LF Edge
Welcome to the LF Edge wiki, where you will find information with a cross project focus. For individual projects, follow the links below.
LF Edge is an umbrella organization that aims to establish an open, interoperable framework for edge computing independent of hardware, silicon, cloud, or operating system. By bringing together industry leaders, LF Edge will create a common framework for hardware and software standards and best practices critical to sustaining current and future generations of IoT and edge devices.
We are fostering collaboration and innovation across the multiple industries including industrial manufacturing, cities and government, energy, transportation, retail, home and building automation, automotive, logistics and health care — all of which stand to be transformed by edge computing.
Questions? Please visit the FAQ.
Projects
Title | Technical Charter | TSC Chair | Description | |||
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STAGE 3: IMPACT |
| Chair: @Yin Ding Co-Chair: @Haruhisa Fukano | Aims to create an open source software stack that supports high-availability cloud services optimized for edge computing systems and applications. | ||
| STAGE 1: AT LARGE | @Trevor Conn | Project Alvarium, with initial code seeded by Dell Technologies, is aimed at building a framework and SDK for trust fabrics that deliver data from devices to applications with measurable confidence. Trust fabrics take a system-level approach by layering trust insertion technologies spanning silicon to cloud and will usher in an entire new era of business models and customer experiences driven by interconnected ecosystems. Initial contributing companies include Dell, the IOTA Foundation, Intel, Arm, VMware and ZEDEDA. | |||
STAGE 4: Emeritus |
| Baetyl (pronounced “Beetle”) offers a general-purpose platform for edge computing that manipulates different types of hardware facilities and device capabilities into a standardized container runtime environment and API, enabling efficient management of application, service, and data flow through a remote console both on cloud and on prem. Baetyl also equips the edge operating system with the appropriate toolchain support, reduces the difficulty of developing edge calculations with a set of built-in services and APIs, and provides a graphical IDE in the future. | ||||
STAGE 3: IMPACT |
| @James Butcher | EdgeX, your data liberated! Highly flexible open source software framework that facilitates interoperability between heterogeneous devices and applications at the IoT Edge, along with a consistent foundation for security and manageability regardless of use case. The open, vendor-neutral platform speeds developer and technology providers time to market by providing modular reference services for device-data ingestion, normalization, analysis and sharing in support of new IoT data services and advanced edge computing applications. | |||
STAGE 1: AT LARGE | @Jiyong Huang | eKuiper is an edge lightweight IoT data analytics/streaming software implemented by Golang, and it can be run at all kinds of resource-constrained edge devices. One goal of eKuiper is to migrate the cloud streaming software frameworks (such as Apache Spark,Apache Storm and Apache Flink) to the edge side. eKuiper helps to bring computation closer to where data is generating, with an introduced rule engine to enable streaming applications on the edge side. | ||||
STAGE 2: GROWTH | @Erik Nordmark | An open abstraction engine that simplifies the development, orchestration and security of cloud-native applications on distributed edge hardware. Supporting containers, VMs and unikernels, EVE provides a flexible foundation for Industrial and Enterprise IoT edge deployments with choice of hardware, applications and clouds. | ||||
STAGE 3: IMPACT | @Robert Raesemann | Fledge is an open source framework and community for the Industrial Edge. Architected for rapid integration of any IIoT device, sensor or machine all using a common set of application, management and security REST APIs with existing industrial "brown field" systems and clouds. Fledge edge services include: Collect Data from any/all sensors, aggregate/combine/organize data. edge based alerting/anomaly detection/machine learning (TensorflowLIte, OpenVino), transform/filter data in flight, buffer data, analyze/visualize edge data, and deliver data to multiple local/cloud destinations. | ||||
| STAGE 4: Emeritus |
| Interoperable, flexible, and scalable edge computing services platform with a set of APIs that can also run with libraries and runtimes. | |||
| STAGE 1: AT LARGE |
| InfiniEdge AI is redefining technology with a pioneering open-source framework designed specifically for edge devices. By tailoring AI models to operate optimally on smartphones, smart speakers, edge cloud systems, and beyond, InfiniEdge AI enables efficient real-time applications that function independently of central servers. This innovative approach drastically cuts data traffic and significantly boosts user privacy and security. | |||
STAGE 1: AT LARGE |
| InstantX solves the problem of asynchronous and instant data exchange across clients in the same region while offering that data for off-line processing and self-learning to derive further added-values. In the specific case of V2X data distribution, it solves the problem of mobility data fragmentation by distributing data and mobility insights across different types of traffic and transportation domains.
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STAGE 1: AT LARGE |
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STAGE 1: AT LARGE |