Edge computing, quite simply, complements the cloud, inexpensively analyzes and keeps data nearer to the where it’s required the most. As the pace of business intensifies, instantaneous response times become a critical expectation. Primarily functioning as a complement to cloud computing, edge computing involves collecting data from sensors, controllers, and other connected devices, and then transmitting it to a local server or laptop for initial analysis. Data processing and its analysis closer to the edge or the network is put immediately into action as opposed to the data center or the cloud.
Why edge computing?
Edge computing facilitates the growing need for real-time data analytics across industries. Performing computational tasks closer to original data sources like smartphones, sensors, drones, robots, HVAC units, etc., reduces transmission time and costs, enabling better response times and operational efficiency. Here are some of the key benefits of implementing edge computing:
- Access to real-time data
- Better data security from reduced risk of data loss or theft
- Enables faster intelligence and insights through reduced data transmission times
- Faster disaster prediction, detection, and prevention
- Optimized resource usage through reduced network traffic and latency
Edge computing use cases
Edge computing offers significant benefits in areas that depend on real-time data and insights for more efficient and intelligent operations. Some common use cases include consumer behavior analysis in the retail sector, compliance analysis in the BFSI sector, remote monitoring of oil rigs, IoT data analysis and monitoring, and smart lighting.
Mobile edge computing: Also known as multi-access edge computing (MEC), mobile edge computing enables data processing at the edge of a telecom network or access nodes. IDC forecasts the MEC market to reach $80 billion by 2021, driven by the need for faster response times and reduced data costs to support advanced gaming, connected vehicles, smart cities, and other mobile value-added services. MEC will act as a key enabler for IoT and advanced 5G applications.
Predictive monitoring: Edge computing is enabling companies, especially those in the industrial sector, to evolve from being reactive to predictive. For example, using edge computing to analyze the data collected from edge sensors can help design better maintenance strategies in oil and gas exploration. As a result, companies can benefit from greater uptime of pumping operations and lower costs of maintaining equipment.
Augmented Reality (AR): AR-based applications require large computation power to be able to quickly respond to the user’s actions and update virtual environments. Edge computing can address this need with its ability to process data quickly with low latency.
Autonomous vehicles: Edge computing will play a crucial role in helping autonomous vehicles to process and transfer critical data in real-time. With this technology, automated vehicles can help save thousands of lives and billions of dollars by preventing automobile casualties.
With the proliferation of IoT, the impending commercial roll-out of the 5G network, and surge in the data being generated by connected devices, edge computing is expected to find numerous applications across industries. According to research estimates, the edge computing market is growing rapidly at a CAGR of over 30 percent and is expected to reach almost USD 7 billion within the next five years. As with any technological change, edge computing will disrupt existing computing models and create new requirements, leading to the emergence of new opportunities and threats. Netscribes helps companies identify and overcome the shifts caused by disruptive technologies through comprehensive technology market intelligence. To know more, reach out to us at firstname.lastname@example.org.