Exploring the Complexities of Big Data in IoT and Cloud Platforms

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Big Data challenges in IOT and Cloud

Problems and challenges
The problem encountered by big data in IoT platforms is huge because the data generated by IoT is
huge. The data generated comes from various sources and there are very few chances that the data will
be structured therefore to handle that data which is incomplete, coming from different sources, is
heterogeneous in nature and present in huge volumes, is very difficult. The two main challenged here
arises due to data mining process in Big data which is used to derive insights from the data for better
business practices but when the data is incomplete and heterogeneous, it is very difficult for the data
mining algorithms to extract and draw insights. For example, an IOT system comprises of cameras,
sensors and social media, the data generated by these will be different in nature hence the data mining
algorithms will find it difficult to integrate the data. Big data has to be modified according to the IOT
environment so that integration of data can become possible which is a huge challenge. Another
problem lies because of the security issues involved in sharing the data between various applications.
The information mined using the data mining techniques can be sensitive and possess the risk of
security (Chen, Deng, Wan, Zhang, Vasilakos & Rong, 2015).
The big data challenges in the cloud environment are due to the large volumes of data generated. The
data produces has to be uploaded to the cloud or the data needs to be retrieved from the cloud in order
to analyze it which can lead to a problem. The data while moving in and out from cloud needs to be
secured from attacks because the data might contain the sensitive information such as credit card
details, passwords, etc. therefore moving the large volumes of sensitive over the internet in case of slow
network speed can be dangerous too. The data might be attacked by the outsides and can be changed
before it even reaches the destination. Ransomware attacks, phishing attacks and denial of distributed
services attacks are going to be a challenge to the companies incorporating big data and cloud. Big data
is responsible for the movement, storing and sharing of the data as smoothly and safely as possible
(Buyya, Ramamohanarao, Leckie, Calheiros, Dastjerdi & Versteeg, 2015)
The structure of the report is as follows, the first section contains the abstract of the report, introduction,
problem statement found in the topic selected which is big data challenges in IOT and cloud. The second
section contains the literature review to analyze the problem statement and its modification if necessary.
Also, the solution to the problem identified is found. This section contains the description of techniques
that were used in the past and the technologies found in the present era in the big data field. The third
section contains the problem and challenges found in the big data domain. Another section contains the
conclusion to the report. The references to support the information stated in the report is present in the
last section of the report.

References
Chen, F., Deng, P., Wan, J., Zhang, D., Vasilakos, A. V., & Rong, X. (2015). Data mining for the internet
of things: literature review and challenges. International Journal of Distributed Sensor Networks,11(8),
431047.
Buyya, R., Ramamohanarao, K., Leckie, C., Calheiros, R. N., Dastjerdi, A. V., & Versteeg, S. (2015,
December). Big data analytics-enhanced cloud computing: Challenges, architectural elements, and future
directions. In 2015 IEEE 21st International Conference on Parallel and Distributed Systems
(ICPADS) (pp. 75-84). IEEE.