Abstracting Application Development for Resource Constrained Wireless Sensor Networks

Ubiquitous computing is a concept whereby computing is distributed across smart objects surrounding users, creating ambient intelligence. Ubiquitous applications use technologies such as the Internet, sensors, actuators, embedded computers, wireless communication, and new user interfaces. The Internet-of-Things (IoT) is one of the key concepts in the realization of ubiquitous computing, whereby smart objects communicate with each other and the Internet. Further, Wireless Sensor Networks (WSNs) are a sub-group of IoT technologies that consist of geographically distributed devices or nodes, capable of sensing and actuating the environment.WSNs typically contain tens to thousands of nodes that organize and operate autonomously to perform application-dependent sensing and sensor data processing tasks. The projected applications require nodes to be small in physical size and low-cost, and have a long lifetime with limited energy resources, while performing complex computing and communications tasks. As a result, WSNs are complex distributed systems that are constrained by communications, computing and energy resources. WSN functionality is dynamic according to the environment and application requirements. Dynamic multitasking, task distribution, task injection, and software updates are required in field experiments for possibly thousands of nodes functioning in harsh environments.The development of WSN application software requires the abstraction of computing, communication, data access, and heterogeneous sensor data sources to reduce the complexities. Abstractions enable the faster development of new applications with a better reuse of existing software, as applications are composed of high-level tasks that use the services provided by the devices to execute the application logic.The main research question of this thesis is: What abstractions are needed for application development for resource constrained WSNs? This thesis models WSN abstractions with three levels that build on top of each other: 1) node abstraction, 2) network abstraction, and 3) infrastructure abstraction. The node abstraction hides the details in the use of the sensing, communication, and processing hardware. The network abstraction specifies methods of discovering and accessing services, and distributing processing in the network. The infrastructure abstraction unifies different sensing technologies and infrastructure computing platforms.As a contribution, this thesis presents the abstraction model with a review of each abstraction level. Several designs for each of the levels are tested and verified with proofs of concept and analyses of field experiments. The resulting designs consist of an operating system kernel, a software update method, a data unification interface, and all abstraction levels combining abstraction called an embedded cloud.The presented operating system kernel has a scalable overhead and provides a programming approach similar to a desktop computer operating system with threads and processes. An over-the-air update method combines low overhead and robust software updating with application task dissemination. The data unification interface homogenizes the access to the data of heterogeneous sensor networks. A unification model is used for various use cases by mapping everything as measurements. The embedded cloud allows resource constrained WSNs to share services and data, and expand resources with other technologies. The embedded cloud allows the distributed processing of applications according to the available services. The applications are implemented as processes using a hardware independent description language that can be executed on resource constrained WSNs. The lessons of practical field experimenting are analyzed to study the importance of the abstractions. Software complexities encountered in the field experiments highlight the need for suitable abstractions.The results of this thesis are tested using proof of concept implementations on real WSN hardware which is constrained by computing power in the order of a few MIPS, memory sizes of a few kilobytes, and small sized batteries. The results will remain usable in the future, as the vast amount, tight integration, and low-cost of future IoT devices require the combination of complex computation with resource constrained platforms

Abstracting Application Development for Resource Constrained Wireless Sensor Networks

Ubiquitous computing is a concept whereby computing is distributed across smart objects surrounding users, creating ambient intelligence. Ubiquitous applications use technologies such as the Internet, sensors, actuators, embedded computers, wireless communication, and new user interfaces. The Internet-of-Things (IoT) is one of the key concepts in the realization of ubiquitous computing, whereby smart objects communicate with each other and the Internet. Further, Wireless Sensor Networks (WSNs) are a sub-group of IoT technologies that consist of geographically distributed devices or nodes, capable of sensing and actuating the environment.WSNs typically contain tens to thousands of nodes that organize and operate autonomously to perform application-dependent sensing and sensor data processing tasks. The projected applications require nodes to be small in physical size and low-cost, and have a long lifetime with limited energy resources, while performing complex computing and communications tasks. As a result, WSNs are complex distributed systems that are constrained by communications, computing and energy resources. WSN functionality is dynamic according to the environment and application requirements. Dynamic multitasking, task distribution, task injection, and software updates are required in field experiments for possibly thousands of nodes functioning in harsh environments.The development of WSN application software requires the abstraction of computing, communication, data access, and heterogeneous sensor data sources to reduce the complexities. Abstractions enable the faster development of new applications with a better reuse of existing software, as applications are composed of high-level tasks that use the services provided by the devices to execute the application logic.The main research question of this thesis is: What abstractions are needed for application development for resource constrained WSNs? This thesis models WSN abstractions with three levels that build on top of each other: 1) node abstraction, 2) network abstraction, and 3) infrastructure abstraction. The node abstraction hides the details in the use of the sensing, communication, and processing hardware. The network abstraction specifies methods of discovering and accessing services, and distributing processing in the network. The infrastructure abstraction unifies different sensing technologies and infrastructure computing platforms.As a contribution, this thesis presents the abstraction model with a review of each abstraction level. Several designs for each of the levels are tested and verified with proofs of concept and analyses of field experiments. The resulting designs consist of an operating system kernel, a software update method, a data unification interface, and all abstraction levels combining abstraction called an embedded cloud.The presented operating system kernel has a scalable overhead and provides a programming approach similar to a desktop computer operating system with threads and processes. An over-the-air update method combines low overhead and robust software updating with application task dissemination. The data unification interface homogenizes the access to the data of heterogeneous sensor networks. A unification model is used for various use cases by mapping everything as measurements. The embedded cloud allows resource constrained WSNs to share services and data, and expand resources with other technologies. The embedded cloud allows the distributed processing of applications according to the available services. The applications are implemented as processes using a hardware independent description language that can be executed on resource constrained WSNs. The lessons of practical field experimenting are analyzed to study the importance of the abstractions. Software complexities encountered in the field experiments highlight the need for suitable abstractions.The results of this thesis are tested using proof of concept implementations on real WSN hardware which is constrained by computing power in the order of a few MIPS, memory sizes of a few kilobytes, and small sized batteries. The results will remain usable in the future, as the vast amount, tight integration, and low-cost of future IoT devices require the combination of complex computation with resource constrained platforms

Regulated Software Meets DevOps

Abstract Context: Regulatory authorities require proofs from critical systems manufacturers that the software in their products is developed in accordance to prescribed development practices before accepting the product to the markets. This is challenging when using DevOps, where continuous integration and deployment are the default practices, which are not a good match with the regulatory software development standards. Objective: We aim to bring DevOps and regulated software development closer to each other. First, we want to make it easier for developers to develop regulated software with tools and practices they are familiar with. Second, we want to allow regulatory authorities to build confidence on solutions provided by manufacturers by defining a mapping between DevOps and regulatory software development. Method: We performed a literature survey and created research suggestions using exploratory research. Results: Tighter integration between development tools, requirements management, version control and deployment pipeline would simplify the creation of regulatory compliant development practices. Conclusions: Regulations could be improved for more agile and incremental method in quality approval, the final step before the actual deployment of the software. Improved development practices and tool integration, created in cooperation by tool vendors, system providers, and regulatory authorities, could support developers who are not comfortable with fixed, and rigid practices of regulated software development.Peer reviewe

A Survey of Wireless Sensor Network Abstraction for Application Development

Wireless sensor network (WSN) application development is not an easy task due to its resource constrained nature and vast feature rich application space. Several abstractions are harnessed to ease out the difficult WSN application development. In this paper, three levels of abstractions are classified from the existing literature: node, network, and infrastructure abstractions. Since the node and network abstractions are already a well-studied area, the infrastructure abstraction is surveyed in detail to complete knowledge. Technology interoperability, service discovery, metadata support, and processing support are found as basic requirements for infrastructure abstraction. Problematic security and quality of service topics are discussed and the open research questions of ontology, service discovery, distributed processing, and performance metrics are defined. Finally, a distributed middleware design is presented as a possible solution for the key open research question: how to utilize capabilities of the abstracted technologies

Rakennusfysikaalisten testivuosien päivitystyö rakentamisen mitoitussäät (RAMI) -hankkeen osana

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Kipsilevytuulensuojallisten puurunkoisten ulkoseinärakenteiden rakennusfysikaalinen toiminta

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An Embedded Cloud Design for Internet-of-Things

Internet-of-Things (IoT) consists of interconnected heterogeneous devices that ubiquitously interact with physical world. The devices are often resource constrained in terms of energy, computation, and communication resources. Distributing processing between these heterogeneous devices could yield to better performance and sharing, and extending resources of the devices could yield to more intelligent ubiquitous applications. Such a design can be called as “embedded cloud”, which is defined in this paper. An embedded cloud design is presented that consists of distributable Process Description Language (PDL), Distributed Middleware (DiMiWa), and an infrastructure. As a result, PDL can execute distributed processes and share resources as services over heterogeneous IoT devices with help of DiMiWa and the infrastructure. The design is evaluated with a prototype implementation, where PDL and DiMiWa are executed on a small 8-bit microcontroller-based IoT device. The implementation requires only 5122 B of program memory (4% of the available), consumes under 1 ms of CPU time per process in the worst case, and allows over 100 simultaneous services per device

Ilmakehän pitkäaaltoinen säteily rakennusfysikaalisissa laskentatarkasteluissa

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