IoT Service Slicing and Task Offloading for Edge Computing

With the advancement of IoT technology, various domains such as smart factories, smart cities and smart cars use the IoT to provide value-added services. In addition, technologies such as MEC and network slicing provide another opportunity for the IoT to support more advanced and real-time services that could not have been previously supported. However, the simple integration of such technologies into the IoT does not take full advantage of MEC and network slicing or the reduction of latency and traffic prioritization, respectively. Therefore, there is a strong need for an efficient integration mechanism for IoT platforms to maximize the benefit of using such technologies. In this article, we introduce a novel architectural framework that enables the virtualization of an IoT platform with minimum functions to support specific IoT services and host the instance in an edge node, close to the end-user. As the instance provides its service at the edge node where the MEC node and network slice are located, the traffic for the end-user does not need to traverse back to the cloud. This architecture guarantees not only low latency but also efficient management of IoT services at the edge node. To show the feasibility of the proposed architecture, we conduct an experimental evaluation by comparing the transmission time of both IoT services running on the central cloud and those using sliced IoT functions in the edge gateway. The results show that the proposed architecture provides two times faster transmission time than that from the conventional cloud-based IoT platform.

[1]  Alexandros Kaloxylos,et al.  A Survey and an Analysis of Network Slicing in 5G Networks , 2018, IEEE Communications Standards Magazine.

[2]  Nadir Shah,et al.  Orchestration of Microservices for IoT Using Docker and Edge Computing , 2018, IEEE Communications Magazine.

[3]  Björn Butzin,et al.  Microservices approach for the internet of things , 2016, 2016 IEEE 21st International Conference on Emerging Technologies and Factory Automation (ETFA).

[4]  Hui Yang,et al.  Distributed Blockchain-Based Trusted Multidomain Collaboration for Mobile Edge Computing in 5G and Beyond , 2020, IEEE Transactions on Industrial Informatics.

[5]  Steve Vinoski,et al.  Node.js: Using JavaScript to Build High-Performance Network Programs , 2010, IEEE Internet Comput..

[6]  Nuno M. Garcia,et al.  Internet of Things Architectures, Technologies, Applications, Challenges, and Future Directions for Enhanced Living Environments and Healthcare Systems: A Review , 2019, Electronics.

[7]  Lewis Nkenyereye,et al.  Towards a Blockchain-enabled IoT Platform using oneM2M Standards , 2018, 2018 International Conference on Information and Communication Technology Convergence (ICTC).

[8]  Erik Blasch,et al.  Enabling Smart Urban Surveillance at The Edge , 2017, 2017 IEEE International Conference on Smart Cloud (SmartCloud).

[9]  JaeHo Kim,et al.  Interworking Models of Smart City with Heterogeneous Internet of Things Standards , 2019, IEEE Communications Magazine.

[10]  Michael Le,et al.  Container and Microservice Driven Design for Cloud Infrastructure DevOps , 2016, 2016 IEEE International Conference on Cloud Engineering (IC2E).

[11]  Jiajia Liu,et al.  Toward Intelligent Task Offloading at the Edge , 2020, IEEE Network.

[12]  Bengt Ahlgren,et al.  Internet of Things for Smart Cities: Interoperability and Open Data , 2016, IEEE Internet Computing.

[13]  Michael Devetsikiotis,et al.  Blockchains and Smart Contracts for the Internet of Things , 2016, IEEE Access.

[14]  F. Richard Yu,et al.  Integrated Blockchain and Edge Computing Systems: A Survey, Some Research Issues and Challenges , 2019, IEEE Communications Surveys & Tutorials.

[15]  Bing Chen,et al.  Data Security and Privacy-Preserving in Edge Computing Paradigm: Survey and Open Issues , 2018, IEEE Access.

[16]  Andreas Kunz,et al.  Interworking architecture between oneM2M service layer and underlying networks , 2014, 2014 IEEE Globecom Workshops (GC Wkshps).

[17]  Yanlin Yue,et al.  AI-Enhanced Offloading in Edge Computing: When Machine Learning Meets Industrial IoT , 2019, IEEE Network.

[18]  Mohsen Guizani,et al.  Internet of Things: A Survey on Enabling Technologies, Protocols, and Applications , 2015, IEEE Communications Surveys & Tutorials.

[19]  Andreas Kunz,et al.  Mobile edge computing with network resource slicing for Internet-of-Things , 2018, 2018 IEEE 4th World Forum on Internet of Things (WF-IoT).

[20]  Cao Guizhen,et al.  JMeter-based aging simulation of computing system , 2010, 2010 International Conference on Computer, Mechatronics, Control and Electronic Engineering.

[21]  Christian Tipantuña,et al.  Network functions virtualization: An overview and open-source projects , 2017, 2017 IEEE Second Ecuador Technical Chapters Meeting (ETCM).

[22]  Alexander Gluhak,et al.  A survey on facilities for experimental internet of things research , 2011, IEEE Communications Magazine.

[23]  Lizhi Wang,et al.  A OneM2M-Compliant Stacked Middleware Promoting IoT Research and Development , 2018, IEEE Access.

[24]  Iván Vidal,et al.  Enabling the Orchestration of IoT Slices through Edge and Cloud Microservice Platforms , 2019, Sensors.

[25]  Tarik Taleb,et al.  Network Slice Mobility in Next Generation Mobile Systems: Challenges and Potential Solutions , 2020, IEEE Network.

[26]  Seungjoon Lee,et al.  Network function virtualization: Challenges and opportunities for innovations , 2015, IEEE Communications Magazine.

[27]  Jacques Bughin,et al.  The internet of things: mapping the value beyond the hype , 2015 .

[28]  Claus Pahl,et al.  Blockchain Based Service Continuity in Mobile Edge Computing , 2019, 2019 Sixth International Conference on Internet of Things: Systems, Management and Security (IOTSMS).

[29]  Andrew Hines,et al.  5G network slicing using SDN and NFV- A survey of taxonomy, architectures and future challenges , 2019, Comput. Networks.

[30]  Sneha A. Dalvi,et al.  Internet of Things for Smart Cities , 2017 .

[31]  Jihun Ha,et al.  Kubernetes Enhancement for 5G NFV Infrastructure , 2019, 2019 International Conference on Information and Communication Technology Convergence (ICTC).

[32]  Jose Ordonez-Lucena,et al.  Network Slicing for 5G with SDN/NFV: Concepts, Architectures, and Challenges , 2017, IEEE Communications Magazine.

[33]  Wei Cao,et al.  Intelligent Offloading in Multi-Access Edge Computing: A State-of-the-Art Review and Framework , 2019, IEEE Communications Magazine.

[34]  Faqir Zarrar Yousaf,et al.  NFV and SDN—Key Technology Enablers for 5G Networks , 2017, IEEE Journal on Selected Areas in Communications.

[35]  Zhu Han,et al.  When Mobile Blockchain Meets Edge Computing , 2017, IEEE Communications Magazine.

[36]  Haining Wang,et al.  Network Management and Orchestration Using Artificial Intelligence: Overview of ETSI ENI , 2018, IEEE Communications Standards Magazine.

[37]  Antonio Brogi,et al.  DockerFinder: Multi-attribute Search of Docker Images , 2017, 2017 IEEE International Conference on Cloud Engineering (IC2E).

[38]  Tarik Taleb,et al.  On Multi-Access Edge Computing: A Survey of the Emerging 5G Network Edge Cloud Architecture and Orchestration , 2017, IEEE Communications Surveys & Tutorials.

[39]  Andreas Kunz,et al.  Connecting and Managing M2M Devices in the Future Internet , 2014, Mob. Networks Appl..

[40]  Joerg Swetina,et al.  Toward a standardized common M2M service layer platform: Introduction to oneM2M , 2014, IEEE Wireless Communications.

[41]  Dario Sabella,et al.  Mobile-Edge Computing Architecture: The role of MEC in the Internet of Things , 2016, IEEE Consumer Electronics Magazine.

[42]  Geyong Min,et al.  Computation Offloading in Multi-Access Edge Computing Using a Deep Sequential Model Based on Reinforcement Learning , 2019, IEEE Communications Magazine.

[43]  Rodrigo Roman,et al.  On the features and challenges of security and privacy in distributed internet of things , 2013, Comput. Networks.