The Era of Edge Computing Is Here
Edge computing is gaining traction as it does address some of the key issues in the Industrial IoT case. Edge computing, for example, allows data to be analyzed and filtered closer to sensors, with only a small amount of data being sent to the cloud, a move that can dramatically reduce network bandwidth costs and cloud data storage costs.
Additionally, many Industrial IoT use cases require sub-second (i.e. 1GHz/1.2s) response times for safe and precise operation. For example, if a human gets too close to an industrial device, the device needs to stop working immediately. In this case, the decision of the device to stop working cannot wait for the signal feedback from the IoT cloud platform. If signal processing is brought to the edge, sub-second response times can be achieved for the entire reflection process. Another use case is self-driving cars, which also require sub-second response times.
Security and privacy requirements in the Industrial IoT case are also driving the need for edge computing. Factories and critical infrastructure are using edge devices to protect critical industrial processes and equipment from other network connections. Likewise, the data generated by these machines is often considered confidential, with edge meters keeping sensitive information inside the factory. Finally, edge computing also allows autonomous operations. Many industrial operations run out of control if there are network connectivity issues. Once edge computing is applied, equipment and factories can continue to operate regardless of network availability.
"Beach landing" edge computing
Edge computing has caught the attention of technology vendors, and some small startups are creating specialized edge computing stacks. IoT platform vendors have edge solutions connected to IoT hardware, and even open source foundations see a potentially huge opportunity in edge computing.
The battle between different vendors and the open source community is still dynamic. Some vendors are looking for complete cloud solutions, some have partnered with each other, and others are working with the open source community. There is no clear front-runner in this space for now, but it seems that some have achieved more success than others.
IoT cloud provider
IoT cloud provider edge computing solutions are committed to providing customers with integrated overall solutions, including devices from edge platforms to cloud platforms as a whole. They make it easier for customers to build, deploy and manage IoT devices connected to their cloud platforms. It's a compelling move for customers looking to quickly launch new connected products. However, the risk of such an integrated solution is that it will be tied to long-term suppliers.
Amazon and Microsoft are heavyweight players in IoT cloud providers, and both have edge computing solutions connected to their respective IoT cloud platforms. Amazon Web Services offers AWS IoT Greengrass, which allows connected devices to run AWS Lambda functions, AWS services to run machine learning, data synchronization, and connectivity to AWS IoT Core. Likewise, Microsoft IoT Edge allows connected devices to run MS Azure services, and Microsoft has made IoT Edge an open source project on GitHub. This seems to make it easier to port IoT edge devices to other hardware platforms, but again it seems to be closely tied to the Azure IoT Hub cloud platform.
Google has released Cloud IoT Edge, which appears to be focused on delivering AI capabilities at the edge, but Cloud IoT Edge is still in alpha. Google also announced a partnership with prominent edge computing provider Foghorn.
Many IoT platform vendors are also creating their own edge computing products. Companies such as Litmus Automation, Clearblade, Bosch IoT Suite, Software AG Cumulocity offer edge computing solutions connected to their IoT platforms. The focus of these companies is to be able to run data analytics and machine learning models on edge hardware.
Some of these vendors also have partnerships with IoT hardware vendors. For example, Software AG has partnered with Dell and Eurotech to offer its edge software solutions on Dell and Eurotech hardware. Integrated hardware and software solutions for this advantage will make it easier for these companies to market joint solutions to customers.
edge computing provider
There are many venture-backed startups focused on delivering edge computing solutions. Companies like Foghorn and Swim focus on delivering machine learning and analytics, and others like Zededa and Edgeworx are bringing edge devices to virtualization and containers. All these companies are forming partnerships with major IoT platforms and IoT cloud providers to connect their edge computing solutions to different IoT platforms.
IoT Hardware Vendors
IoT gateway vendors are investing in software stacks that run on their hardware. These software stacks are becoming more complex to meet the demands of edge computing use cases. Interestingly, many hardware vendors are building software solutions based on open source projects.
Dell and Rigado have IoT gateways running Ubuntu Core that allow remote management and deployment of software running on their gateway devices, and Dell is also a leader in the EdgeX open-source project for edge computing. Eurotech provides the Everywhere Software Framework based on Eclipse Kura for building edge computing applications. ADLINK, a major Taiwanese gateway manufacturer, has developed Vortex Edge and Vortex DDS, which is an Eclipse Cyclone DDS-based project, to more easily deploy software on its gateways.
open source community
Open source foundations are also actively participating in the edge computing revolution. Due to the neutrality of the Open Source Foundation, it can provide a better communication platform for companies and individuals, promote multiple collaborations, and research innovative edge computing technologies together. The burgeoning edge computing open source community offers an interesting alternative for companies worried about being controlled by vendors, especially AWS and Microsoft.
For the most part, IoT cloud providers, IoT platform vendors, and Edge startups are not involved in the collaborative open source community building edge technologies. Only a small minority have created their own open source projects, and most continue to focus on delivering vendor-specific commercial solutions. Commercial solutions are often built on open source technologies, but companies are not actively involved. However, these actions by these vendors have not dampened the momentum of the Open Source Foundation to initiate collaborative open source projects for edge computing.
The Linux Foundation recently announced the formation of the LF Edge community. LF Edge includes 5 different open source projects, including EdgeX and Zededa's virtualization project Project EVE. The community already has 60 member companies, including Arm, AT&T, Dell, Ericsson, IBM, Intel, Samsung, and more, who have agreed to collaborate on building a common framework for edge computing.
The Eclipse Foundation is one of the most mature open source communities in the IoT space. Eclipse IoT was created 6 years ago and has more than 30 open source projects, including many for edge computing. Eclipse Kura is Eclipse's edge computing project, which also includes Eclipse ioFog and Eclipse fogO5, which create new edge computing technologies. Eclipse also hosts implementations of popular industry standards required for edge computing, such as MQTT, OPC-UA, DDS, CoAP, and LWM2M.
The OpenStack Foundation has also gradually expanded into the field of edge computing. In October 2018, the StarlingX project was launched based on the code contribution of Wind River. It is an integrated project of different open source projects, including CentOS, OvS-DPDK, Ceph, Kubernetes, and OpenStack, etc. The purpose is to be used on edge devices. Run cloud services.
Edge computing will be an integral part of any IoT solution. Customers benefit from the innovation and diversity of edge computing solutions. There is a trade-off between the full benefits of a single vendor and the ease of use of cloud infrastructure versus the cost of integrating the solution and avoiding vendor lock-in in the long term. Over time, customers often require heterogeneous computing solutions for distributed technologies such as edge computing. If history repeats itself, this time the industry will address the issue by defining common standards and protocols for edge computing and cloud communications. Like web technologies, these standards and protocols may be implemented by open source and standards communities that are not tied to any vendor.
Knowledge Base Team
Knowledge Base Team
Knowledge Base Team
Knowledge Base Team
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