Integration challenges of Artificial Intelligence in Cloud Computing, Internet of Things and Software-defined networking

Artificial Intelligence is playing a pivot role in all the significant areas of technology. The nature-inspired capabilities of artificial intelligence are taking the enterprises into a new environment, which is more efficient, strategic, and insight-driven. Different technologies like cloud, Internet of Things (IoT) and Software-defined networking, have their benefits providing to the community. The integration of all these technologies with artificial intelligence are taking beneficiaries to the next level of performance. However, the fusion of these technologies is perturbed and has put forth many challenges for the researchers to address. This paper explains the challenges and opportunities faced in integrating these technologies for all the communities.

[1]  Muhammad Alam,et al.  Cloud Service ranking using Checkpoint based Load balancing in real time scheduling of Cloud Computing , 2019, ArXiv.

[2]  Shahaboddin Shamshirband,et al.  The Rise of Internet of Things (IoT) in Big Healthcare Data: Review and Open research Issues , 2019, ArXiv.

[3]  Eui-Nam Huh,et al.  Fog Computing: The Cloud-IoT\/IoE Middleware Paradigm , 2016, IEEE Potentials.

[4]  Rajkumar Buyya,et al.  Next generation cloud computing: New trends and research directions , 2017, Future Gener. Comput. Syst..

[5]  Stanislav Lange,et al.  Heuristic Approaches to the Controller Placement Problem in Large Scale SDN Networks , 2015, IEEE Transactions on Network and Service Management.

[6]  Zhou Shijie,et al.  Data Transmission Using IoT in Vehicular Ad-Hoc Networks in Smart City Congestion , 2019, Mob. Networks Appl..

[7]  Zainab AlMeraj,et al.  Challenges of IoT Based Smart-Government Development , 2018, 2018 IEEE Green Technologies Conference (GreenTech).

[8]  Michael J. Kavis,et al.  Architecting the Cloud: Design Decisions for Cloud Computing Service Models (Saas, Paas, and Iaas) , 2014 .

[9]  P. Schulte,et al.  FinTech Is Merging with IoT and AI to Challenge Banks: How Entrenched Interests Can Prepare , 2017 .

[10]  Mauro Conti,et al.  CENSOR: Cloud‐enabled secure IoT architecture over SDN paradigm , 2018, Concurr. Comput. Pract. Exp..

[11]  Young-Sik Jeong,et al.  DistBlockNet: A Distributed Blockchains-Based Secure SDN Architecture for IoT Networks , 2017, IEEE Communications Magazine.

[12]  Nei Kato,et al.  An Intelligent Traffic Load Prediction-Based Adaptive Channel Assignment Algorithm in SDN-IoT: A Deep Learning Approach , 2018, IEEE Internet of Things Journal.

[13]  Dirk Schaefer,et al.  Software-defined cloud manufacturing for industry 4.0 , 2016 .

[14]  Liang Xiao,et al.  IoT Security Techniques Based on Machine Learning: How Do IoT Devices Use AI to Enhance Security? , 2018, IEEE Signal Processing Magazine.

[15]  Ai-Chun Pang,et al.  Flow-Aware Routing and Forwarding for SDN Scalability in Wireless Data Centers , 2018, IEEE Transactions on Network and Service Management.

[16]  Mazin Yousif Intelligence in the Cloud - We Need a Lot of it , 2017, IEEE Cloud Comput..

[17]  Kostas E. Psannis,et al.  Secure integration of IoT and Cloud Computing , 2018, Future Gener. Comput. Syst..

[18]  Mahdi H. Miraz,et al.  Internet of Nano-Things, Things and Everything: Future Growth Trends , 2018, Future Internet.

[19]  PRADIP KUMAR SHARMA,et al.  A Software Defined Fog Node Based Distributed Blockchain Cloud Architecture for IoT , 2018, IEEE Access.

[20]  Nalini Venkatasubramanian,et al.  Ride: A Resilient IoT Data Exchange Middleware Leveraging SDN and Edge Cloud Resources , 2018, 2018 IEEE/ACM Third International Conference on Internet-of-Things Design and Implementation (IoTDI).

[21]  Mounir Ghogho,et al.  Deep Recurrent Neural Network for Intrusion Detection in SDN-based Networks , 2018, 2018 4th IEEE Conference on Network Softwarization and Workshops (NetSoft).