Edge Computing
Edge computingis a method of optimizing cloud computing systems by performing data processing at the edge of the network, near the source of the data.
This reduces the communications bandwidth needed between sensors and the central datacenter by performing analytics and knowledge generation at or near the source of the data.
This approach requires leveraging resources that may not be continuously connected to a network such as laptops, smartphones, tablets and sensors.Edge computing covers a wide range of technologies including wireless sensor networks, mobile data acquisition, mobile signature analysis, cooperative distributed peer-to-peerad hoc networking and processing also classifiable as local cloud/fog computing and grid/mesh computing, dew computing, mobile edge computing, cloudlet, distributed data storage and retrieval, autonomic self-healing networks, remote cloud services, augmented reality, and more.
Possible advantages of edge computing are
- Edge application services significantly decrease the volumes of data that must be moved, the consequent traffic, and the distance the data must travel, thereby reducing transmission costs, shrinking latency, and improving quality of service(QoS).
- Edge computing eliminates, or at least de-emphasizes, the core computing environment, limiting or removing a major bottleneck and a potential point of failure.
- The ability to "virtualize" (i.e., logically group CPU capabilities on an as-needed, real-time basis) extends scalability. The edge-computing market generally operates basically on a "charge for network services" model, and it could be arguedthat typical customers for edge services are organizations desiring linear scale of business application performance to the growth of, e.g., a subscriber base.
LFEdge
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. https://www.lfedge.org/#
EVE (Edge Virtualization Engine)
Project EVE develops the open source Edge Virtualization Engine (EVE). EVE leverages a type-1 hypervisor, so it deploys on bare metal device hardware. It also provides system and orchestration services, and a container runtime. This means developers can enjoy consistent behavior on any supported platform. EVE can run both legacy and newer cloud-native apps in edge computing devices.
Edge devices based on EVE gain the following capabilities:
- Higher efficiency and usage of device resources
- "Secure by default" deployment profile
- Host any operating system deployable in a virtual machine
- Host many apps in virtual machines and containers
- Serverless capability via unikernels
- Scalable, centralized management for many devices over large distances, and hosting many apps
- Remote updates of entire software stack
- Remote control of all device resources including CPU, memory, networking, and device ports
- Automated patching for security updates
- Automated connectivity to one or more public clouds
- Built-in mesh networking capabilities for edge-to-edge data flow
- Built-in cloud networking using standard VPN technologies available in public clouds
https://www.lfedge.org/projects/eve