MIS 3406 PRO Points Assignment
Edge computing shortens the distance between running applications and data sources. Proximity can improve bandwidth, providing faster insights to businesses. By processing data in edge locations rather than central servers, it can decrease the load placed on a single data center while increasing security in case one area is taken down. Green cloud computing is a method of cloud computing that focuses on minimizing environmental impact. This can be achieved by designing and using spaces such as data centers in a relatively environmentally friendly way.
In our second in-class activity, we used CloudFront CDN to service our webpages across the globe, allowing people from halfway across the world to load a page as quickly as anyone else. Using a CDN is important since we stored our data in S3, a regional service provided by Amazon. It allows us to copy our webpage from the S3 buckets to various edge locations across the globe for anyone to have proximity, and thus quick access to the page. This would be an example of edge computing since we used a CDN to shorten the distance between people running an application and the data source via edge locations. During the course introduction, we covered the concept of incremental cost scaling – the idea that cloud computing involves renting outsourced virtual hardware and software instead of buying physical hardware and software. Costs are variable instead of fixed, capacity is not unused, the platform is resistant to demand shocks, and the company does not have to worry as much about hardware and software. This means that companies who choose cloud computing already prioritize costs over other factors. By using green cloud computing to design a data center in a way that reduces energy consumption, companies that own data centers can use these energy savings to reduce costs and attract more cost conscientious customers who are making the switch to cloud native.
Edge computing provides many environmental benefits that one could potentially argue that edge computing itself is an example of green cloud computing. Some of these benefits include efficiency, lower latency, Big Data filtering, and hardware reuse. Edge spaces are typically less restricted than data centers, allowing them to be better optimized for efficient energy consumption. The proximity between the device where data is created and the edge location where data is processed also reduces latency, also resulting in less energy required for network operation. Edge locations can also play a filtering role, determining which data is important enough to get sent back to the data center. This further reduces energy consumption and even bandwidth costs.
NVIDIA uses edge computing to manage environmentally friendly resources such as EVs, solar panels, wind farms, and home batteries. This helps them develop smart grids, autonomous operations at energy sites, energy pipeline optimization, power grid maintenance, and power grid simulation. It seems natural that a company integrating AI into its sustainability efforts does so via edge computing since it integrates green cloud computing for reasons listed above.
References
Anand, A. (2022, July 11). Green cloud computing: the future of sustainable cloud computing. The Cloud Report. https://cloud.report/articles/green-cloud-computing-the-future-of-sustainable-cloud-computing
Banik, A. (2021, December 13). Top security issues and benefits for edge computing and 5G. Analytics Insight. https://www.analyticsinsight.net/top-security-issues-and-benefits-for-edge-computing-and-5g/
Gomez, R. (2022, January 27). Edge computing fuels a sustainable future for energy. https://developer.nvidia.com/blog/edge-computing-fuels-a-sustainable-future-for-energy/
IBM. (n.d.). What is edge computing? https://www.ibm.com/cloud/what-is-edge-computing
Velez, J. (2022, September 10). How industrial companies can reduce their energy costs with edge computing. Barbara IoT. https://barbaraiot.com/blog/how-industrial-companies-reduce-energy-cost-edge-computing