level language MinTax coupled with an in-situ compilation solution for real time Operating Systems enabling energy-aware dynamic reconfiguration while supporting hardware heterogeneity in Wireless Sensor Networks

Remote Control and Monitoring of Smart Home Facilities via Smartphone with Wi-Fly

Due to the widespread ownership of smartphone devices, the application of mobile technologies to enhance the monitoring and control of smart home facilities has attracted much academic attention. This study indicates that tools already in the possession of the end user can be a significant part of the specific context-aware system in the smart home. The behaviour of the system in the context of existing systems will reflect the intention of the client. This model system offers a diverse architectural concept for Wireless Sensor Actuator Mobile Computing in a Smart Home (WiSAMCinSH) and consists of sensors and actuators in various communication channels, with different capacities, paradigms, costs and degree of communication reliability. This paper focuses on the utilization of end users’ smartphone applications to control home devices, and to enable monitoring of the context-aware environment in the smart home to fulfil the needs of the ageing population. It investigates the application of an iPhone to supervise smart home monitoring and control electrical devices, and through this approach, after initial setup of the mobile application, a user can control devices in the smart home from different locations and over various distances

Efficient and Reliable Task Scheduling, Network Reprogramming, and Data Storage for Wireless Sensor Networks

Wireless sensor networks (WSNs) typically consist of a large number of resource-constrained nodes. The limited computational resources afforded by these nodes present unique development challenges. In this dissertation, we consider three such challenges. The first challenge focuses on minimizing energy usage in WSNs through intelligent duty cycling. Limited energy resources dictate the design of many embedded applications, causing such systems to be composed of small, modular tasks, scheduled periodically. In this model, each embedded device wakes, executes a task-set, and returns to sleep. These systems spend most of their time in a state of deep sleep to minimize power consumption. We refer to these systems as almost-always-sleeping (AAS) systems. We describe a series of task schedulers for AAS systems designed to maximize sleep time. We consider four scheduler designs, model their performance, and present detailed performance analysis results under varying load conditions. The second challenge focuses on a fast and reliable network reprogramming solution for WSNs based on incremental code updates. We first present VSPIN, a framework for developing incremental code update mechanisms to support efficient reprogramming of WSNs. VSPIN provides a modular testing platform on the host system to plug-in and evaluate various incremental code update algorithms. The framework supports Avrdude, among the most popular Linux-based programming tools for AVR microcontrollers. Using VSPIN, we next present an incremental code update strategy to efficiently reprogram wireless sensor nodes. We adapt a linear space and quadratic time algorithm (Hirschberg\u27s Algorithm) for computing maximal common subsequences to build an edit map specifying an edit sequence required to transform the code running in a sensor network to a new code image. We then present a heuristic-based optimization strategy for efficient edit script encoding to reduce the edit map size. Finally, we present experimental results exploring the reduction in data size that it enables. The approach achieves reductions of 99.987% for simple changes, and between 86.95% and 94.58% for more complex changes, compared to full image transmissions - leading to significantly lower energy costs for wireless sensor network reprogramming. The third challenge focuses on enabling fast and reliable data storage in wireless sensor systems. A file storage system that is fast, lightweight, and reliable across device failures is important to safeguard the data that these devices record. A fast and efficient file system enables sensed data to be sampled and stored quickly and batched for later transmission. A reliable file system allows seamless operation without disruptions due to hardware, software, or other unforeseen failures. While flash technology provides persistent storage by itself, it has limitations that prevent it from being used in mission-critical deployment scenarios. Hybrid memory models which utilize newer non-volatile memory technologies, such as ferroelectric RAM (FRAM), can mitigate the physical disadvantages of flash. In this vein, we present the design and implementation of LoggerFS, a fast, lightweight, and reliable file system for wireless sensor networks, which uses a hybrid memory design consisting of RAM, FRAM, and flash. LoggerFS is engineered to provide fast data storage, have a small memory footprint, and provide data reliability across system failures. LoggerFS adapts a log-structured file system approach, augmented with data persistence and reliability guarantees. A caching mechanism allows for flash wear-leveling and fast data buffering. We present a performance evaluation of LoggerFS using a prototypical in-situ sensing platform and demonstrate between 50% and 800% improvements for various workloads using the FRAM write-back cache over the implementation without the cache

A 64mW DNN-based Visual Navigation Engine for Autonomous Nano-Drones

Fully-autonomous miniaturized robots (e.g., drones), with artificial intelligence (AI) based visual navigation capabilities are extremely challenging drivers of Internet-of-Things edge intelligence capabilities. Visual navigation based on AI approaches, such as deep neural networks (DNNs) are becoming pervasive for standard-size drones, but are considered out of reach for nanodrones with size of a few cm${}^\mathrm{2}$. In this work, we present the first (to the best of our knowledge) demonstration of a navigation engine for autonomous nano-drones capable of closed-loop end-to-end DNN-based visual navigation. To achieve this goal we developed a complete methodology for parallel execution of complex DNNs directly on-bard of resource-constrained milliwatt-scale nodes. Our system is based on GAP8, a novel parallel ultra-low-power computing platform, and a 27 g commercial, open-source CrazyFlie 2.0 nano-quadrotor. As part of our general methodology we discuss the software mapping techniques that enable the state-of-the-art deep convolutional neural network presented in [1] to be fully executed on-board within a strict 6 fps real-time constraint with no compromise in terms of flight results, while all processing is done with only 64 mW on average. Our navigation engine is flexible and can be used to span a wide performance range: at its peak performance corner it achieves 18 fps while still consuming on average just 3.5% of the power envelope of the deployed nano-aircraft.Comment: 15 pages, 13 figures, 5 tables, 2 listings, accepted for publication in the IEEE Internet of Things Journal (IEEE IOTJ

Smart system signalization prototype for flow control of people in crosswalks

Mestrado de dupla diplomação com a UTFPR - Universidade Tecnológica Federal do ParanáBad lighting conditions on crosswalks is a common problem on the urban environment. This scenery entail a large number of pedestrians fatalities and it shows a demand for solutions able to ensure their safety using lighting resources. The present work proposes a crosswalk’s crossing process oriented by a system which is compound for a pair of Smart Devices that fit themselves in the Smart City idea. Inside this propose, they are capable to signalize for pedestrians the safe moment to enter on the crosswalk. These devices are a prototype of a system programmed in Python language and based in the Raspberry Pi and LoRa technologies. The work is split, mainly, on the hardware and software components development. In hardware level, it shows a circuit schematic design based on the Raspberry Pi Compute Module operating with the RFM95W LoRa module. In software level, it shows the incremental development of a Embedded System which reads inputs, gives lighting outputs and implements the communication, with encrypted messages, between the devices. Finally, this thesis shows a circuit schematic implementation wiled in KiCAD software and a embedded system focused in ensure well lighting and signalization on crosswalks. To validate the system are made hypothetical tests toward pedestrians behavior to cross the street on crosswalks.As más condições de iluminação em passadeiras são um problema recorrente no ambiente urbano. Esse cenário implica em um grande número de fatalidades e deixa evidente a demanda por uma solução capaz de garantir a segurança do pedestre usando recursos de iluminação. O presente trabalho propõe um processo de travessia em faixas de pedestres orientado por um sistema composto por um par de dipositivos inteligentes que se encaixam na ideia de cidades inteligentes. Dentro dessa proposta, eles são capazes de sinalizar para os pedestres o momento seguro para entrar na passadeira. Esses dispositivos são um protótipo de sistema programado em linguagem Python e baseado nas tecnologias Raspberry Pi e LoRa. O trabalho é dividido, principalmente, no desenvolvimento das componentes de hardware e software. A nível de hardware, ele mostra um projeto esquemático do circuito baseado no Raspberry Pi Compute Module que opera com o módulo LoRa RFM95W. A nível de software, ele mostra o desenvolvimento incremental de um sistema incorporado que lê entradas, fornece saídas de iluminação e implementa a comunicação, com mensagens criptografadas, entre os dispositivos. Finalmente, esta tese mostra a implementação do esquemático de um circuito usando o software KiCAD e um sistema embarcado focado em garantir iluminação e a sinalização nas passadeiras. Para validar o sistema são feitos testes hipotéticos em relação ao comportamento dos pedestres para atravessar a rua em faixas de pedestres

Wireless Sensor Node for Autonomous Monitoring and Alerts in Remote Environments

A method, apparatus, system, and computer program products provides personal alert and tracking capabilities using one or more nodes. Each node includes radio transceiver chips operating at different frequency ranges, a power amplifier, sensors, a display, and embedded software. The chips enable the node to operate as either a mobile sensor node or a relay base station node while providing a long distance relay link between nodes. The power amplifier enables a line-of-sight communication between the one or more nodes. The sensors provide a GPS signal, temperature, and accelerometer information (used to trigger an alert condition). The embedded software captures and processes the sensor information, provides a multi-hop packet routing protocol to relay the sensor information to and receive alert information from a command center, and to display the alert information on the display