Big Data Driven Networking Explained
Before understanding “Big Data Driven Networking” let’s break the title. You get two major terms, Big Data and Networking. What is Big Data? It is simply a term that describes large sets of data. It can be structured and unstructured. It’s not the amount of data we’re concerned with but what we do with the data that matters i.e. applying data science principles to it and draw some useful insights from it.
What is Networking? Networking in simplest terms is a process of connecting two computers together. It’s like establishing a connection between two workstations to exchange information. Big Data and Networking are closely related to each other and work hand in hand. This article is about how Big Data is utilized in networking. To give a brief outline, large amounts of data is first collected from various sources, and then it is sorted/pre-processed and transported to various data centers where the process of data analysis takes place. We would also be discussing 5G and its role in revolutionizing Big Data and networking.
5G and The Concept Of Communication, Caching and Computing:
To put it simply, 5G is a wireless network that enables faster communication. To understand this, imagine downloading a 1.25 GB movie in 10–20 seconds. With the arrival of 5G in hand, we would experience the massive flow of Data. To understand 5G better and its relation with the Big Data, we have to understand the three basic phenomenon that comprises 5G i.e. communication, caching and computing.
The 5G wireless network will support multiple diversities in terms of communication. This is where the concept of small cell base stations arrives. Small cell base stations would be densely deployed to improve the quality of communication across 5G networks. Small cell base stations are generally used to accommodate large amounts of traffic.
As we know that small cell base stations would be used to manage large amounts of data flowing, but there is one problem we need to tackle, the backhaul congestion. Backhauling is simply a process of sending network data over and out of the way route, taking it farther than its destination in order to get data there. With the massive amount of traffic being generated by 5G, then it’s obvious that the backhauling would be impacted as well. That’s where the concept of caching arrives. Caching will simply store the most requested content as its first priority and reduce redundant transmission to the remote server. For example, if there are 500 users are active at the moment and 300 of them are requesting the data “A” then the caching would simply store “A” in the first place closer to the users so that when the users request “A” then it will simply send the data reducing redundancy.
Now that we’ve understood the concept of communication and caching, let’s discuss one more important concept called cloud computing. What is a cloud? No, it’s not that cloud that causes rain. It is a backup option to store all your data when you know that your main source of data might be lost or get corrupted. Cloud computing is becoming a new trend in this day and age and with the arrival of 5G, it will completely change the dynamics of information sending and retrieving. Cloud computing will support various network-intensive applications such as augmented reality. So now, you have a broad idea of how communication, caching and computing improves 5G.
5G wireless networks: The Bridge
Before we dive into the concept of what the bridge in networking is, let’s understand the concept of data center and data source. The data center is simply the entity that requests data from the data source (which has the requested data) and then the data source replies back to the data center with the requested data. 5G will be used as the medium for the communication between the data center and the data source.
The concept discussed above was just the tip of the iceberg. Let’s go a little deeper and explore how exactly data center and data source communicates and what processes and subprocess are involved. The communication between data source and data center can be broken down into three processes, data acquisition, data preprocessing and data transportation.
Data Acquisition is simply acquiring data from the data source. For example, automobiles, mobile phones, smart meters, drones and various other electronic devices are generating a truckload of data constantly with the help of data gathers such as sensors. We call this a raw data because it is unsorted, unstructured and unorganized.
Data preprocessing is a method that helps to sort and to organize data. Various sub-processes such as data compression and data aggregation are applied for sorting. This process occurs before the transmission of data to data centers. 5G wireless networks support data preprocessing with the help of RAN. After the process of preprocessing, the transmission of data takes place.
Data transmission takes place when the data is preprocessed and it’s ready for transmission. First data is transmitted from RAN to the core network and then to the data center for analysis. Different datasets have different requirements when it is being transmitted from data source to data centers. For example, healthcare data and smart metering data are two distinct data sets so the requirements would be different for each of them. Healthcare data needs to be more secure and organized than the smart metering data which is giving out just random readings.
Networking for Big Data:
To support efficient networking for big data, big data’s features such as volume, velocity, and variety should be accommodated by the 5G wireless networks. First big data volume requires great network capacity and that capacity can be made available by use and re-use of spectrums. Spectrums help to boost network capacity. So, adding more spectrums can boost network capacity which enables the 5G to exchange huge amounts of data. The velocity of Big Data refers to how rapidly the data is acquired, pre-processed and delivered. The more the velocity, the better will be the communication. Lastly, variety refers to the different types of data sets. As described earlier, different data sets need to satisfy different requirements in terms of deploying it. So, you can say that volume and velocity features mainly aim for the efficient use of the infrastructure of the network while variety feature is more related to its deployment methods.
In Big Data processing chain, communication, computing, and storage resources are needed at different points between the journey from the data source to the data center. Here is the important point, the infrastructure of the 5G wireless networks remains same but the Big Data will be different in terms of its variety. So, communication, computing, and storage resources have to be called at different points between the data source and the data center. It is like manipulating all the available resources in the infrastructure to satisfy the data requirements.
One method for handling all the varieties of Big Data simultaneously is called network slicing. As the name suggests, we would slice our network to pieces and each piece would handle a different functionality but utilize the same resource pool. Easy, right? Now let’s try to understand this concept in a deeper and a slightly technical way for you to really grasp the concept of slicing. Suppose the two organizations power grid supply and financial institutions are requesting data exchange from the same wireless network. As you can see that these two organization’s data are different in terms of variety so the network utilization would be completely different so how would the network handle it simultaneously? We would then divide the whole infrastructure of the network to small pieces and each piece would be allotted a certain task to perform. That way, we can easily manage these two different data requests. Note that each section/piece of the network would use the same resources available to them.
In our journey to the Big Data, we learnt that how Big Data can utilize 5G networks for its usage and what are the basic factors that are enabling this interaction. With Big Data and networking combined, there will be a revolution in the world of information exchanging and we would efficiently utilize the resources to get the maximum output.
(This article was authored by Research Nest’s Technical Writer Zeeshan Mushtaq)
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