Real-time QoS-aware Routing Scheme in SDN-based Robotic Cyber-Physical Systems

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

doi:10.1109/icmsr.2019.8835463

Cited by 11 publications

(7 citation statements)

References 21 publications

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“…The size of data packets used for routing is 512 bytes with the traffic model considered for generating packets follows the constant bit rate (CBR) traffic pattern. 38,39 Among the complete number of mobile nodes deployed in the environment, approximately 10%-40% of the mobile nodes are made to act as non-cooperative nodes (comprising of malicious nodes and selfish nodes), and it is induced to drop considerable number of packets forwarded by them. The simulation time used for implementing the proposed FPROMETHEE-NCE scheme is 11.04 min.…”

Section: Simulation Results and Discussionmentioning

confidence: 99%

“…The mobile nodes move based on the random way point model and the percentage of packet dropped by them is set to 70%–90%. The size of data packets used for routing is 512 bytes with the traffic model considered for generating packets follows the constant bit rate (CBR) traffic pattern 38,39 . Among the complete number of mobile nodes deployed in the environment, approximately 10%–40% of the mobile nodes are made to act as non‐cooperative nodes (comprising of malicious nodes and selfish nodes), and it is induced to drop considerable number of packets forwarded by them.…”

Section: Simulation Results and Discussionmentioning

confidence: 99%

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Fuzzy preference ranking organization method for enrichment evaluation‐based node cooperation technique for improving QoS in MANETs

Mylsamy¹,

Jayaprakash²

2022

Int J Communication

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Summary Cooperation between mobile nodes is the predominant factor required for achieving reliable data dissemination in mobile ad hoc networks (MANETs), since non‐cooperative nodes crumbles the routing process and degrades network performance. The degree of non‐cooperation rendered by mobile nodes need to be accurately identified by exploring feasible and comprehensive number of criteria to achieve maximized cooperation in uncertain MANET. In this paper, fuzzy preference ranking organization method for enrichment evaluation (FPROMETHEE)‐based node cooperation technique is proposed with the merits of trapezoidal fuzzy interval numbers that aids in the selection of high trustworthy mobile nodes for attaining maximized data delivery. This FPROMETHEE technique utilizes complex and multiple criteria for potential ranking in the presence of finite number of mobile nodes. It prevented the bias of information that is more common during the judgmental process associated with the cooperation estimation of mobile nodes. It includes information about the relative weights of criteria and decision maker's preferences for estimating the trust of mobile nodes to include or isolate them from the routing path. It is also useful in handling the degree of uncertainly involved in the process of routing without compromising Quality of Service (QoS) level in the network. The simulation experiments of the proposed FPROMETHEE technique conducted using ns‐2 simulator confirmed its predominance in enhancing the packet dissemination rate, throughput, energy consumptions, total overhead, and packet loss rate for different number of mobile nodes, malicious nodes, and pairs of source and destination nodes.

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Section: Simulation Results and Discussionmentioning

confidence: 99%

Section: Simulation Results and Discussionmentioning

confidence: 99%

Fuzzy preference ranking organization method for enrichment evaluation‐based node cooperation technique for improving QoS in MANETs

Mylsamy¹,

Jayaprakash²

2022

Int J Communication

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“…Without a doubt, it is also possible that no paths meeting users' QoS requirements can be found, in which case, P = ∅.Under the circumstance that the constructed model is aimed at finding one and only one path P div , parameter z i is designed to signify whether the path P i ∈ P is selected or not. Moreover, z i is expressed in the following (13):…”

Section: A Model Buildingmentioning

confidence: 99%

Study on QoS Routing Optimization Algorithms for Smart Ocean Networks

Tian

Chang

Chen³

et al. 2023

IEEE Access

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Nowadays, ocean networks gradually become increasingly important for communication among network entities such as maritime and sea-crossing users. However, ocean networks are highly dynamic because the communication links are composed of satellite and microwave links, which could be easily influenced by the environment such as local climate. Thus, network transmission in ocean networks faces great challenges, including low reliability and low efficiency. In this paper, we propose a smart ocean network architecture, where we use Software Defined Network (SDN) to perform unified management of the network, and Segment Routing (SR) to control data forwarding paths. In this way, we can control network flows and optimize network routing among diverse network entities in an ocean network. However, many Quality of Service (QoS) guaranteed applications in ocean networks, such as remote control, require lower delay. To guarantee the performance for such applications, we further propose QoS routing algorithms based on Fuzzy-Lagrange for the smart ocean networks architecture, where the optimization objective is to ensure service quality provided to users. According to experimental results, it is proved that, in comparison with the benchmark algorithms, the Fuzzy-Lagrange (FuzLag) algorithm proposed based on link fuzzification and Lagrangian Relaxation can improve the performance by 23% at most. INDEX TERMSOcean networks, control overhead, QoS routing, software defined network, segment routing.

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“…The data plane that comprises switches or any packetforwarding devices will forward packets to their destined egress point. Besides simplifying the network architectures, SDN is also able to improve Quality-of-Service (QoS) of an industrial cyber-physical systems, typically robotic cyber-physical system using SDN-based routing mechanism [1] and network slicing purpose [2]. Further, SDN has the potential to ease the manageability of the Multiple-Input-Multiple-Output (MIMO) system as there are plenty of research has been carried out to focus on improving the performance of massive MIMO system, for example, pilot contamination [3].…”

Section: Introductionmentioning

confidence: 99%

Flow Management Mechanism in Software-Defined Network

Tan¹,

Chong²,

Anbar³

2022

Computers, Materials &Amp; Continua

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Software-defined networking (SDN) is a paradigm shift in modern networking. However, centralised controller architecture in SDN imposed flow setup overhead issue as the control plane handles all flows regardless of size and priority. Existing frameworks strictly reduce control plane overhead and it does not focus on rule placement of the flows itself. Furthermore, existing frameworks do not focus on managing elephant flows like RTSP. Thus, the proposed mechanism will use the flow statistics gathering method such as random packet sampling to determine elephant flow and microflow via a predefined threshold. This mechanism will ensure that the control plane works at an optimum workload because the controller only manages elephant flows via reactive routing and rule placement respectively. Reactive routing has reduced link bandwidth usage below the pre-defined threshold. Furthermore, rule placement has increased average throughput and total transfer to 238%. Meanwhile, the data plane switches will be able to forward microflows via multipath wildcard routing without invoking controller in greater responding time by 85 ms faster in two Transmission Control Protocol (TCP) traffic and achieved 11% and 12% higher total transfer size and throughput respectively. Hence, the controller's workload reduced significantly to 48% in two TCP traffic.

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Real-time QoS-aware Routing Scheme in SDN-based Robotic Cyber-Physical Systems

Cited by 11 publications

References 21 publications

Fuzzy preference ranking organization method for enrichment evaluation‐based node cooperation technique for improving QoS in MANETs

Fuzzy preference ranking organization method for enrichment evaluation‐based node cooperation technique for improving QoS in MANETs

Study on QoS Routing Optimization Algorithms for Smart Ocean Networks

Flow Management Mechanism in Software-Defined Network

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