Everyone is familiar with cloud computing. Many enterprises host their applications on AWS or Google Cloud for example because it is an affordable and scalable solution for their computing needs. They pay a monthly subscription, can choose to increase their computing power as needed, all without the hassle of having to manage, own and maintain on-premise servers.
However, cloud computing may have a few draw backs depending on the use cases. The end user is unable to know or control at which location their data is being processed. This can result in lowered responsiveness as the data could be processed very far from the source, resulting in a delay from sending information to the cloud, processing it, and sending back the output.
You may have even experienced this yourself, when you ask your Smart Home Device a question, it takes a few seconds to send your question to the cloud and get an answer before replying you. This happens for any cloud service provider whether it’s AWS, Apple iCloud or Google Cloud.
Edge cloud computing seeks to bridge this gap and improve the responsiveness of connected devices by delivering compute power closer to the data source. Given the increased use of Internet-of-Things (IoT) devices, example for Augmented Reality and Facial Recognition, edge cloud computing will become increasingly important to improve application performance and further propel the growing use of IoT devices.
Benefits of edge cloud computing with cloud service providers
Edge cloud computing is important for the delivery of mission-critical data that requires real-time responsiveness. Typically, on-premise solutions allow you to process data more quickly but require a higher investment into infrastructure and manpower. However, a cloud computing solution will mean delays in data delivery since data has to be sent back to the cloud belonging to the cloud service provider and you may end up with higher bandwidth requirements if you are consistently transmitting large amounts of data.
Edge cloud computing solutions provided by cloud service providers utilise edge devices or hubs that are closer to your devices. Your devices can send raw data to an edge cloud computing hub, have the data processed and then only send back the relevant information to your HQ or DC. This will improve responsiveness and reduce bandwidth requirements.
If you have data localisation requirements, edge cloud computing enables you to keep sensitive information on local servers that are highly secure without having to send it globally to the centralised cloud.
You benefit from:
- Lower latency
- Lower cost of ownership (vis a vis on premise solutions)
- Compliance with data localisation rules
Applications of edge cloud computing
Edge cloud computing can be used in any situation that requires real-time responses and data transmission from IoT solutions such as autonomous vehicles or video analytics.
Connected machinery and equipment can send real-time data on manufacturing process yield, production output and status. This will allow managers to make adjustments to improve efficiency.
Edge cloud computing also powers the use of IoT in factories and enable predictive maintenance. IoT sensors can pick up signals that indicate that equipment is due for servicing and maintenance work, which can avoid downtime that may lower production efficiency. IoT also facilitates the use of augmented reality to troubleshoot factory issues and provide remote support.
IoT sensors can be used in a retail outlet to track footfall and the products that attract the most attention and interest. This would enable a store manager to stock up on items that sell quickly proactively and make decisions on product placement. A Point of Sales (POS) video analytics solution can also be used to quickly serve the right ad to the right person as they are viewing the display.
IoT technology can further be used to manage facilities. Building managers can enable auto-locking for rooms to increase security and use intelligent features that predict and manage environmental conditions. For example, air-conditioners can be set to turn on automatically when someone is in the room.
Video analytics can be used to track mobility and areas where queues or congestion are forming so that building managers and traffic wardens can act quickly to smoothen out traffic flow.
Furthermore, governments are partnering with cloud service providers to look at video analytics and contact tracing, such as Singapore’s TraceTogether app. They are considering using video analytics as tools to monitor public health and mobility during the pandemic. These depend on IoT technology to collect data from various devices and inputs and gather them for real time analysis. The data can be processed at the nearest edge cloud location and enable government authorities to react swiftly to prevent further viral infections within communities.
Capabilities of edge cloud computing with cloud service provider SPTel
SPTel’s pervasive hubs around the island means your computing is done close to the data source. This provides you with faster computing speeds and lower latency without having to make a hefty investment into on-premise solutions.
You also don’t have to transmit large volumes of data to the cloud or a central data centre which can lower the cost of bandwidth. SPTel can connect our edge cloud servers to data centres and public clouds to complete the data transmission ecosystem.
With SPTel as your cloud service provider, you benefit from
- Enhanced performance as IoT devices need only to relay data to their nearest Edge server for fast data processing
- Lowers the bandwidth required to relay data, allowing companies to expand their computing capacity and optimise their network expenditure