Increasing fault tolerance of data plane on the internet of things using the software-defined networks

Abstract

Considering the Internet of Things (IoT) impact in today’s world, uninterrupted service is essential, and recovery has received more attention than ever before. Fault-tolerance (FT) is an essential aspect of network resilience. Fault-tolerance mechanisms are required to ensure high availability and high reliability in systems. The advent of software-defined networking (SDN) in the IoT plays a significant role in providing a reliable communication platform. This paper proposes a data plane fault-tolerant architecture using the concepts of software-defined networks for IoT environments. In this work, a mathematical model called Shared Risk Link Group (SRLG) calculates redundant paths as the primary and backup non-overlapping paths between network equipment. In addition to the fault tolerance, service quality was considered in the proposed schemes. Putting the percentage of link bandwidth usage and the rate of link delay in calculating link costs makes it possible to calculate two completely non-overlapping paths with the best condition. We compare our two proposed dynamic schemes with the hybrid disjoint paths (Hybrid_DP) method and our previous work. IoT developments, wireless and wired equipment are now used in many industrial and commercial applications, so the proposed hybrid dynamic method supports both wired and wireless devices; furthermore multiple link failures will be supported in the two proposed dynamic schemes. Simulation results indicate that, while reducing the error recovery time, the two proposed dynamic designs lead to improved service quality parameters such as packet loss and delay compared to the Hybrid_DP method. The results show that in case of a link failure in the network, the proposed hybrid dynamic scheme’s recovery time is approximately 12 ms. Furthermore, in the proposed hybrid dynamic scheme, on average, the recovery time, the packet loss, and the delay improved by 22.39%, 8.2%, 5.66%, compared to the Hybrid_DP method, respectively.

Adaptive quality of service for packet loss reduction using OpenFlow meters

“…SDN has addressed many network programmability problems ( Hu et al, 2013 ; Zhou, Zhu & Xiao, 2015 ; Long et al, 2013 ; Chou et al, 2014 ; Yang & Yeung, 2020 ; Ze & Yeung, 2017 ; Kaur, Kaur & Gupta, 2016 ; Kiadehi, Rahmani & Molahosseini, 2021 ) and has provided a flexible way of managing networks. Some of these include load balancing applications such as the work in Hwang & Chi (2003) , which implements load balancing in wide-area OpenFlow networks, controller load balancing ( Hu et al, 2013 ) to reduce overhead message exchange traffic, path switching to dynamically balance the traffic during data transmission in data centers ( Zhou, Zhu & Xiao, 2015 ), distributing large dataset to clients using genetic algorithm ( Long et al, 2013 ), and load balancers which converts the data plane into load balancers by employing certain strategies in the POX controller ( Ze & Yeung, 2017 ).…”

“…Another solution presented a method of minimizing network bandwidth ( Chou et al, 2014 ) for flow monitoring by polling some statistics to prevent overwhelming the OpenFlow switches. SDN has not only leveraged the possibilities in organizational networks but also in IoT by providing fault tolerant solutions ( Kiadehi, Rahmani & Molahosseini, 2021 ).…”

The importance of nature‐inspired metaheuristic algorithms in the data routing and path finding problem in the internet of things

“…Battery‐powered devices may potentially cease to function due to a lack of energy supply. In such situations, sensor nodes are prone to failure to fulfill their functions or provide inaccurate readings that do not precisely represent the actual status of the environmental phenomena or events being monitored 103 …”