The advent of web services by the end of the year 2004, saw the emergence of many internet services, among which social networks, cloud computing, and so on. These services combined with the generalization of IoTs (Internet of Things) in 2010, contributed to the production of huge volumes of data, known today as Big data, which had to be transported through several networks, from different production sources to storage and processing places, based on cloud computing data centers.

Cloud Computing

Cloud computing is a centralized pool of shared and configurable computer resources that are network-accessed, rapidly provisioned and released with minimal management effort or provider interaction.

During the period from 2004 to 2010, only cloud computing could handle the huge and evolving demand for data storage and processing. And as the volumes of data to be stored and processed increased, increased,  orders for services kept pouring in, so that cloud computing hit an unprecedented hype. The Gartner Group included it in their ''hype cycle graph'', as a technology of the future.

But over time, the continuous exponential increase of the huge volumes of data produced daily, especially with new processing needs, which require certain data to be processed in very short time frames, network latency has proven to be a penalizing factor.

So, to get around this hurdle, some IT companies designed a solution based on CDN Network (Content Distributed Network - built around distributed proxy servers and data centers, with the goal to provide high availability and performance by distributing the service over internet to end users).

This initiative gave birth to the emergence of a new network service, based on a paradigm in total disruption with the techniques used by cloud computing, with the final objective of reducing the latency encountered with the latter. This service is called Edge Computing.

Edge Computing

Edge Computing is a technology, based on micro data centers, located closer to IoTs networks, so that large volumes of data generated by IoTs can be processed with reduced latency.

Besides resolving the latency problem, edge computing offers a lot of others benefits, compared to cloud computing, such as:

  • Reduced cost, as data doesn’t have to be moved over an important number of networks as it is with cloud computing, Instead, data is collected at the edge of the IoTs networks, stored ans processed nearby,
  • Enhanced security, as the surface of hacking attack is very thin because data is not being moved over networks,
  • Compliance with regulatory requirements through the processing, storage and deletion of personal data as close as possible to the source,
  • Connection doesn’t have to be kept on, to do the processing, once data is collected and stored,
  • IoTs are programmable devices, so they can extend the equipment capital with hardware scaling, Applications in need of large bandwidth, can get good performance,
  • Legal investigations can be conducted if hacking attacks happen, as edge data centers are all located in regions within the US, which is not the case with cloud computing, whose data centers are most of the time deployed overseas, which would present judicial issues, as there exist for the time being no transnational laws taking care of hacking problems, within the cyberspace,
  • And, so on.

For all the reasons related to the advantages provided by edge computing, many public cloud providers, like Google, Amazon web services, Microsoft azure, etc, already offer dedicated edge computing, by hosting the infrastructures on the premises of client companies. Furthermore, some IT companies have made edge computing one of their areas of development.

In addition, the advent of 5G, which proposes to bring an internet speed ten times faster than the current standard for a latency time of the order of a millisecond, will boost the capacities of edge computing. Once coupled to 5G, Edge Computing will be able to meet data processing requirements in near real time.

Conclusion

Due to the many benefits mentioned above, that edge computing offers for the processing of big and time-sensitive data, many companies have adopt it.

Hence, deciding which of cloud or edge computing to choose for your applications seems to be straightforward. But, one has to keep in mind that these two technologies are different in architecture and functioning, and cannot, whatsoever, as said above, replace one another. They can though be complementary, as once data is collected and processed at the edge, it can be moved to the cloud, to be stored, and if needed, reprocessed for others purposes.