Modeling cooperative behavior for resilience in cyber-physical systems using SDN and NFV

Cyber-Physical Systems (CPSs) are increasingly important in everyday applications including the latest mobile devices, power grids and intelligent buildings. CPS functionality has intrinsic characteristics including considerable heterogeneity, variable dynamics, and complexity of operation. These systems also typically have insufficient resources to satisfy their full demand for specialized services such as data edge storage, data fusion, and reasoning. These novel CPS characteristics require new management strategies to support the resilient global operation of CPSs. To reach this goal, we propose a Software Defined Networking based solution scaled out by Network Function Virtualization modules implemented as distributed management agents. Considering the obvious need for orchestrating the distributed agents towards the satisfaction of a common set of global CPS functional goals, we analyze distinct incentive strategies to enact a cooperative behavior among the agents. The repeated operation of each agent’s local algorithm allows that agent to learn how to adjust its behavior following both its own experience and observed behavior in neighboring agents. Therefore, global CPS management can evolve iteratively to ensure a state of predictable and resilient operation.

[1]  Ali Nauman,et al.  Smart Contract Privacy Protection Using AI in Cyber-Physical Systems: Tools, Techniques and Challenges , 2020, IEEE Access.

[2]  Lida Xu,et al.  Big data for cyber physical systems in industry 4.0: a survey , 2019, Enterp. Inf. Syst..

[3]  Nerea Toledo,et al.  Toward an SDN-enabled NFV architecture , 2015, IEEE Communications Magazine.

[4]  Jörg Ott,et al.  Consolidate IoT Edge Computing with Lightweight Virtualization , 2018, IEEE Network.

[5]  Attila Szolnoki,et al.  Statistical Physics of Human Cooperation , 2017, ArXiv.

[6]  David Hutchison,et al.  Architecture and design for resilient networked systems , 2018, Comput. Commun..

[7]  Jun Wu,et al.  Bandwidth Slicing in Software-Defined 5G: A Stackelberg Game Approach , 2018, IEEE Vehicular Technology Magazine.

[8]  Fan Wu,et al.  Sustainable Incentives for Mobile Crowdsensing: Auctions, Lotteries, and Trust and Reputation Systems , 2017, IEEE Communications Magazine.

[9]  Jianchao Zheng,et al.  QoE Driven Decentralized Spectrum Sharing in 5G Networks: Potential Game Approach , 2017, IEEE Transactions on Vehicular Technology.

[10]  N. Arunkumar,et al.  Enabling technologies for fog computing in healthcare IoT systems , 2019, Future Gener. Comput. Syst..

[11]  Qing Ding,et al.  A Public Goods Game Theory-Based Approach to Cooperation in VANETs Under a High Vehicle Density Condition , 2019, IEEE Transactions on Intelligent Transportation Systems.

[12]  Miao Pan,et al.  A Survey of Contract Theory-Based Incentive Mechanism Design in Wireless Networks , 2017, IEEE Wireless Communications.

[13]  Mohamed Faten Zhani,et al.  Research Challenges in Nextgen Service Orchestration , 2018, Future Gener. Comput. Syst..

[14]  Tao Yu,et al.  Nash Equilibrium-Based Asymptotic Stability Analysis of Multi-Group Asymmetric Evolutionary Games in Typical Scenario of Electricity Market , 2018, IEEE Access.

[15]  David Hutchison,et al.  QoS Filters: Addressing the Heterogeneity Gap , 1996, IDMS.

[16]  Tarik Taleb,et al.  A Survey on Emerging SDN and NFV Security Mechanisms for IoT Systems , 2019, IEEE Communications Surveys & Tutorials.

[17]  Fung Po Tso,et al.  Federated Service Chaining: Architecture and Challenges , 2020, IEEE Communications Magazine.

[18]  Chen-Ching Liu,et al.  Cyber security of a power grid: State-of-the-art , 2018, International Journal of Electrical Power & Energy Systems.

[19]  Jonathan Rodriguez,et al.  Robust Mobile Crowd Sensing: When Deep Learning Meets Edge Computing , 2018, IEEE Network.

[20]  Giancarlo Fortino,et al.  Task Offloading and Resource Allocation for Mobile Edge Computing by Deep Reinforcement Learning Based on SARSA , 2020, IEEE Access.

[21]  David Hutchison,et al.  Management patterns: SDN-enabled network resilience management , 2014, 2014 IEEE Network Operations and Management Symposium (NOMS).

[22]  Hongming Cai,et al.  Ubiquitous Data Accessing Method in IoT-Based Information System for Emergency Medical Services , 2014, IEEE Transactions on Industrial Informatics.

[23]  KleinbergRobert,et al.  Network Formation in the Presence of Contagious Risk , 2013 .

[24]  Mateusz P. Nowak,et al.  Smart SDN Management of Fog Services , 2020, 2020 Global Internet of Things Summit (GIoTS).

[25]  Abbas Jamalipour,et al.  An Evolutionary Game Theory-Based Approach to Cooperation in VANETs Under Different Network Conditions , 2015, IEEE Transactions on Vehicular Technology.

[26]  Guang Yang,et al.  Promoting Cooperation by the Social Incentive Mechanism in Mobile Crowdsensing , 2017, IEEE Communications Magazine.

[27]  Zibin Zheng,et al.  Blockchain for Internet of Things: A Survey , 2019, IEEE Internet of Things Journal.

[28]  Subhas Chandra Mukhopadhyay,et al.  Sensing Technologies for Monitoring Intelligent Buildings: A Review , 2018, IEEE Sensors Journal.

[29]  Navrati Saxena,et al.  Next Generation 5G Wireless Networks: A Comprehensive Survey , 2016, IEEE Communications Surveys & Tutorials.

[30]  Bradley R. Schmerl,et al.  Software Engineering for Smart Cyber-Physical Systems: Challenges and Promising Solutions , 2017, SOEN.

[31]  Christopher Edwards,et al.  Efficient access of mobile flows to heterogeneous networks under flash crowds , 2016, Comput. Networks.

[32]  David Hutchison,et al.  Assessing the impact of intra-cloud live migration on anomaly detection , 2014, 2014 IEEE 3rd International Conference on Cloud Networking (CloudNet).

[33]  Weisi Guo,et al.  A Survey of Online Data-Driven Proactive 5G Network Optimisation Using Machine Learning , 2020, IEEE Access.

[34]  Igor Linkov,et al.  Features of resilience , 2017, Environment Systems and Decisions.

[35]  David Hutchison,et al.  Game Theory for Multi-Access Edge Computing: Survey, Use Cases, and Future Trends , 2017, IEEE Communications Surveys & Tutorials.

[36]  Raquel Gómez-Chabla,et al.  IoT Applications in Agriculture: A Systematic Literature Review , 2018, ICT for Agriculture and Environment.

[37]  Paul Rimba,et al.  Data-Driven Cybersecurity Incident Prediction: A Survey , 2019, IEEE Communications Surveys & Tutorials.

[38]  David Hutchison,et al.  Resilient Cyber-Physical Systems:Using NFV Orchestration , 2020, 2003.12401.

[39]  Quanyan Zhu,et al.  Physical Intrusion Games—Optimizing Surveillance by Simulation and Game Theory , 2017, IEEE Access.

[40]  Liang Li,et al.  A Link-Based Variable Probability Learning Approach for Partially Overlapping Channels Assignment on Multi-Radio Multi-Channel Wireless Mesh Information-Centric IoT Networks , 2019, IEEE Access.

[41]  F. Richard Yu,et al.  A Survey of Machine Learning Techniques Applied to Software Defined Networking (SDN): Research Issues and Challenges , 2019, IEEE Communications Surveys & Tutorials.

[42]  Yousof Al-Hammadi,et al.  A Stackelberg game for street-centric QoS-OLSR protocol in urban Vehicular Ad Hoc Networks , 2018, Veh. Commun..

[43]  Qing-Long Han,et al.  A Survey on Model-Based Distributed Control and Filtering for Industrial Cyber-Physical Systems , 2019, IEEE Transactions on Industrial Informatics.

[44]  Zhu Han,et al.  A Hierarchical Game Approach for Visible Light Communication and D2D Heterogeneous Network , 2016, 2016 IEEE Global Communications Conference (GLOBECOM).

[45]  Xiaofeng Xu,et al.  Accurate Position Estimation of Mobile Robot Based on Cyber-Physical-Social Systems (CPSS) , 2020, IEEE Access.

[46]  Fernando A. Kuipers,et al.  SDN and Virtualization Solutions for the Internet of Things: A Survey , 2016, IEEE Access.

[47]  Éva Tardos,et al.  Network Formation in the Presence of Contagious Risk , 2011, TEAC.

[48]  Md. Arafatur Rahman,et al.  Smart Routing Management Framework Exploiting Dynamic Data Resources of Cross-Layer Design and Machine Learning Approaches for Mobile Cognitive Radio Networks: A Survey , 2020, IEEE Access.

[49]  David Hutchison,et al.  Network service orchestration standardization: A technology survey , 2017, Comput. Stand. Interfaces.

[50]  David Hutchison,et al.  A Scalable User Fairness Model for Adaptive Video Streaming Over SDN-Assisted Future Networks , 2016, IEEE Journal on Selected Areas in Communications.

[51]  Dusit Niyato,et al.  Distributed resource allocation in wireless networks under uncertainty and application of Bayesian game , 2011, IEEE Communications Magazine.

[52]  Shui Yu,et al.  A Dynamic Pricing Method for Carpooling Service Based on Coalitional Game Analysis , 2016, 2016 IEEE 18th International Conference on High Performance Computing and Communications; IEEE 14th International Conference on Smart City; IEEE 2nd International Conference on Data Science and Systems (HPCC/SmartCity/DSS).

[53]  Nikhil Kapade TLC: Trust Point Load Balancing Method using Coalitional Game Theory for message forwarding in VANET , 2014, 2014 IEEE Global Conference on Wireless Computing & Networking (GCWCN).

[54]  Jun Wu,et al.  NLES: A Novel Lifetime Extension Scheme for Safety-Critical Cyber-Physical Systems Using SDN and NFV , 2019, IEEE Internet of Things Journal.

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

[56]  Mohammad Hossein Anisi,et al.  Social networking-based cooperation mechanisms in vehicular ad-hoc network - a survey , 2017, Veh. Commun..

[57]  Long Chen,et al.  TARCO: Two-Stage Auction for D2D Relay Aided Computation Resource Allocation in HetNet , 2017, IEEE Transactions on Services Computing.

[58]  Liming Zhu,et al.  Analysis of Blockchain Solutions for IoT: A Systematic Literature Review , 2019, IEEE Access.

[59]  Victor C. M. Leung,et al.  Beh-Raft-Chain: A Behavior-Based Fast Blockchain Protocol for Complex Networks , 2020, IEEE Transactions on Network Science and Engineering.

[60]  Yueqi Liu,et al.  A Distributed Storage and Computation k-Nearest Neighbor Algorithm Based Cloud-Edge Computing for Cyber-Physical-Social Systems , 2020, IEEE Access.

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

[62]  Alagan Anpalagan,et al.  A game-theoretic perspective on self-organizing optimization for cognitive small cells , 2015, IEEE Communications Magazine.

[63]  Yoshiaki Tanaka,et al.  Optimal Pricing and Service Selection in the Mobile Cloud Architectures , 2019, IEEE Access.

[64]  Hui Liu,et al.  An Incentive Mechanism Combined With Anchoring Effect and Loss Aversion to Stimulate Data Offloading in IoT , 2019, IEEE Internet of Things Journal.

[65]  Sanjeev Khanna,et al.  Strategic Network Formation with Attack and Immunization , 2016, WINE.

[66]  Ofelia Begovich,et al.  IoT architecture for urban agronomy and precision applications , 2017, 2017 IEEE International Autumn Meeting on Power, Electronics and Computing (ROPEC).

[67]  Giancarlo Fortino,et al.  Trust and Reputation in the Internet of Things: State-of-the-Art and Research Challenges , 2020, IEEE Access.

[68]  Dionysia Kolokotsa,et al.  The role of smart grids in the building sector , 2016 .

[69]  Indrajit Banerjee,et al.  A robust forwarding node selection mechanism for efficient communication in urban VANETs , 2018, Veh. Commun..

[70]  Joachim Fabini,et al.  Resilience and Security: A Qualitative Survey of Urban Smart Grid Architectures , 2016, IEEE Access.

[71]  Luís Veiga,et al.  SD-CPS: Taming the challenges of Cyber-Physical Systems with a Software-Defined approach , 2017, 2017 Fourth International Conference on Software Defined Systems (SDS).

[72]  Karl Henrik Johansson,et al.  Cross-Layer Optimization for Industrial Control Applications Using Wireless Sensor and Actuator Mesh Networks , 2017, IEEE Transactions on Industrial Electronics.

[73]  Sanjeev Khanna,et al.  Network Formation under Random Attack and Probabilistic Spread , 2019, IJCAI.

[74]  Guillaume Fréchette,et al.  On the Determinants of Cooperation in Infinitely Repeated Games: A Survey , 2014 .