Things in the Cloud


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Cloud computing is one of those things that is becoming “popular” these days. Now when things become popular in the world of technology—as opposed to the world of “pop” culture for instance—there is usually also a technical and economic reason. In addition, as with most popular things, the exact definition of what constitutes cloud computing could best be described as “nebulous.” In this case, however, that means that cloud computing can take many forms depending on the type of application or service, or how it is provided.

Basically, however, cloud computing is modeled on the idea that there is a remote server or servers that provide the service of hosting a client’s data and/or applications so the client can avoid the upfront investment in servers. This can help many start-up ventures get off the ground because as the amount of storage and usage grows, the cloud service provider adds more server resources and charges accordingly. Of course, there are many issues with such a model, such as security, availability (will the service provider always be online?), volume of Internet usage as data is sent back and forth to the remote servers, and privacy to mention a few.

Cloud services are often hosted on large server farms that are shared by a large number of clients with widely differing needs and applications. In many instances their data is hosted along with their, often proprietary, applications on the cloud servers. Of course, this makes it convenient for remote and mobile users to take advantage of the service wherever they are, but it also brings up problems with security and other matters. So there are quite a few decisions a potential user must make when contracting for a cloud computing service—which brings us to the Internet of Things.

With the ever-growing number of devices that are connected to the Internet, the issues of managing them are growing as well, as is the question of the role of cloud computing involving large numbers of often relatively simple devices. Remote management of embedded systems has long been attractive because of the potential savings in terms of service calls and the ability to do things like large scale updates from a remote site. Often the management strategy will depend on the number and complexity of the systems involved. 

For example, if you are managing 100 remote pumping installations, it might make sense to have each one with an embedded web page that could be individually called up for monitoring, diagnostics and upgrades and that could also autonomously send data and alerts as needed. Managing such a small number of sites in a cloud computing model might not be the most attractive scenario. However, when the picture changes to managing 10,000 relatively simple devices like vending machines, things can look entirely different.

In such a scenario, each machine still has a connection to the Internet, but we have a large number of devices dealing with relatively small amounts of data each. There is still a need for two-way communication but it must now be via a large database on a server rather than directly with actual users or service personnel. To be sure, service personnel are still involved but seldom interact with the individual devices. An application can be used to sweep up all the data and present it in any way desired for things like routing delivery and service vehicles or ordering more product to fill the machines. The application can be hosted on the cloud server or on machines at the user’s site. The advantage of reducing the investment in server hardware remains. There is also a rather intriguing possible advantage in terms of security.

Something as simple as a vending machine or a remote sensor may only send data infrequently and then perhaps only a packet or two at a time. If such data needs to be confidential, the actual meaning of the data in the packet can be secured by the application. The bit fields in the packet are not identified in the packet. They are simply written to by the device and read by the application. Thus the actual fields representing things like device ID, time, amount deposit, number of Jolt Colas, Mountain Dews, etc., are only known at the end of the network, not within the cloud. This, of course, depends on the application not being hosted in the cloud as well.

As intelligent devices connected to the Internet and to private networks proliferate, the data they generate will grow at many times that rate and require huge amounts of storage and connectivity to manage. The emergence of the cloud model to accommodate such growth will become more attractive as ideas that begin as relatively small applications grow to very large ones.