Edge Processing Flashcards
What is Edge Computing?
Many organizations would like to implement edge computing, but its future will be determined, at least in part, by the cost of its hardware and the development of appropriate software. At present, edge computing is very expensive to install, and only large businesses and corporations can afford these systems. Two factors restrict the use of edge computing – the expense of the hardware and the cost of creating customized edge computing software solutions.
Edge computing describes a range of networks and devices that monitor and work with nearby technology. The basic concept deals with processing data nearer its source, rather than sending it to a cloud that may be located far, far away. It takes time for data to move from point A to point B, and back – the greater the distance, the longer it takes (referred to as “latency”). By handling the data through the use of nearby edge computers (often specialized mini-computers), more data can be processed at greater speeds.
“The whole point of edge computing is to get closer to devices, to reduce the amount of data that needs to be moved around for latency reasons, to get closer so that responses are faster.”
The use of edge computing provides results more quickly than the cloud.
What solutions are used for Edge Computing?
Traditional edge devices include edge routers, routing switches, firewalls, multiplexers, and other wide area network (WAN) devices. Intelligent edge devices have built-in processors with onboard analytics or artificial intelligence capabilities. Such devices might include sensors, actuators, and IoT gateways.
What is driving edge computing?
Organizations have begun to transition to SSE or are considering SSE for two main reasons. The first, which started a while ago, is the increased reliance on cloud-delivered applications. Organizations needed a way for branch and remote users to access applications like Office 365 and Salesforce without introducing latency.
A traditional approach to securing these applications would be to put a centralized firewall or VPN solution between the user and application, forcing the user to access the application through the corporate data center. Inevitably, this slows down access to the application.
By moving security services to the cloud edge, SSE allows users to access cloud-delivered applications over a direct internet connection for a much faster experience.
The second main driver of SSE was COVID-19. The sharp and sudden rise in remote work forced organizations to think about how they could deliver a consistent user experience for a user whether they were at home, at the branch or at the campus.
The ability of SSE to apply unified security policies suddenly became very attractive for IT leaders. With SSE, security policy stays with the user, regardless of where they are getting work done.
How do you secure edge computing?
Edge security devices may include routers, firewalls, WAN devices and more — designed to protect an organization from IoT edge computing devices that connect to the network. These security devices are intended to preserve the network’s perimeter and protect the network from devices on the edge
What are the limitations to edge computing?
Two factors restrict the use of edge computing – the expense of the hardware and the cost of creating customized edge computing software solutions.
How can edge computing for space?
Although studies on edge computing in existing terrestrial networks have been actively conducted, a different approach is needed to apply edge computing to LEO satellites. This is because all satellite components of the core networks, including LEO satellite networks, are connected wirelessly, and the satellites orbit around the Earth at a very high speed. Furthermore, the satellites have a lower power supply and computing power than terrestrial networks. Therefore, customized solutions are needed for new areas that have not been covered by terrestrial networks.
Professor Jeongho Kwak and Professor Jihwan Choi’s research teams proposed a network slicing technique that harnesses the distribution and movement characteristics of LEO satellites and the characteristics of wireless-channel environments in a scenario with several virtualized services. At the same time, they also proposed a code and data-offloading technique for satellite-edge computing.
The edge-computing and slicing techniques developed for LEO satellites in this research are significant because they advance the domestic satellite network technology one step further. However, in South Korea, this technology is still in the early stages compared with overseas countries, where LEO satellite internet services such as Elon Musk’s Starlink are being commercialized.
Professor Jeongho Kwak of the Department of Electrical Engineering and Computer Science at DGIST said, “This research analyzed the effect of network slicing and code/data offloading ratio according to the changing LEO satellite environment.” He added, “Our goal is to provide a blueprint for novel applications for LEO satellites in the 6G era in the future.”
Key Ideas of Edge Computing?
Boosts performance
Hosting applications and data on centralized hosting platforms or centers can create latency when users try to use them over the internet. The process of requesting data from these data centers can get slow when there are internet connectivity issues. Edge computing solves this issue by keeping the data on the edge of the devices for easier access.
Enhances privacy protections and data security
Data security and privacy protections are burning issues in the IT world. Edge computing provides more data security and privacy protection because data is processed within the edge rather than from central servers.
Reduces operational costs
Moving data around on cloud hosting services is one of the things businesses spend a lot of money on. The higher the volume of data being moved on these centralized hosting providers, the more money organizations spend.
However, with edge computing, organizations spend less on operational costs due to the minimal need to move data to the cloud. In addition, since data is processed in the same location it’s generated, there is also a reduction in the bandwidth needed to handle the data load.
Helps in meeting regulatory and compliance requirements
Meeting regulatory and compliance requirements can be made more difficult when data is hosted and managed by different data centers or hosting providers. This is because each data center has its peculiar privacy and regulatory requirements.
Enhances reliability and resiliency
With edge computing, data can still be fetched and processed with little or no hindrances, even when there is a poor internet connectivity issue. In addition, when there is a failure at one edge device, it won’t alter the operation of other edge devices in the ecosystem, facilitating the reliability of the entire connected system.
Supports AI/ML applications
There is no denying the growing relevance of artificial intelligence (AI) and machine learning (ML) in modern computing. However, AI/ML applications work by fetching and processing huge volumes of data, which can suffer latency and connectivity issues when the data is hosted on a centralized server.
In contrast, edge computing facilitates AI/ML applications because data is processed close to where it’s created, making it easier and faster for AI/ML to obtain results.
