Research and Development of Delay-Sensitive Routing Tensor Model in IoT Core Networks

In the article, we present the research and development of an improved delay-sensitive routing tensor model for the core of the IoT network. The flow-based tensor model is considered within the coordinate system of interpolar paths and internal node pairs. The advantage of the presented model is the application for IoT architectures to ensure the Quality of Service under the parameters of bandwidth, average end-to-end delay, and the probability of packet loss. Hence, the technical task of delay-sensitive routing is formulated as the optimization problem together with constraints and conditions imposed on the corresponding routing variables. The system of optimality criteria is chosen for an investigation. Each selected criterion concerning the specifics of the demanded routing problem solution aims at the optimal use of available network resources and the improvement of QoS indicators, namely, average end-to-end delay. The analysis of the obtained routing solutions under different criteria is performed. Numerical research of the improved delay-sensitive routing tensor model allowed us to discover its features and proved the adequacy of the results for the multipath order of routing.

[1]  Oleksandr Lemeshko,et al.  Investigation of Load-Balancing Fast ReRouting Model with Providing Fair Priority-Based Traffic Policing , 2020 .

[2]  Sasu Tarkoma,et al.  Enhancing the Internet of Things with Knowledge-Driven Software-Defined Networking Technology: Future Perspectives , 2020, Sensors.

[3]  Jerome Henry,et al.  IoT Fundamentals: Networking Technologies, Protocols, and Use Cases for the Internet of Things , 2017 .

[4]  Y. H. Ku Diakoptics: The piecewise solution of large-scale systems: by Gabriel Kron. 166 pages, diagrams, 9 × 11 in. London, Macdonald & Co., Ltd., 1963. Price, 50s. (approx. $7.00) , 1965 .

[5]  Danilo P Mandic,et al.  Tensor Networks for Latent Variable Analysis: Novel Algorithms for Tensor Train Approximation , 2020, IEEE Transactions on Neural Networks and Learning Systems.

[6]  Yanghee Choi,et al.  A constrained multipath traffic engineering scheme for MPLS networks , 2002, 2002 IEEE International Conference on Communications. Conference Proceedings. ICC 2002 (Cat. No.02CH37333).

[7]  Pavel Segeč,et al.  Quality of Service Protection Scheme under Fast ReRoute and Traffic Policing Based on Tensor Model of Multiservice Network , 2019, 2019 International Conference on Information and Digital Technologies (IDT).

[8]  Yong Lu,et al.  Centralized QoS Routing Using Network Calculus for SDN-Based Streaming Media Networks , 2019, IEEE Access.

[9]  Jiannong Cao,et al.  Accurate Recovery of Internet Traffic Data: A Sequential Tensor Completion Approach , 2018, IEEE/ACM Transactions on Networking.

[10]  Murat Karakus,et al.  RoutingChain: A Proof-of-Concept Model for a Blockchain-Enabled QoS-Based Inter-AS Routing in SDN , 2020, 2020 IEEE International Black Sea Conference on Communications and Networking (BlackSeaCom).

[11]  Oleksandr Lemeshko,et al.  Tensor Multiflow Routing Model to Ensure the Guaranteed Quality of Service Based on Load Balancing in Network , 2020 .

[12]  I. Solovskaya,et al.  Tensor model of multiservice network with different classes of traffic service , 2013, 2013 12th International Conference on the Experience of Designing and Application of CAD Systems in Microelectronics (CADSM).

[13]  Olexandr V. Lemeshko,et al.  A tensor model of multipath routing based on multiple QoS metrics , 2013, 2013 International Siberian Conference on Control and Communications (SIBCON).

[14]  Walter Goralski,et al.  The Illustrated Network: How TCP/IP Works in a Modern Network , 2008 .

[15]  Oleksandra S. Yeremenko,et al.  QoS solution of traffic management based on the dynamic tensor model in the coordinate system of interpolar paths and internal node pairs , 2016, 2016 International Conference Radio Electronics & Info Communications (UkrMiCo).

[16]  Yeunwoong Kyung,et al.  QoS-Aware Flexible Handover Management in Software-Defined Mobile Networks , 2020, Applied Sciences.

[17]  Oleksandr Lemeshko,et al.  Research of optimization model of fault-tolerant routing with bilinear path protection criterion , 2017, 2017 2nd International Conference on Advanced Information and Communication Technologies (AICT).

[18]  Laurence T. Yang,et al.  A Tensor-Based Big-Data-Driven Routing Recommendation Approach for Heterogeneous Networks , 2019, IEEE Network.

[19]  Naixue Xiong,et al.  A Cross-Layer Optimized Opportunistic Routing Scheme for Loss-and-Delay Sensitive WSNs , 2018, Sensors.

[20]  Naixue Xiong,et al.  Differentiated Data Aggregation Routing Scheme for Energy Conserving and Delay Sensitive Wireless Sensor Networks , 2018, Sensors.

[21]  Qi Qi,et al.  Tensor-Based Reinforcement Learning for Network Routing , 2021, IEEE Journal of Selected Topics in Signal Processing.

[22]  Oleksandr Lemeshko,et al.  Development of the tensor model of multipath qоe-routing in an infocommunication network with providing the required quality rating , 2018 .

[23]  Oleksandr Lemeshko,et al.  Dynamic presentation of tensor model for multipath QoS-routing , 2016, 2016 13th International Conference on Modern Problems of Radio Engineering, Telecommunications and Computer Science (TCSET).

[24]  Haixia Xu,et al.  Deep Tensor Capsule Network , 2020, IEEE Access.

[25]  Oleksandra Yeremenko Development of the dynamic tensor model for traffic management in a telecommunication network with the support of different classes of service , 2016 .

[26]  Gabriel Kron,et al.  Tensor analysis of networks , 1967 .

[27]  Irina Strelkovskaya,et al.  Tensor decomposition in the structure optimization tasks of LTE/MVNO networks , 2014, 2014 IEEE International Black Sea Conference on Communications and Networking (BlackSeaCom).

[28]  Roman Orus,et al.  A Practical Introduction to Tensor Networks: Matrix Product States and Projected Entangled Pair States , 2013, 1306.2164.

[29]  Liu Chang,et al.  A Smart Collaborative Routing Protocol for Delay Sensitive Applications in Industrial IoT , 2020, IEEE Access.

[30]  Yu Wu,et al.  A Community Detecting Algorithm Based on Modular Tensor in Temporal Network , 2018, 2018 IEEE 16th Intl Conf on Dependable, Autonomic and Secure Computing, 16th Intl Conf on Pervasive Intelligence and Computing, 4th Intl Conf on Big Data Intelligence and Computing and Cyber Science and Technology Congress(DASC/PiCom/DataCom/CyberSciTech).

[31]  L. Javier García-Villalba,et al.  Key Technologies in the Context of Future Networks: Operational and Management Requirements , 2016, Future Internet.

[32]  Oleksandr Lemeshko,et al.  Diakoptical Method of Inter-area Routing with Load Balancing in a Telecommunication Network , 2021 .

[33]  Nadeem Javaid,et al.  DIEER: Delay-Intolerant Energy-Efficient Routing with Sink Mobility in Underwater Wireless Sensor Networks , 2020, Sensors.

[34]  Oleksandr Lemeshko,et al.  ADVANCED TENSOR APPROACH TO FAST REROUTE WITH QUALITY OF SERVICE PROTECTION UNDER MULTIPLE PARAMETERS , 2020 .

[35]  Guo Cao,et al.  Application-Aware SDN-Based Iterative Reconfigurable Routing Protocol for Internet of Things (IoT) , 2020, Sensors.

[36]  Peter Lundqvist,et al.  QOS-Enabled Networks: Tools and Foundations , 2011 .

[37]  Y. W. Chen,et al.  Robust supervised learning based on tensor network method , 2018, 2018 33rd Youth Academic Annual Conference of Chinese Association of Automation (YAC).

[38]  Ning Wang,et al.  An overview of routing optimization for internet traffic engineering , 2008, IEEE Communications Surveys & Tutorials.