There are five imperatives that are driving computing toward the edge: Latency/Determinism (Microseconds to sub-seconds, Consistency); Data/Bandwidth (Massive or moderate, Local value or aggregated value); Limited Autonomy (Occasionally autonomous or fully dependent, Self-organizing and discovering); Privacy/Security (Private/Sensitive or public, Regulated/Geo-Specific or unregulated); and Local Interactivity (Locally Collaborative or Locally Responsive, Horizontal or Vertical). Another use is distributed content and Domain Name System (DNS) caching, which reduces server load and speeds up delivery of data to customers.[15]. Edge Computing will not be a single market dominated by one vendor; there will be many types of edges and with many markets, addressed by various architectures, topologies, vendors and providers. The virtual appliance applications are delivered as packaged operating system virtual machine (VM) images or containers incorporating operating systems and applications. A predominant type of Edge Computing is called Mobile Edge Computing (MEC), an architecture that utilizes the edge of the cellular network for enhanced operations. Like in a gateway device or a PC sitting next to the device. Edge Computing is a part of a distributed computing/network topology that requires and includes a “core”, either an enterprise data center or a centralized cloud service. Technical standards for MEC are being developed by the European Telecommunications Standards Institute, which has produced a technical white paper about the concept. [19], Another pattern is failure to integrate security from concept to production. There are several related terms that have been used in place of the “Edge Computing” term. 5G); and Cloudlets, which is essentially “cloud in a box”, bringing the cloud closer to users, enabling disconnected cloud computing. [7], In the context of IIoT, the edge refers to the computing infrastructure that exists close to the sources of data, for example, industrial machines (e.g. Data is processed at the edge, and all or a portion of it is sent to the central processing or storage repository in a corporate data center, co-location facility, or IaaS cloud. This proximity to data at its source can deliver … A Survey on Mobile Edge Computing. Moving vehicles, machines, parts, people or fluids are examples where delays could equal missed opportunities, high costs or security threats. It will continue to enable many new use cases and open up opportunities for telecom providers to … However, in that instance, a quick turnaround of data and action result is expected. Edge computing refers to applications, services, and processing performed outside of a central data center and closer to end users. This eliminates the need to send engine sensor data back to a central server, either on the plane or in the cloud to determine more pressing tactical issues, such as if the engine is overheating or burning too lean.[11]. Industry 4.0 transforms the traditional production system into the new model called “Industrial Internet of Things” (IIoT). There are, however, several key drivers making Edge Computing a more viable reality today. The purpose is to remove processing latency, because the data does not need to be sent from the edge to the core central processing system and back again. The ability to deal with these processes at the edge will take care of about 90% of most required IoT-based processing, and the data and computation requirements are typically small. 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. An Edge Device can be any device that produces data. Edge Computing locations will develop organically in enterprises and enterprise-owned locations, spread out from cloud providers and carriers, and expand from the footprints of smartphones, appliances, game consoles, smart speakers, and gateways. The far edge expands beyond the manufacturing floor and connects manufacturers with business partners and even consumers to improve proactive service for after-sales parts and services. However, the cloud is still an important part of IIoT equation. Multi-access edge computing (MEC), formerly mobile edge computing, is an ETSI-defined[1] network architecture concept that enables cloud computing capabilities and an IT service environment at the edge of the cellular network[2][3] and, more in general at the edge of any network. Once referred to as mobile edge computing, its name has shifted over the years as its immense capabilities have evolved. India: 10th IEEE International Conference on Intelligent Systems and Control (ISCO’16), India. This server provides computing resources, storage capacity, connectivity and access to RAN information. MEC technology is designed to be implemented … Edge computing brings cloud resources—compute, storage and networking—closer to applications, devices and users. MEC technology is designed to be implemented at the cellular base stations or other edge nodes, and enables flexible and rapid deployment of new applications and services for customers. [16] Through Edge Computing, IT professionals hope to improve network security and enhance other network outcomes. However, data transport to and from the cloud is limited by the speed of light and the “size” of the internet “pipes”. Edge computing is where server resources, ranging from credit-card-size computers to micro data centers, are placed closer to data and information-generation sources, to reduce the latency and bandwidth issues associated with large-scale cloud computing. Long latency (delay), as is typical across networks when data is shared to a cloud or data center, is undesirable for IoT devices. Edge computing is a cloud computing optimization. Oppose - Edge devices in networking get you onto to the network. However, there will be a wide variety of choices in between, based on latency, bandwidth, connection to the core, autonomy, security, privacy, regulatory requirements, etc. Edge Computing deploys data-handling activities or other network operations away from centralized and always-connected network segments and core, and toward individual sources of data capture, such as endpoints like laptops, tablets, or smartphones. 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