Although not the primary function of a web proxy, many implementations, in addition to enabling controls and compliance with access policies, can also considerably assist bandwidth savings for enterprises.
The term bandwidth, applied in this article, is not related to creating mechanisms that prevent users from using resources such as streaming, online radio, social networks, and cloud backup tools and so on. On the contrary, the concept presented here will focus on the economy of appeal, without the need to apply changes in Internet access policy.
Nevertheless, how is this possible? By using caching techniques integrated with the proxy service, it is possible to ensure that certain objects requested on sites are copied to the proxy, so if other users from the same network access the same website, there is no need to proceed with a new request, since the data will be stored in the proxy.
For small businesses, caching can offer a faster browsing experience for the user; that is fine, but it has little financial impact on a business. For medium and large companies, caching represents more than speed for users, but it brings financial savings by allowing a slower link to serve a larger number of employees.
In this article, we will discuss how to economize bandwidth using the caching feature in various web proxy solutions available in the market.
Since the proxy is an asset responsible for mediating all traffic between two parties (usually a user and an internet service/website), it is automatically possible to access content of both the request and the response.
This positioning is fundamental to understand how the overall functioning of a caching structure is. The objects requested by browsers, through the instructions contained in the code of the pages, when passed through the proxy, can be stored locally (recorded on disk or other storage device), allowing other requests to be downloaded locally instead of going to the internet, generating much higher access speed.
Imagine a company with approximately 200 employees accessing the internet daily through their computers. It is common for news websites or other content to be consumed equally by multiple users throughout the day.
Without a caching structure, all the requests made by these users pass through the proxy, being directed to the internet. With caching, most requests are still being sent to the internet, but there is considerable bandwidth savings, since certain types of objects are recorded locally, optimizing access.
If each user consumes around 20Mb internet daily, we have a total of approximately 4 Gb. If 30% of this traffic goes to websites common to them and have 2 Mb caching per user, at the end of the day the caching will bring about an internet usage savings of approximately 400Mb.
This is just one example of how caching can truly help bandwidth savings in a business. The savings rate can vary greatly according to the company’s access profile, and the type of solution used.
There are several caching applications and levels of expertise. In corporate environments, it is natural to work with caching of certain objects, and that is enough. However, for large providers, performing streaming caching can be very interesting to provide better response times for your subscribers, in addition to large bandwidth savings.
Therefore, it is important to identify and characterize the need for bandwidth savings, in order to create a correct alignment of solution expectation. For most business cases, of the most varied sizes, combining the web proxy feature with caching is quite satisfactory.
The caching is stored on low or high-speed magnetic disks, depending on the criticality of the environment. In addition, it is common to keep more requested objects in a memory space, to avoid read and write operations on disks, which end up being much slower than unloading the object from memory.
There are several algorithms for distributing storage, selecting objects to be stored, updating, and replacement policy, since caching space does not necessarily have to be dedicated, and it will always have finite space.
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