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The IUP Journal of Information Technology
FogBDA: Incorporating Data Analytics in Fog Layer for Real-Time Applications†
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Despite the expansive utilization of Fog computing, most of the real-time applications and quality services have not still benefitted from this computing paradigm due to cohesive problem of latency, location-awareness and lack of mobility support and awareness about the device condition. As a result, FogBDA has emerged as an encouraging platform to provide flexible resources at the edge of network. The paper discusses the current paradigm of Fog computing and proposes an extensive architecture. It also analyzes the designing goals and challenges in the FogBDA platform and presents the platform design with several illustrative applications. Further, a simulation model is illustrated in order to measure the efficacy of the proposed model. The simulated results depict the decreased response time and cost as compared to cloud.

 
 

While cloud-based technologies are full-proof platform for the Internet of Things (IoT), but most of the IoT services cannot take efficient advantage of it. Enterprise IoT solutions demand low decision time, immediate processing and low response time. Standard institutions cannot afford the delay caused by the round-trip time between the end layers and cloud-based platforms. The solution demands persistent movement of dataset with lower response time. For example, if a chemical plant is totally based on the cloud-based IoT platform, then it may be too late before the IoT-based platform shuts down the plant after detecting a bizarre combination of temperature and pressure thresholds value. Instead, the anomaly should be detected nearby within milliseconds, followed by an immediate action trigged by a protocol. Following all these requires building a quick responsive system, and hence a new concept came into picture, i.e., Fog computing, coined by Bonomi et al. (2012), which has the potential to solve the problem of the cloud-based IoT platforms by simply modifying the existing architecture. One of the main reasons behind the gained momentum of IoT in the recent past is the rise of fog-based computing paradigm. Although the concept of M2M has existed for a long time, institutions never think of the rich and valuable data derived from the datasets pattern generated by sensors and different smart devices. Existing architectural-based infrastructure was not just ready to tackle the huge scale resource demanded by the connected devices paradigm. Hence fog computing has become a priceless resource for organizations.

 
 

Information Technology Journal, Fog computing, FogBDA, Internet of Things(IoT), Big data