Do you want to publish a course? Click here

Femto-Containers: DevOps on Microcontrollers with Lightweight Virtualization & Isolation for IoT Software Modules

181   0   0.0 ( 0 )
 Added by Emmanuel Baccelli
 Publication date 2021
and research's language is English




Ask ChatGPT about the research

Development, deployment and maintenance of networked software has been revolutionized by DevOps practices, which boost system software quality and agile evolution. However, as the Internet of Things (IoT) connects low-power, microcontroller-based devices which take part in larger distributed cyberphysical systems, such low-power IoT devices are not easy to integrate in DevOps workflows. In this paper, we contribute to mitigate this problem by designing Femto-Containers, a new hardware-independent mechanism which enable the virtualization and isolation of software modules embedded on microcontrollers, using an approach extending and adapting Berkeley Packet Filters (eBPF). We implement a Femto-Container hosting engine, which we integrate in a common low-power IoT operating system (RIOT), and is thus enhanced with the ability to start, update or terminate Femto-Containers on demand, securely over a standard IPv6/6LoWPAN network. We evaluate the performance of Femto-Containers in a variety of use cases. We show that Femto-Containers can virtualize and isolate multiple software modules executed concurrently, with very small memory footprint overhead (below 10%) and very small startup time (tens of microseconds) compared to native code execution. We carry out experiments deploying Femto-Containers on a testbed using heterogeneous IoT hardware based on the popular microcontroller architectures Arm Cortex-M, ESP32 and RISC-V. We show that compared to prior work on software-based low-power virtualization and isolation, Femto-Containers offer an attractive trade-off in terms of memory footprint, energy consumption, and security. The characteristics of Femto-Containers satisfy both the requirements of software modules hosting high-level logic coded in a variety of common programming languages, and the constraints of low-level debug snippets inserted on a hot code path.



rate research

Read More

Internet of Things (IoT) and Network Softwarization are fast becoming core technologies of information systems and network management for next generation Internet. The deployment and applications of IoT ranges from smart cities to urban computing, and from ubiquitous healthcare to tactile Internet. For this reason the physical infrastructure of heterogeneous network systems has become more complicated, and thus requires efficient and dynamic solutions for management, configuration, and flow scheduling. Network softwarization in the form of Software Defined Networks (SDN) and Network Function Virtualization (NFV) has been extensively researched for IoT in recent past. In this article we present a systematic and comprehensive review of virtualization techniques explicitly designed for IoT networks. We have classified the literature into software defined networks designed for IoT, function virtualization for IoT networks, and software defined IoT networks. These categories are further divided into works which present architectural, security, and management solutions. In addition, the paper highlights a number of short term and long term research challenges and open issues related to adoption of software defined Internet of things.
Internet-native audio-visual services are witnessing rapid development. Among these services, object-based audio-visual services are gaining importance. In 2014, we established the Software Defined Media (SDM) consortium to target new research areas and markets involving object-based digital media and Internet-by-design audio-visual environments. In this paper, we introduce the SDM architecture that virtualizes networked audio-visual services along with the development of smart buildings and smart cities using Internet of Things (IoT) devices and smart building facilities. Moreover, we design the SDM architecture as a layered architecture to promote the development of innovative applications on the basis of rapid advancements in software-defined networking (SDN). Then, we implement a prototype system based on the architecture, present the system at an exhibition, and provide it as an SDM API to application developers at hackathons. Various types of applications are developed using the API at these events. An evaluation of SDM API access shows that the prototype SDM platform effectively provides 3D audio reproducibility and interactiveness for SDM applications.
Internet of Things Driven Data Analytics (IoT-DA) has the potential to excel data-driven operationalisation of smart environments. However, limited research exists on how IoT-DA applications are designed, implemented, operationalised, and evolved in the context of software and system engineering life-cycle. This article empirically derives a framework that could be used to systematically investigate the role of software engineering (SE) processes and their underlying practices to engineer IoT-DA applications. First, using existing frameworks and taxonomies, we develop an evaluation framework to evaluate software processes, methods, and other artefacts of SE for IoT-DA. Secondly, we perform a systematic mapping study to qualitatively select 16 processes (from academic research and industrial solutions) of SE for IoT-DA. Thirdly, we apply our developed evaluation framework based on 17 distinct criterion (a.k.a. process activities) for fine-grained investigation of each of the 16 SE processes. Fourthly, we apply our proposed framework on a case study to demonstrate development of an IoT-DA healthcare application. Finally, we highlight key challenges, recommended practices, and the lessons learnt based on frameworks support for process-centric software engineering of IoT-DA. The results of this research can facilitate researchers and practitioners to engineer emerging and next-generation of IoT-DA software applications.
310 - Martin Bauer 2021
For IoT to reach its full potential, the sharing and reuse of information in different applications and across verticals is of paramount importance. However, there are a plethora of IoT platforms using different representations, protocols and interaction patterns. To address this issue, the Fed4IoT project has developed an IoT virtualization platform that, on the one hand, integrates information from many different source platforms and, on the other hand, makes the information required by the respective users available in the target platform of choice. To enable this, information is translated into a common, neutral exchange format. The format of choice is NGSI-LD, which is being standardized by the ETSI Industry Specification Group on Context Information Management (ETSI ISG CIM). Thing Visors are the components that translate the source information to NGSI-LD, which is then delivered to the target platform and translated into the target format. ThingVisors can be implemented by hand, but this requires significant human effort, especially considering the heterogeneity of low level information produced by a multitude of sensors. Thus, supporting the human developer and, ideally, fully automating the process of extracting and enriching data and translating it to NGSI-LD is a crucial step. Machine learning is a promising approach for this, but it typically requires large amounts of hand-labelled data for training, an effort that makes it unrealistic in many IoT scenarios. A programmatic labelling approach called knowledge infusion that encodes expert knowledge is used for matching a schema or ontology extracted from the data with a target schema or ontology, providing the basis for annotating the data and facilitating the translation to NGSI-LD.
Each day the world inches closer to a climate catastrophe and a sustainability revolution. To avoid the former and achieve the latter we must transform our use of energy. Surprisingly, todays growing problem is that there is too much wind and solar power generation at the wrong times and in the wrong places. We argue for the construction of TerraWatt: a geographically-distributed, large-scale, zero-carbon compute infrastructure using renewable energy and older hardware. Delivering zero-carbon compute for general cloud workloads is challenging due to spatiotemporal power variability. We describe the systems challenges in using intermittent renewable power at scale to fuel such an older, decentralized compute infrastructure.
comments
Fetching comments Fetching comments
mircosoft-partner

هل ترغب بارسال اشعارات عن اخر التحديثات في شمرا-اكاديميا