Container Live Migration for Latency Critical Industrial Applications on Edge Computing

A new level of factory automation demands processing vast amounts of data, complex orchestration of cyber-physical systems, and coordination of computation as well as communication resources in real-time. Virtualization and decentralized computation is becoming a de-facto solution for factory automation. Edge Computing (EC) is a promising approach to achieve the low latencies required by many industrial systems. It employs resource rich edge servers distributed within a factory that are placed close to end devices and assist them in executing computation intensive tasks and also in coordinating with each other. This paper discusses the requirements and challenges of EC for factory automation applications. In a distributed EC infrastructure, safe and timely operation of industrial applications require load balancing and mobility support and thus a seamless service migration between the edge servers. With the recent advances in virtualization and due to its advantages, virtual machine (VM) and container technologies are pavings its way into factory. Though containers have some distinctive advantages over VMs in EC, the service live migration has comparatively high downtime. This paper proposes a novel live migration scheme called redundancy migration that reduces the downtime by a factor of 1.8 compared to the stock migration in linux containers.

[1]  Samuel T. King,et al.  ReVirt: enabling intrusion analysis through virtual-machine logging and replay , 2002, OPSR.

[2]  Henrik Klessig,et al.  Requirements and current solutions of wireless communication in industrial automation , 2014, 2014 IEEE International Conference on Communications Workshops (ICC).

[3]  Didier Stricker,et al.  Remote execution vs. simplification for mobile real-time computer vision , 2014, 2014 International Conference on Computer Vision Theory and Applications (VISAPP).

[4]  Meenu Chawla,et al.  A three phase optimization method for precopy based VM live migration , 2016, SpringerPlus.

[5]  Jay Lee,et al.  A Cyber-Physical Systems architecture for Industry 4.0-based manufacturing systems , 2015 .

[6]  Volker Paelke,et al.  Augmented reality in the smart factory: Supporting workers in an industry 4.0. environment , 2014, Proceedings of the 2014 IEEE Emerging Technology and Factory Automation (ETFA).

[7]  Ákos Kovács,et al.  Comparison of different Linux containers , 2017, 2017 40th International Conference on Telecommunications and Signal Processing (TSP).

[8]  Michael I. Hill,et al.  Generalizeability of Latency Detection in a Variety of Virtual Environments , 2004 .

[9]  Peter Neumann,et al.  Industrial Communication Protocols , 2009, Handbook of Automation.

[10]  Tucker R. Balch,et al.  Distributed sensor fusion for object position estimation by multi-robot systems , 2001, Proceedings 2001 ICRA. IEEE International Conference on Robotics and Automation (Cat. No.01CH37164).

[11]  Alexander Verl,et al.  Cooperation of human and machines in assembly lines , 2009 .

[12]  Hosny A. Abbas.  Future SCADA challenges and the promising solution: the agent-based SCADA , 2014, Int. J. Crit. Infrastructures.

[13]  Aaron F. Bobick,et al.  Probabilistic human action prediction and wait-sensitive planning for responsive human-robot collaboration , 2013, 2013 13th IEEE-RAS International Conference on Humanoid Robots (Humanoids).

[14]  Claudia Linnhoff-Popien,et al.  ME-VoLTE: Network functions for energy-efficient video transcoding at the mobile edge , 2015, 2015 18th International Conference on Intelligence in Next Generation Networks.

[15]  Keith A. Lantz,et al.  Preemptable remote execution facilities for the V-system , 1985, SOSP 1985.

[16]  Binoy Ravindran,et al.  Lightweight Live Migration for High Availability Cluster Service , 2010, SSS.

[17]  Miika Komu,et al.  Hypervisors vs. Lightweight Virtualization: A Performance Comparison , 2015, 2015 IEEE International Conference on Cloud Engineering.

[18]  Bin Cheng,et al.  Real-time data reduction at the network edge of Internet-of-Things systems , 2015, 2015 11th International Conference on Network and Service Management (CNSM).

[19]  Roberto Morabito,et al.  Enabling Data Processing at the Network Edge through Lightweight Virtualization Technologies , 2016, 2016 IEEE International Conference on Sensing, Communication and Networking (SECON Workshops).

[20]  Heping Chen,et al.  Topological Indoor Localization and Navigation for Autonomous Mobile Robot , 2015, IEEE Transactions on Automation Science and Engineering.

[21]  Umesh Deshpande,et al.  Post-copy live migration of virtual machines , 2009, OPSR.

[22]  Andrew Warfield,et al.  Live migration of virtual machines , 2005, NSDI.

[23]  Malte Brettel,et al.  How Virtualization, Decentralization and Network Building Change the Manufacturing Landscape: An Industry 4.0 Perspective , 2014 .

[24]  Antonio Iera,et al.  Lightweight service replication for ultra-short latency applications in mobile edge networks , 2017, 2017 IEEE International Conference on Communications (ICC).

[25]  Jiang Wu,et al.  A Novel Hybrid-Copy Algorithm for Live Migration of Virtual Machine , 2017, Future Internet.

[26]  Hai Jin,et al.  Live migration of virtual machine based on full system trace and replay , 2009, HPDC '09.

[27]  Seng Wai Loke,et al.  Mobile cloud computing , 2015 .

[28]  Jay Lee,et al.  Industrial Big Data Analytics and Cyber-physical Systems for Future Maintenance & Service Innovation , 2015 .