Teemu Laukkarinen

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.

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.

Program image dissemination protocol for low-energy multihop wireless sensor networks

A Wireless Sensor Network (WSN) consists of programmable, low-cost and resource-constrained nodes. Adding new features or error fixes requires reprogramming nodes. Manually reprogramming hundreds or thousands of nodes is impractical as it takes significant effort and time. Therefore, WSNs require a mechanism for updating the nodes program image, which contains the applications and protocols running on each node. Current protocols for updating program images rely on a large external memory that is used to temporary store program images. In this paper we present the design, implementation and experimental measurements of a lightweight and reliable Program Image Dissemination Protocol (PIDP) for autonomous adhoc multihop WSNs. PIDP requires no external memory storage, is independent of the WSN stack, offers a low overhead protocol for transferring program images, and can reprogram the whole WSN stack. An update procedure with PIDP in one part of the network does not interfere with the WSN elsewhere. PIDP was implemented on a node platform with an 8-bit 2 MIPS Microchip PIC18LF8722 microcontroller and a 2.4 GHz Nordic Semiconductors nRF24L01 radio. PIDP requires less than 7 kilobytes of program memory and from 22 to 815 bytes of data memory. In experiments PIDP reprogrammed a campus WSN, which is a running deployment of 178 nodes, in 5 hours.

Pilot studies of wireless sensor networks: Practical experiences

For enabling successful field pilots of Wireless Sensor Network (WSN) applications, the network reliability and prototype testing become limiting factors. Application pilot studies need to operate end-to-end, covering the physical durability of devices, embedded software, and infrastructure interfaces and data collection. This paper summarizes our pilot study experiences, and what tools and practices were required. Six lessons are proposed: a systematic pilot template results straightforward pilot completion; shared WSN infrastructure reduces labor; tailored embedded software testing tools are needed; the pilot must be prepared carefully; the WSN technology must be usable for research partners; and the pilot must be maintained and maintenance tools are required in large scale pilots. Our experiences base on over 20 pilot studies and over 1000 deployed devices. This paper describes 11 main pilots, which utilize from 10 to 377 devices per pilot.

Unified service access for wireless sensor networks

Sensor networks enable large scale and fine resolution monitoring via interconnected sensor devices that range from home appliances and mobile phones to dedicated sensing platforms. While new wireless technologies are emerging, the challenge is in the interpretation and utilization of heterogeneous data received through varying types of interfaces. This paper presents a unified service access architecture, interfaces, and message formats for Wireless Sensor Networks (WSNs) collectively referred to as WSN OpenAPI. It supports sensor data collection, actuator control, real-time alerts based on sensor values, and querying measurement and alert history. Compared to the related work, WSN OpenAPI allows efficient machine-to-machine (M2M) communications with low complexity message formats and avoiding extensive queries with publish/subscribe paradigm.

Survey and evaluation of neural computation models for bio-integrated systems

Abstract Integrating neurobiological cultures with computer systems presents an opportunity to enhance computational energy efficiency. These Bio-Integrated Systems (BISs) require knowledge about structure and behavior of neural components and their interfacing. In the early design phases, modeling neurons offers cost, failure-free and retrial benefits compared to laboratory grown neural networks. The usefulness of these models lays in characteristics of being realistic but also computationally efficient. This survey reviews computational models of spiking neurons and their changes in connections, known as plasticity. The review studies models that are faithful to real neural cultures, and are computational efficient for real-time BISs. Also, criteria and methods for comparing models with ‘in-vitro’ experiments are reviewed to conclude on the level of realism of models in comparison with biological setups. Izhikevich’s model of spiking neurons is recommended due to its accuracy in reproducing real neural firing patterns, computational efficiency, and ease of parameter adjustment. The model of Spike-timing dependent plasticity is recommended as current basis for representing neuron changes in connections. For the analysis of network connectivity and connectivity changes in BIS, the Cox method is recommended because it evaluates connections based on activities from all recorded neurons as opposed to pair-wise approaches.

HybridKernel: Preemptive kernel with event-driven extension for resource constrained wireless sensor networks

A low-power wireless sensor network (WSN) implements dynamic communication protocols and embedded sensing applications on resource constrained platform. WSNs utilize dozens of tasks, which have differentiated realtime requirements. This requires an efficient implementation with the use of a real-time operating system optimized for WSNs. Current WSN operating systems are based either on preemptive or event-driven kernels. Preemption provides accurate timings but requires large data memory footprint. Event-driven kernels have small footprint but do not support time as accurately. This paper presents a new HybridKernel for WSNs which combines the advantages of both kernels. It meets five key requirements without any major drawbacks: it halves footprint of preemptive kernels, it provides 2 µs timing accuracy, it minimizes energy consumption, and it can be easily configured and used between preemptive and event-driven parts through a coherent system call interface.

DevOps in regulated software development: case medical devices

DevOps and continuous development are getting popular in the software industry. Adopting these modern approaches in regulatory environments, such as medical device software, is not straightforward because of the demand for regulatory compliance. While DevOps relies on continuous deployment and integration, regulated environments require strict audits and approvals before releases. Therefore, the use of modern development approaches in regulatory environments is rare, as is the research on the topic. However, as software is more and more predominant in medical devices, modern software development approaches become attractive. This paper discusses the fit of DevOps for regulated medical device software development. We examine two related standards, IEC 62304 and IEC 82304-1, for obstacles and benefits of using DevOps for medical device software development. We found these standards to set obstacles for continuous delivery and integration. Respectively, development tools can help fulfilling the requirements of traceability and documentation of these standards.

Building wireless sensor networks with biological cultures: components and integration challenges

Abstract The development of wireless sensor networks (WSNs) struggles with limited computing, communication, and energy resources. Bio-Integrated Systems (BISs) contain cultured cells that perform certain tasks. For instance, neurons can work as brains for robots. BISs could provide solutions to overcome WSNs resource constraints. Biological entities integrating in computing hardware gains interest especially in robotics. This interest is due to the potentials of such integration in deep learning capacity, massive parallelism, energy savings, and communication and integration with living subjects. This paper collects existing BISs research and provides research motivations for Bio-Integrated WSNs (BI-WSNs). BI-WSNs solutions for improving energy preserving, sensing, processing, and communication are proposed and supported with existing examples. Further, on-going research on integrating neural networks in WSNs is presented. Challenges related to protection of biological entities from external environment are discussed. Finally, a prospective model of BI-WSNs consisting in optogenetic communication combined with neural network processing is given. Graphical abstract This graphical abstract represents the different components of a node of a sensor networks. This paper studies the possibilities to replace each of these components with a biological counterpart enabling similar functionalities. The benefits and challenges for the development of such biological sensors, named Bio-Integrated Wireless Sensor Network (BI-WSN), are discussed in this study.

Social Index: A Content Discovery Application for Ad Hoc Communicating Smart Phones

A modern smart phone contains detailed information about the owner through the phone book, music lists, and social media integration, which can be used to recommend new interesting content to the user. Combining this information with ad hoc peer-to-peer communication of the smart phones allows users to find new interesting content and persons in the proximity and exchange messages. Social Index allows users to anonymously find interesting new content in the proximity. The prototype Social Index application was tested with a simulator running anonymized Facebook profiles, and with real test users. All the test users found interesting people using the simulator.