Machine Learning Routing Protocol in Mobile IoT based on Software-Defined Networking

J. F. Jurado Letizia Marchegiani A. Abu-Mahfouz + 2 lainnya

3 Februari 2022

Wireless Sensor Network (WSN), which are enablers of the Internet of Things (IoT) technology, are typically used en-masse in widely physically distributed applications to monitor the dynamic conditions of the environment. They collect raw sensor data that is processed centralised. With the current traditional techniques of state-of-art WSN programmed for specific tasks, it is hard to react to any dynamic change in the conditions of the environment beyond the scope of the intended task. To solve this problem, a synergy between Software-Defined Networking (SDN) and WSN has been proposed. This paper aims to present the current status of Software-Defined Wireless Sensor Network (SDWSN) proposals and introduce the readers to the emerging research topic that combines Machine Learning (ML) and SDWSN concepts, also called ML-SDWSNs. ML-SDWSN grants an intelligent, centralised and resource-aware architecture to achieve improved network performance and solve the challenges currently found in the practical implementation of SDWSNs. This survey provides helpful information and insights to the scientific and industrial communities, and professional organisations interested in SDWSN, mainly the current state-of-art, ML techniques, and open issues.

L. Mamatas T. Theodorou

29 September 2020

The Internet of Things (IoT) brings new potentials in humans’ everyday life activities through enabling applications with stringent communication demands, including mobile IoT applications. State-of-the-art routing protocols for the IoT, such as IPv6 routing protocol for low-power and lossy networks (RPL), have not been originally designed for such challenging applications. Recent proposals blend the software-defined networking (SDN) paradigm with IoT, enabling better-informed and bespoke routing control, matching the application requirements. In this article, we propose SD-MIoT, an open-source SDN solution for mobile IoT environments that consists of a modular SDN controller and an OpenFlow-like protocol. SD-MIoT detects passively in real-time, the network’s mobile nodes through mobility detector (MODE), an intelligent algorithm that utilizes the connectivity graph of the SDN controller. It incorporates novel mobility-aware topology discovery mechanisms, routing policies, and flow-rule establishment methods, all of them balancing control overhead with routing robustness, according to nodes’ mobility behavior detected by MODE. We provide extensive evaluation results over two realistic scenarios, further confirming the suitability of SD-MIoT for mobile IoT environments and demonstrating reliable operation in terms of successful data packet delivery with low control overhead.

R. Fantacci Michele Bonanni L. Pierucci + 1 lainnya

28 April 2021

Software Defined Networking (SDN) provides a new perspective for the Internet of Things (IoT), since, with the separation of the control from the data planes, it is viable to optimise the traditional networks operation management. In particular, the SDN Controller has a global vision of the network of sensors/actuators domain, allowing real-time network nodes and data flows reconfiguration. As a consequence, devices, usually facing limited communications and computing resources, are relieved of the route selection task in a distributed and, thus, suboptimal way. This paper proposes a SDN-IoT architecture, specifically focusing on the Controller design, which dynamically optimises in real time the end-to-end flows delivery. In particular, the dynamic routing policy adaptation is based on the real-time estimation of the network status and it allows jointly minimising the end-to-end latency and energy consumption and, consequently, to improve the network life time. The performance of the proposed approach is analysed in terms of the average latency, energy consumption and overhead, pointing out a better behaviour in comparison with the existing distributed approaches.

Prasad Desai S. Mini Deepak K. Tosh

1 Oktober 2022

The efficiency of communication between devices in any network depends on the network architecture and the routing algorithms. This efficiency vastly affects the productivity of the Internet of Things (IoT) nodes when utilized in an industrial environment. The conundrum of using the conventional network architecture in an industry/factory connected by IoT devices has paved the way for the development of software-defined networking (SDN). Traditional network architectures lack network programmability and hinder the testing and performance evaluation of new communication protocols. The use of vendor-specific hardware is a major hindrance to create a network where the control is centralized for the deployment of different policies over the network. This article aims to find an optimal path for efficient communication between the nodes present in a programmable Industrial IoT (IIoT) network. A programmable IIoT network is created and end-user routing algorithms are designed to find the optimal path for communication. We integrate an SDN framework with IIoT nodes for the creation of a centralized programmable network architecture and deploy custom routing algorithms over it for evaluation. To further reduce the communication latency, we incorporate edge computing servers (ECSs) in the network. Three routing algorithms: 1) $K$ -means-based optimal path algorithm; 2) cluster-based optimal path algorithm; and 3) minimum interval-based optimal path algorithm, that can be deployed over an SDN are proposed in this article. Experimental results reveal that the proposed algorithms are more efficient than the existing algorithms.

L. Mamatas T. Theodorou

1 Juni 2020

The Internet of Things (IoT) is gradually incorporating multiple environmental, people, or industrial monitoring deployments with diverse communication and application requirements. The main routing protocols used in the IoT, such as the IPv6 Routing Protocol for Low-Power and Lossy Networks (RPL), are focusing on the many-to-one communication of resource-constraint devices over wireless multi-hop topologies, i.e., due to their legacy of the Wireless Sensor Networks (WSN). The Software-Defined Networking (SDN) paradigm appeared as a promising approach to implement alternative routing control strategies, enriching the set of IoT applications that can be delivered, by enabling global protocol strategies and programmability of the network environment. However, SDN can be associated with significant network control overhead. In this paper, we propose VERO-SDN, an open-source SDN solution for the IoT, bringing the following novelties in contrast to the related works: (i) programmable routing control with reduced control overhead through inherent protocol support of a long-range control channel; and (ii) a modular SDN controller and an OpenFlow-like protocol improving the quality of communication in a wide range of IoT scenarios through supporting two alternative topology discovery and two flow establishment mechanisms. We carried out simulations with various topologies, network sizes and high-volume transmissions with alternative communication patterns. Our results verified the robust performance and reduced control overhead of VERO-SDN for alternative IoT deployments, e.g., achieved up to 47% reduction in network’s overall end-to-end delay time compared to RPL and a packet delivery ratio of over 99.5%.