A Blockchain-Based Decentralized Composition Solution for IoT Services

Diversified Internet of Things services are becoming more complex and strictly user-defined. Traditional cloud solutions proved to be both costly in terms of resources and time efficiency. To overcome such a burden, researchers developed fog solutions for faster service responsiveness. Fog-to-Fog communication and cooperation was then introduced to compose services on-the-go for user-specific requests with the aid of mobile edge devices. This paper introduces a blockchain-based decentralized service composition solution for complex multimedia service delivery to cloud subscribers. The proposed work dynamically creates user-defined services without requiring any intermediary service or network provider entities to authenticate and deliver composite services. The composition process uses a reinforcement learning technique to construct secure and reliable composition paths. Participants are rewarded by cloud and fog entities for solving complex composition processes. Simulation results conducted on the system show that by adapting the proposed technique, fog and cloud entities require less resources and reduced power usage with increased service delivery success rates to cloud subscribers.

[1]  Elmar Gerhards-Padilla,et al.  BonnMotion: a mobility scenario generation and analysis tool , 2010, SimuTools.

[2]  Ahmed Karmouch,et al.  A QoS Monitor Selection Mechanism for Cellular Data Networks , 2014, 2015 IEEE Global Communications Conference (GLOBECOM).

[3]  Sherali Zeadally,et al.  Fog Computing Architecture, Evaluation, and Future Research Directions , 2018, IEEE Communications Magazine.

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

[5]  Hong Ji,et al.  A D2D-Assisted MEC Computation Offloading in the Blockchain-Based Framework for UDNs , 2019, ICC 2019 - 2019 IEEE International Conference on Communications (ICC).

[6]  Azzedine Boukerche,et al.  Comparing Fog Solutions for Energy Efficiency in Wireless Networks: Challenges and Opportunities , 2019, IEEE Wireless Communications.

[7]  Young-Sik Jeong,et al.  SoftEdgeNet: SDN Based Energy-Efficient Distributed Network Architecture for Edge Computing , 2018, IEEE Communications Magazine.

[8]  Thar Baker,et al.  A Profitable and Energy-Efficient Cooperative Fog Solution for IoT Services , 2020, IEEE Transactions on Industrial Informatics.

[9]  Ismaeel Al Ridhawi,et al.  Minimizing delay in IoT systems through collaborative fog-to-fog (F2F) communication , 2017, 2017 Ninth International Conference on Ubiquitous and Future Networks (ICUFN).

[10]  Lei Zhang,et al.  An IoT Unified Access Platform for Heterogeneity Sensing Devices Based on Edge Computing , 2019, IEEE Access.

[11]  Victor C. M. Leung,et al.  Distributed Resource Allocation in Blockchain-Based Video Streaming Systems With Mobile Edge Computing , 2019, IEEE Transactions on Wireless Communications.

[12]  Thar Baker,et al.  Providing secure and reliable communication for next generation networks in smart cities , 2020, Sustainable Cities and Society.

[13]  Yaser Jararweh,et al.  Data and Service Management in Densely Crowded Environments: Challenges, Opportunities, and Recent Developments , 2019, IEEE Communications Magazine.

[14]  Ahmed Karmouch,et al.  Ontology-based negotiation protocol and context-level agreements , 2008 .

[15]  Yousif Al Ridhawi,et al.  Dynamic Composition of Service Specific Overlay Networks , 2013 .

[16]  S. Krause,et al.  OverSim: A Flexible Overlay Network Simulation Framework , 2007, 2007 IEEE Global Internet Symposium.

[17]  Lewis Tseng,et al.  Blockchain for Managing Heterogeneous Internet of Things: A Perspective Architecture , 2020, IEEE Network.