Context-Aware Placement of Industry 4.0 Applications in Fog Computing Environments

The fourth industrial revolution, widely known as Industry 4.0, is realizable through widespread deployment of Internet of Things (IoT) devices across the industrial ambiance. Due to communication latency and geographical distribution, Cloud-centric IoT models often fail to satisfy the Quality of Service requirements of different IoT applications assisting Industry 4.0 in real time. Therefore, Fog computing focuses on harnessing edge resources to place and execute these applications in the proximity of data sources. Since most of the Fog nodes are heterogeneous, distributed, and resource-constrained, it is challenging to place Industry 4.0-oriented applications (I4OAs) over them ensuring time-optimized service delivery. Diversified data sensing frequency of different industrial IoT devices and their data size further intensify the application placement problem. To address this issue, in this article we propose a context-aware application placement policy for Fog environments. Our policy coordinates the IoT device-level contexts with the capacity of Fog nodes and minimizes the service delivery time of various I4OAs such as image processing and robot navigation applications. It also ensures that the streams of input data flowing toward the placed applications neither congest the network nor increase the computing overhead of host Fog nodes significantly. Performance of the proposed policy is evaluated in both real-world and simulated Fog environments and compared with the existing placement policies. The experiment results show that our policy offers overall 16% improvement in service latency, network relaxation, and computing overhead management compared to other placement policies.

[1]  Sherali Zeadally,et al.  Deploying Fog Computing in Industrial Internet of Things and Industry 4.0 , 2018, IEEE Transactions on Industrial Informatics.

[2]  Hans-Georg Kemper,et al.  Application-Pull and Technology-Push as Driving Forces for the Fourth Industrial Revolution , 2014 .

[3]  Shun-ichi Azuma,et al.  Secure Real-Time Control Through Fog Computation , 2019, IEEE Transactions on Industrial Informatics.

[4]  Neeraj Kumar,et al.  Fog computing for Healthcare 4.0 environment: Opportunities and challenges , 2018, Comput. Electr. Eng..

[5]  Rajkumar Buyya,et al.  FogBus: A Blockchain-based Lightweight Framework for Edge and Fog Computing , 2018, J. Syst. Softw..

[6]  Lei Shu,et al.  Smart Factory of Industry 4.0: Key Technologies, Application Case, and Challenges , 2018, IEEE Access.

[7]  Jiong Jin,et al.  Multi-objective resource allocation for Edge Cloud based robotic workflow in smart factory , 2019, Future Gener. Comput. Syst..

[8]  Rajkumar Buyya,et al.  Modelling and Simulation of Fog and Edge Computing Environments using iFogSim Toolkit , 2018, ArXiv.

[9]  Eiji Kamioka,et al.  CFC-ITS: Context-Aware Fog Computing for Intelligent Transportation Systems , 2018, IT Professional.

[10]  Kyunghan Lee,et al.  CAS: Context-Aware Background Application Scheduling in Interactive Mobile Systems , 2017, IEEE Journal on Selected Areas in Communications.

[11]  Tobias Achterberg,et al.  SCIP: solving constraint integer programs , 2009, Math. Program. Comput..

[12]  Mauro Conti,et al.  Software defined service function chaining with failure consideration for fog computing , 2018, Concurr. Comput. Pract. Exp..

[13]  Chun-Cheng Lin,et al.  Cost-Efficient Deployment of Fog Computing Systems at Logistics Centers in Industry 4.0 , 2018, IEEE Transactions on Industrial Informatics.

[14]  Anne E. James,et al.  Modeling industry 4.0 based fog computing environments for application analysis and deployment , 2019, Future Gener. Comput. Syst..

[15]  Mohammad S. Obaidat,et al.  Edge Computing-Based Security Framework for Big Data Analytics in VANETs , 2019, IEEE Network.

[16]  Rajkumar Buyya,et al.  Latency-Aware Application Module Management for Fog Computing Environments , 2018, ACM Trans. Internet Techn..

[17]  Rajkumar Buyya,et al.  Quality of Experience (QoE)-aware placement of applications in Fog computing environments , 2019, J. Parallel Distributed Comput..

[18]  Sujata Banerjee,et al.  Granular Computing and Network Intensive Applications: Friends or Foes? , 2017, HotNets.

[19]  Christian Wietfeld,et al.  Payload-Size and Deadline-Aware scheduling for time-critical Cyber Physical Systems , 2017, 2017 Wireless Days.

[20]  Zhenyu Zhou,et al.  A Distributed and Context-Aware Task Assignment Mechanism for Collaborative Mobile Edge Computing , 2018, Sensors.

[21]  Hong Liu,et al.  An Attribute Credential Based Public Key Scheme for Fog Computing in Digital Manufacturing , 2019, IEEE Transactions on Industrial Informatics.

[22]  Jiong Jin,et al.  Context-Aware Privacy Preservation in a Hierarchical Fog Computing System , 2019, ICC 2019 - 2019 IEEE International Conference on Communications (ICC).

[23]  Lyes Khoukhi,et al.  Industrial IoT Data Scheduling Based on Hierarchical Fog Computing: A Key for Enabling Smart Factory , 2018, IEEE Transactions on Industrial Informatics.

[24]  Jiafu Wan,et al.  Fog Computing for Energy-Aware Load Balancing and Scheduling in Smart Factory , 2018, IEEE Transactions on Industrial Informatics.

[25]  Dilawaer Duolikun,et al.  Energy-Efficient Recovery Algorithm in the Fault-Tolerant Tree-Based Fog Computing (FTBFC) Model , 2019, AINA.

[26]  Mirjana Ivanovic,et al.  Context Aware Resource and Service Provisioning Management in Fog Computing Systems , 2017, IDC.

[27]  Waqar Mahmood,et al.  Energy efficient context aware traffic scheduling for IoT applications , 2017, Ad Hoc Networks.

[28]  Debashis De,et al.  Internet of Things (IoT) for Smart Precision Agriculture and Farming in Rural Areas , 2018, IEEE Internet of Things Journal.

[29]  Agya Mishra,et al.  Color Image Enhancement Techniques: A Critical Review , 2012 .

[30]  Song Han,et al.  Industrial Internet of Things: Challenges, Opportunities, and Directions , 2018, IEEE Transactions on Industrial Informatics.

[31]  Philip Moore,et al.  FOG Computing and Low Latency Context-Aware Health Monitoring in Smart Interconnected Environments , 2018, EIDWT.