Edge computing is an IT architecture designed to put applications and data closer to the users or “things” that need them. It brings bandwidth-intensive content and latency-sensitive applications closer to the user or data source
Vast volumes of data are being produced from various sources in our hyper connected world. Every second we are adding millions of gigabytes of data to the already overflowing data bank. Where is all this data coming from? Be it social media platforms or e-commerce sites, streaming services to enterprises, all of us are generating a surfeit of data from multiple assets, adding to data volumes. Most of this data travels across the internet and adding to this data clutter chaos is the fact that less important data is travelling over the same network as business-critical data. Unfortunately, the internet is not designed to factor in how much time a given data package takes to reach its destination.
For businesses, data represents a treasure trove of actionable information. It can yield valuable insights about customers, competition, markets and much else. True, that our devices are becoming smarter by the day and are capably taking their own decisions. As for businesses, Internet of Things is make judicious use of data possible - it could be used to cut down unseen expenses, or to develop strategic business plans and remain competitive, or to innovate new revenue streams or simply to improve efficiencies all around.
But the increasing volume and velocity of data has brought on inefficiencies. These result from our legacy systems, frequent server downtimes, lack of visibility, and general latency in transmitting this huge data volume to a cloud or datacenter for processing. Often, devices are unable to handle the data overload and affect the seamless communication between device and IoT server, rendering it slow and inefficient. The result of all this is network latency which spikes up the network bandwidth cost. Data storage, security and compliance are also affected adversely.
All this gives rise to the need for a technology that can seamlessly handle the ever growing data deluge. Here’s more about Edge computing:
What is Edge Computing?
In simpler terms, Edge is the ability to collect and process data at the device level, without having to wait for device-cloud server integration. As bandwidth-intensive content and the number of attached “things” over the internet keep growing, slowing the data transport networks and decreasing data availability, Edge brings computing nearer to our devices. It works to minimize these issues and enable a seamless experience. Our current needs are growing apace and if we go by it, our future needs will far outstrip the current technology capabilities. It is to support these current and future needs that mobile telecom networks and data networks are converging into a cloud computing architecture and computing power and storage is being inserted out on the network edge. This will lower data transport time and increase availability.
Simply put, Edge computing depends on edge agents that are the intelligence at the edge of our connected devices. These agents are like covert operatives who collect, process, and analyze data right at the device level. This means that there is no need for the entire volume of data to go to the server sites. Edge thus enables faster analysis, and quicker detection of anomalies by saving the time that the entire data traveling to the server would take. But edge is more than just an intelligence operative. It is also a troubleshooter that remains unfazed in the face of challenges. Edge can capably take all decisions including critical action when a connection fails between Edge and the cloud server. The result: A snag-free system or service function.
Technically speaking, Edge computing is an IT architecture designed to put applications and data closer to the users or “things” that need them. The difference between cloud computing and edge computing is that while the former drove the creation of few mega datacenters; edge computing brings distributed IT with an exponential number of micro datacenters. Thus, Edge computing brings bandwidth-intensive content and latency-sensitive applications closer to the user or data source.
Why Edge Computing?
To answer this question we need to understand the digital transformation landscape. Companies around the world are deploying cloud-based IT resources, from compute power to storage and applications, all is cloud architecture, in order to improve customer experience, streamline operations, and create new business opportunities. However, to meet user expectations, companies need to complement these cloud-based resources.
Putting it in perspective, a Schneider Electric White Paper titled ‘The Drivers and Benefits of Edge Computing’ says, this is where edge computing comes in. Companies can achieve higher bandwidth, lower latency, regulatory compliance around location and data privacy, by deploying Edge data centers. Edge computing enables this by placing data acquisition and control functions, storage of high bandwidth content, and applications closer to the end user. Edge intelligence is inserted into a logical end point of a network (Internet or private network), as part of a larger cloud computing architecture.
Schneider Electric White Paper provides three primary applications of Edge Computing:
1. Edge computing is a tool to gather massive information from local “things” as an aggregation and control point.
Edge computing enables high bandwidth content distribution. But first let us understand what latency means. It is the time between the moment a data packet is transmitted to the moment it reaches its destination (one way) and returns (round trip). These data packets are information time-bombs for enterprises, and any delay can be critical. Most data travels only one way, but it is almost impossible to measure. That is why round-trip time from a single point is the most common latency measurement. Bandwidth on the other hand refers to the transmission speed of data on the network. However, the actual speed obtained in a given network is almost always lower than the peak rating provided by the manufacturers. Excessive latency becomes a problem as it creates traffic jams preventing data from filling the network to capacity. Now, latency can impact a network bandwidth temporarily, lasting just a few seconds much like traffic lights at a junction; or its impact can be more constant like being stuck in a single lane bridge.
To overcome these issues, now and in the future, and decongest a network to improve streaming of high bandwidth content like video content, service providers are interconnecting a system of computers on the Internet. This system caches the content closer to the user and enables the content to be deployed rapidly to numerous users by duplicating the content on multiple servers and directing the content to users based on proximity. These computers caching content are an example of Edge computing.
2. Edge computing finds it second and critical application as IoT aggregation and control point.
As we look forward to become residents of “smart” cities, travel in smart cars, eat produce of smart agriculture, have access to smart healthcare and surround ourselves with everything smart, we are making huge demands on technology. The technology of the future requires massive deployment of Internet of Things (IoT) sensors. An IoT sensor is defined as a non-computer node or object with an IP address that connects to the Internet. IoT can automate operations by: Gathering information automatically about physical assets (machines, equipment, devices, facilities, vehicles) to monitor status or behavior and by using that information to provide visibility and control to optimize processes and resources. With declining price of sensors, the number of connected IoT things will skyrocket. As per a Cisco estimate, the IoT will consist of 50 billion devices connected to the Internet by 2020. Machine to Machine (M2M), considered an integral part of the IoT, brings several benefits to industry and business in general as it has a wide range of applications in the Smart City. Our smart lifestyle of the future will, hence, rely on Edge computing.
3. The third application of Edge is in on-premise applications.
For enterprises, the need to maintain or increase availability of IT and its networks is a top concern. While cloud computing is a centralized architecture; Edge computing transforms cloud computing into a more distributed computing cloud architecture. The advantage with Edge computing then is that any kind of disruption is limited to only one point in the network instead of the entire network. For example, a Distributed Denial of Service DDoS attack or a long lasting power outage, would be limited to the edge computing device and the local applications on that device as opposed to all applications running on a centralized cloud datacenter. Companies that have migrated to off-premise cloud computing can take advantage of edge computing for increased redundancy and availability. Business critical applications or applications needed to operate the core functions of the business can be duplicated on-site.
Edge computing is the future. By helping to solve latency challenges, it enables companies to take better advantage of opportunities leveraging a cloud computing architecture. Further, as Edge datacenters bring bandwidth intensive content closer to the end user and latency-sensitive applications closer to the data, latency is competently tackled. With Edge computing, power and storage capabilities are inserted directly on the edge of the network thus lowering transport time and improving availability. There is no time-bomb ticking on the Edge.
(This article is based on Schneider Electric White Paper titled ‘The Drivers and Benefits of Edge Computing’)