Which of the following will you typically see in an edge network? (Select all that apply.)
Compute nodes
Core network
Cloud data center
Virtualized servers
Intermediary data hubs
Answers
Explanation:
Edge computing is a distributed computing paradigm that brings computation and data storage closer to the location where it is needed, to improve response times and save bandwidth.[1]
The origins of edge computing lie in content delivery networks that were created in the late 1990s to serve web and video content from edge servers that were deployed close to users.[2] In the early 2000s, these networks evolved to host applications and application components at the edge servers,[3] resulting in the first commercial edge computing services[4] that hosted applications such as dealer locators, shopping carts, real-time data aggregators, and ad insertion engines.[3]
Modern edge computing significantly extends this approach through virtualization technology that makes it easier to deploy and run a wider range of applications on the edge servers.
Concept Edit
The increase of IoT devices at the edge of the network is producing a massive amount of data to be computed at data centers, pushing network bandwidth requirements to the limit.[10] Despite the improvements of network technology, data centers cannot guarantee acceptable transfer rates and response times, which could be a critical requirement for many applications.[11] Furthermore, devices at the edge constantly consume data coming from the cloud, forcing companies to build content delivery networks to decentralize data and service provisioning, leveraging physical proximity to the end user.
In a similar way, the aim of Edge Computing is to move the computation away from data centers towards the edge of the network, exploiting smart objects, mobile phones or network gateways to perform tasks and provide services on behalf of the cloud[12]. By moving services to the edge, it is possible to provide content caching, service delivery, storage and IoT management resulting in better response times and transfer rates. At the same time, distributing the logic in different network nodes introduces new issues and challenges.
Privacy and security Edit
The distributed nature of this paradigm introduces a shift in security schemes used in cloud computing. Not only should data be encrypted, but different encryption mechanism should be adopted, since data may transit between different distributed nodes connected through the internet before eventually reaching the cloud. Edge nodes may also be resource constrained devices, limiting the choice in terms of security methods. Moreover, a shift from centralized top-down infrastructure to a decentralized trust model is required.[13] On the other hand, by keeping data at the edge it is possible to shift ownership of collected data from service providers to end-users.
Scalability Edit
Scalability in a distributed network must face different issues. First, it must take into account the heterogeneity of the devices, having different performance and energy constraints, the highly dynamic condition and the reliability of the connections, compared to more robust infrastructure of cloud data centers. Moreover, security requirements may introduce further latency in the communication between nodes, which may slow down the scaling process.[11]
Reliability Edit
Management of failovers is crucial in order to maintain a service alive. If a single node goes down and is unreachable, users should still be able to access a service without interruptions. Moreover, edge computing systems must provide actions to recover from a failure and alerting the user about the incident. To this aim, each device must maintain the network topology of the entire distributed system, so that detection of errors and recovery become easily applicable. Other factors that may influence this aspect are the connection technology in use, which may provide different levels of reliability, and the accuracy of the data produced at the edge that could be unreliable due to particular environment conditions.[11]
Speed Edit
Edge computing brings analytical computational resources close to the end users and therefore helps to speed up the communication speed. A well designed edge platform would significantly outperform a traditional cloud-based system.
Efficiency Edit
Due to the proximity of the analytical resources to the end users, sophisticated analytical tools and Artificial Intelligence tools can run on the edge of the system. This placement at the edge helps to increase operational efficiency and contributes many advantages to the system
Answer:
Compute nodes
Virtualized servers
Intermediary data hubs
Explanation: