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

Abstract

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.

Advanced Tensor Solution to the Problem of Inter-Domain Routing with Normalized Quality of Service

“…Regarding QoS routing [19,22,[28][29][30][31][32][33], the tensor methodology of network research seems to be relevant [31][32][33]. This class of solutions allows us to obtain the analytical conditions for Quality of Service guaranteed under several indicators, such as average end-to-end packet delay, bandwidth, and packet loss probability.…”

“…According to the methodology of network tensor modeling [22][23][24]32,33], the domain structure determines the anisotropic space formed by coordinate paths. Network edges (links), circuits, interpolar paths, and node pairs can serve as coordinate paths where the network poles are the routers R p in and R p out .…”

“…Further, the index p in all tensor quantities and their projections will be omitted for greater clarity of information perception because it is always a question of only physical quantities associated with the pth domain. The tensor can be written in the index form [32,33]:…”

Flow-based Routing Model with Load Balancing on the Traffic Engineering Principles Taking into Account the Information Security Risks

“…Данні, які наведені в табл. 1, були використані для розрахунку ризиків інформаційної безпеки маршрутизаторів, каналів зв'язку (7), шляхів (11)…”

“…Розповсюдженим підходом до розв'язання задач безпечної та QoS-маршрутизації є використання маршрутних метрик, що мають бути безпосередньо пов'язаними з показниками QoS і NS [5][6][7][8][9][10]. Метричний підхід показує досить високу ефективність в умовах забезпечення QoS або NS за одним попередньо обраним основним показником ефективності ТКМ, наприклад, кількістю переприйомів, середньою затримкою або ймовірністю компрометації пакетів [7,8]. У статті [10] запропоновано маршрутне рішення з урахуванням ризиків інформаційної безпеки за допомогою базових метрик критичності вразливостей.…”