Software Engineering for Internet of Things

物联网（IoT）是新一代软件密集型技术的前沿，必将对社会产生深远影响。物联网应用将各种传感器和执行器连接到人，建筑物，城市等，并在云端收集和处理数据，以改善人们的生活，提高经济效率，并确保更好的环境保护。特定的子领域，如自动驾驶汽车和机器人，智能交通和建筑（一般称为网络物理系统），增强系统的驱动能力，以改变其行为，结构或参数。 该研究计划的长期目标是为可预测和强大的物联网系统开发科学和工程基础。为了实现可预测和运行时可管理的物联网系统，我们需要方法和工具来指定它们的运行时可变性和约束。新一代物联网系统是数据密集型的，数据是由位于基础设施边缘的分散传感器以高速率大量生成的。这是昂贵的，并导致延迟和可变性，以将整个数据传输到公共云。我们专注于如何指定数据流和自适应组件，如传感器，执行器，分析器和规划器，以便它们以分散或集中的方式适时地放置计算和传输数据。 物联网系统在运行时具有内在的自适应性：它们监控环境，分析数据并适应变化。适应的决定可以由系统本身在可行的情况下做出，或者由人在回路中在需要人为干预的情况下做出。同时，还有自适应软件系统管理，其中软件组件在运行时自动重新配置，优化或保护或修复。我们将探讨这些自适应服务的设计，实施，干扰和最终的协调，使整体系统的要求得到满足。 构建强大的物联网应用程序的基础是软件和物理世界的模型。在设计时，模型可以允许设计人员探索行为空间并验证是否满足规范。在运行时，模型将服务于运行时自适应控制器来管理软件和物理部分。 该研究计划将使用理论和实验方法，并在物联网，自适应系统和云计算的新兴领域培养学生。这些培训将使他们为加拿大经济中需求量很大的工作做好准备。该计划还将为学生提供知识，以了解新技术的社会和道德影响。预计这项研究计划的结果将推动对加拿大工业，研究人员和公民非常重要的领域的最新技术。

The Internet of Things (IoT) is at the forefront of the new generation of software intensive technologies that are bound to deeply impact society. IoT applications interconnect a variety of sensors and actuators attached to people, buildings, cities, etc., and collect and process data in the cloud to improve people's lives, increase economic efficiency and ensure better environmental protection. Specific subdomains, such as autonomous vehicles and robots, smart transportation and buildings (generically known as Cyber Physical Systems), augment systems with actuating capabilities to change their behavior, structure or parameters. The long term goal of this research program is to develop scientific and engineering foundations for IoT systems that are predictable and robust. To achieve predictable and runtime manageable IoT systems, we need methods and tools to specify their runtime variability and constraints. The new generation of IoT systems is data intensive, where data is generated in large volumes and at high rates by dispersed sensors located at the edges of the infrastructure. It is costly and induces latency and variability to transfer the entire data to the public cloud. We focus on how to specify the data flows and adaptation components, such as sensors, actuators, analyzers and planners, so that they opportunistically place computation and transfer data, either in a decentralized or centralized manner. IoT systems are inherently adaptive at runtime: they monitor their environment, analyze the data and adapt to changes. The decision to adapt can be taken by the system itself when this is feasible or by a human-in-the-loop when the decision requires human intervention. Concurrently, there is the adaptive software system management, where software components are automatically reconfigured, optimized or protected or repaired at runtime. We will explore the design, implementation, interference and eventual coordination of these adaptive services so the overall system requirements are met. Fundamental to building robust IoT applications are models of the software and of the physical world. At design time, models can allow the designer to explore the behavioral space and verify if specifications are met. At runtime, models will serve runtime adaptive controllers to manage both the software and the physical parts. This research program will use theoretical and experimental methodologies and train students in the emergent fields of Internet of Things, adaptive systems and cloud computing. The training will prepare them for jobs that are in high demand in the Canadian economy. The program will also equip the students with the knowledge to understand the social and ethical implications of the new technologies. It is expected that the results of this research program will advance the state of the art in areas that are of great importance to Canadian industry, researchers, and citizens.