Managing Industrial Communication Delays with Software-Defined Networking

Jhaveri, Rutvij H.; Tan, Rui; Easwaran, Arvind; Ramani, Sagar

doi:10.1109/rtcsa.2019.8864557

Cited by 12 publications

(10 citation statements)

References 19 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Since there are fewer entries in the flow table, there is less memory overhead associated with the controller's full installation of flow entries in the switches [34]. 7 shows a comparison of the proposed approach's performance with that of the FT Link and SPRA methods [35]. It can be shown that the proposed method performs better than either technique.…”

Section: Resultsmentioning

confidence: 99%

Reliability Awareness Multiple Path Installation in Software Defined Networking using Machine Learning Algorithm

Majeed

Amin²,

Ali

et al. 2022

IJIST

View full text Add to dashboard Cite

Link failure is still a severe problem in today's networking system. Transmission delays and data packet loss cause link failure in the network. Rapid connection recovery after a link breakdown is an important topic in networking. The failure of the networking link must be recovered whenever possible because it could cause blockage of network traffic and obstruct normal network operation. To overcome this difficulty, backup or secondary channels can be chosen adaptively and proactively in SDN based on data traffic dynamics in the network. When a network connection fails, packets must find a different way to their destination. The goal of this research is to find an alternative way. Our proposed methodology uses a machine-learning algorithm called Linear Regression to uncover alternative network paths. To provide for speedy failure recovery, the controller communicates this alternate path to the network switches ahead of time. We train, test, and validate the learning model using a machine learning approach. To simulate our proposed technique and locate the trials, we use the Mini net network simulator. The simulation results show that our suggested approach recovers link failure most effectively compared to existing solutions.

show abstract

Section: Resultsmentioning

confidence: 99%

Reliability Awareness Multiple Path Installation in Software Defined Networking using Machine Learning Algorithm

Majeed

Amin²,

Ali

et al. 2022

IJIST

View full text Add to dashboard Cite

show abstract

“…Aiming at the intersection and correlation characteristics of information organization and information field, fuzzy clustering can give confidence interval while analyzing feature similarity, which is an effective method to study multisource information collaboration in urban system [25]. If the energy management system is an independent system, the energy consumption in the building will be statistically analyzed.…”

Section: Mobile Information Systemsmentioning

confidence: 99%

Design and Application of Smart City Internet of Things Service Platform Based on Fuzzy Clustering Algorithm

Yin

2022

Mobile Information Systems

View full text Add to dashboard Cite

The development of the city is dependent on various information technologies, the core of which is the Internet of Things technology. The traditional multisource information collaboration mode of urban system is relatively single, with low collaboration efficiency and lack of effective measurement of collaboration structure. In this paper, a design scheme of IoT (Internet of Things) service platform for smart cities is proposed, and a multisource information collaborative difference measurement model with a given confidence interval is constructed based on a fuzzy clustering algorithm to meet the needs of developing IoT energy management application services and “smart city” energy management in different environments. In the experiment of participating in the fusion, the number of participating nodes is reduced to about 50 from the third iteration, which is reduced by half. In the traditional algorithm, almost all nodes participate in every fusion process. However, the improved algorithm can greatly reduce the number of participating nodes, thus greatly reducing the computational requirements of the algorithm. The experimental results show that the fuzzy clustering algorithm is effective. The system can be used in vehicle networking, geological disaster prevention, environmental monitoring, and other fields.

show abstract

“…For protection against failures, the SDN controller preinstalled primary and several backup paths in the data plane elements by applying the fast failover mechanism presented in [32]. Jhaveri et al [33] proposed the end-to-end delay estimation technique with SDN which uses default probe packets to decrease the overhead in communication. Besides, the literature designed a contract-based fault-resilient method to reroute the flows through the restoration approach and react to the changes in the network condition.…”

Section: Link Failure Recoverymentioning

confidence: 99%

Industrial Networks Driven by SDN Technology for Dynamic Fast Resilience

et al. 2021

View full text Add to dashboard Cite

Software-defined networking (SDN) provides the prospect of logically centralized management in industrial networks and simplified programming among devices. It also facilitates the reconfiguration of connectivity when there is a network element failure. This paper presents a new Industrial SDN (ISDN) resilience that addresses the gap between two types of resilience: the first is restoration while the second is protection. Using a restoration approach increases the recovery time proportionally to the number of affected flows contrarily to the protection approach which attains the fast recovery. Nevertheless, the protection approach utilizes more flow rules (flow entries) in the switch which in return increments the lookup time taken to discover an appropriate flow entry in the flow table. This can have a negative effect on the end-to-end delay before a failure occurs (in the normal situation). In order to balance both approaches, we propose a Mixed Fast Resilience (MFR) approach to ensure the fast recovery of the primary path without any impact on the end-to-end delay in the normal situation. In the MFR, the SDN controller establishes a new path after failure detection and this is based on flow rules stored in its memory through the dynamic hash table structure as the internal flow table. At that time, it transmits the flow rules to all switches across the appropriate secondary path simultaneously from the failure point to the destination switch. Moreover, these flow rules which correspond to secondary paths are cached in the hash table by considering the current minimum path weight. This strategy leads to reduction in the load at the SDN controller and the calculation time of a new working path. The MFR approach applies the dual primary by considering several metrics such as packet-loss probability, delay, and bandwidth which are the Quality of Service (QoS) requirements for many industrial applications. Thus, we have built a simulation network and conducted an experimental testbed. The results showed that our resilience approach reduces the failure recovery time as opposed to the restoration approaches and is more scalable than a protection approach. In the normal situation, the MFR approach reduces the lookup time and end-to-end delay than a protection approach. Furthermore, the proposed approach improves the performance by minimizing the packet loss even under failing links.

show abstract

Managing Industrial Communication Delays with Software-Defined Networking

Cited by 12 publications

References 19 publications

Reliability Awareness Multiple Path Installation in Software Defined Networking using Machine Learning Algorithm

Reliability Awareness Multiple Path Installation in Software Defined Networking using Machine Learning Algorithm

Design and Application of Smart City Internet of Things Service Platform Based on Fuzzy Clustering Algorithm

Industrial Networks Driven by SDN Technology for Dynamic Fast Resilience

Contact Info

Product

Resources

About