Dear Maysam,

I would not consider IoT and Big Data as two distinct disciplines. From my point of view, to a certain extent, IoT is part of what could be considered as "Big Data". Not only because the data generated from the aforementioned sensors can be big in terms of size (volume), but also because they might generate different data at different level of granularity (variety).

To answer your questions, yes you can indeed simulate IoT data. Depending on what exactly you would like to simulate, you might need different kind of techniques. In some cases, you can build a model using standard data mining techniques (leveraging distributed computation if the data is really huge). However, if the goal is to simulate data that consider the full end-to-end interconnection of the objects you might need different techniques to simulate the data. For instance, if you want --using the simulated data-- monitor a user across multiple sensors (e.g., "action A" on "sensor1", "action B" on "sensor2", "Action C" on "sensor1") one solution could be to use process mining techniques to build a business process model that can in turn be used to generate simulated data.

Here is an interesting article introducing IoT, process mining, and data mining: http://wwwis.win.tue.nl/~wvdaalst/old/publications/p769.pdf

Hope it helps.

Gaël

Big data and analysis in the center of modern science and business. These data are generated from online transactions, emails, videos, sounds, clicks, logs and posts, search queries, correct notes, social networking interactions, scientific data, sensors and mobile phones, and their applications. They are stored on large-scale biosphere databases, and it's difficult to capture, shape, store, manage, share, analyze, and display them through a variety of database software tools. Five exabytes (10 bytes 18 bytes) of data have been created by humans by 2003. Today, this amount of information is generated in two days. In 2012, digital data was upgraded to 2.72 bytes (10 bytes to 21 bytes). It is expected to double this amount every two years to about 8 za bytes in 2015.

IBM showed that 2.5 exabytes of data are generated each day, and 90% of the data was generated in the last two years. A personal computer holds up to 500 GB (10 bytes 9 bytes) of data, so it needs around 20 billion PCs to store all of the world's data. In the past, the process of manifesting human genes was about 10 years old, now it's not over a week. Multimedia data has a massive weight in Internet traffic and is expected to increase to 70% in 2013. Just google has more than one million servers around the world. There are 6 billion mobile subscriptions in the world and 10 billion text messages are sent every day. By 2020, 50 billion devices will be connected to networks and the Internet.

In 2012, human exposure was carried out with big data as a global project with a centralized, real-time collection that displays and analyzes a large amount of data. Based on this project, many statistics were taken. Facebook has ninety-ninety-five million active accounts per month in 70 languages, 140 billion images uploaded, 125 billion friend connections, and 30 billion pieces of content per day, and 2.7 billion likes and comments. Every 48 hours of video is uploaded every day, and 4 billion views are played on YouTube every day. Google supports many services, which monitors 7.2 billion pages every day, and translates data into 20 languages ​​(up to 15 bytes per day) in 66 languages ​​every day. One Billion Tweet every 72 hours from more than 140 million active Twitter users. 571 new website is created every minute. About a decade later, the number of information will increase by 50 times, but the number of IT professionals who control all of this information will increase 1.5 times. Part 1 presents the basic implications, benefits, challenges, results, examples, methods and Knowledge discovery is provided from big data, and in Section 2, important implications for security implications are reviewed, and Part 3 provides benefits, actual barriers, challenges and barriers to big data, and Part 4 includes work.

What is Big Data?

1.BIG DATA

Here, important implications are reviewed and described in various sections.

1-1. Important messages

Big Data requires a forward turning step from a traditional data analysis that is described with its three main components: variety, volume, velocity.

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https://www.simplilearn.com/how-big-data-powering-internet-of-things-iot-revolution-article

How Big Data is Powering the Internet of Things (IoT) Revolution

Big data and the Internet of Things: Two sides of the same coin?

https://www.sas.com/en_us/insights/articles/big-data/big-data-and-iot-two-sides-of-the-same-coin.html

thank you Azedine Boulmakoul ?