Addressing the Future Data Management Challenges in IoT: A Proposed Framework
Journal Title: International Journal of Advanced Computer Science & Applications - Year 2017, Vol 8, Issue 5
Abstract
Internet of Thing (IoT) has been attracting the interest of researchers in recent years. Traditionally, only handful types of devices had the capability to be connected to internet/intranet, but due to the latest developments in RFID, NFC, smart sensors and communication protocols billions of heterogeneous devices are being connected each year. From smart phones uploading the data regarding location and fitness to smart grids uploading the data regarding energy consumption and distribution, these devices are generating a huge amount of data each passing moment. This research paper proposes a data management framework to securely manage the huge amount of data that is being generated by IoT enabled devices. The proposed framework is divided into nine layers. The framework incorporates layers such as data collection layer, fog computing layer, integrity management layer, security layer, data aggregation layer, data analysis layer, data storage layer, application layer and archiving layer. The security layer has been proposed as a background layer because all layers shall ensure the privacy and security of the data. These layers will help in managing the data from the point where it is generated by an IoT enabled device until the point where the data is archived at the data center.
Authors and Affiliations
Mohammad Asad Abbasi, Zulfiqar A. Memon, Tahir Q. Syed, Jamshed Memon, Rabah Alshboul
Keywords
Related Articles
- EP ID EP258759
- DOI 10.14569/IJACSA.2017.080525
- Views 75
- Downloads 0
A Computationally Efficient P-LRU based Optimal Cache Heap Object Replacement Policy
The recent advancement in the field of distributed computing depicts a need of developing highly associative and less expensive cache memories for the state-of-art processors i.e., Intel Core i6, i7, etc. Hence, various...
Image Blocks Model for Improving Accuracy in Identification Systems of Wood Type
Image-based recognition systems commonly use an extracted image from the target object using texture analysis. However, some of the proposed and implemented recognitionues systems of wood types up to this time have not b...
An Enhanced MPLS-TE For Transferring Multimedia packets
Multi-Protocol Label Switching is useful in managing multimedia traffic when some links are too congested; MPLS Traffic Engineering is a growing implementation in today's service provider networks. In This paper we propo...
WordNet based Implicit Aspect Sentiment Analysis for Crime Identification from Twitter
Crime analysis has become an interesting field that deals with serious public safety issues recognized around the world. Today, investigating Twitter Sentiment Analysis (SA) is a continuing concern within this field. Asp...
Analysis of Significant Factors for Dengue Infection Prognosis Using the Random Forest Classifier
Random forests have emerged as a versatile and highly accurate classification and regression methodology, requiring little tuning and providing interpretable outputs. Here, we briefly explore the possibility of applying...