LBSMT: Load Balancing Switch Migration Algorithm for Cooperative Communication Intelligent Transportation Systems

Babbar, Himanshi; Rani, Shalli; Nawaz, Raheel

doi:10.1109/tgcn.2022.3162237

Cited by 23 publications

(10 citation statements)

References 29 publications

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“…Most of the data forwarding decisions are controlled by the SDN control plane. 36 Queueing analytical methods provide an effective means of collecting valuable information to make appropriate decisions. It is found that using the most dynamic and on-demand traffic flow approach can minimize delay and packet losses.…”

Section: Performance Analysis In Vanetsmentioning

confidence: 99%

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Stochastic modeling and performance analysis in balancing load and traffic for vehicular ad hoc networks: A review

Ravi

Kumar²,

et al. 2023

Int J Network Mgmt

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SummaryThe rapid growth of vehicular applications has resulted in high demand for Internet technology, which demands an unprecedented network capacity and a high quality of service (QoS). In vehicular ad hoc networks (VANETs), since nodes (vehicles) are highly mobile. The dynamic nature of the network topology in the VANET system changes due to frequent changes in link connectivity. The vehicles‐to‐vehicles (V2V), vehicles‐to‐infrastructure (V2I), and QoS, as well as the heterogeneity of applications within the VANET. VANETs have been introduced to make driving comfortable by providing safety and support to drivers. Due to the flexibility and offloading schemes available in‐vehicle applications, there are some limitations. However, there are many issues in providing optimum service provisioning and scheduling in the vehicular environment. In VANETs, BSs and roadside units (RSUs) improve QoS. However, Internet services transmit packets to vehicles using stochastic models, and it predicts the traffic on a VANET. We provide open challenges to drive stochastic models in this direction.

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Section: Performance Analysis In Vanetsmentioning

confidence: 99%

“…Consequently, the stochastic modeling method appears to be a tool for dealing with massive data produced in a large VANET environment. Most of the data forwarding decisions are controlled by the SDN control plane 36 …”

Section: A Comprehensive Review Of Vanetmentioning

confidence: 99%

Stochastic modeling and performance analysis in balancing load and traffic for vehicular ad hoc networks: A review

Ravi

Kumar²,

et al. 2023

Int J Network Mgmt

View full text Add to dashboard Cite

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“…Traditional network-based QoS policies are usually based on open shortest path first (OSPF) [ 2 ], equal-cost multipath routing (ECMP) [ 3 ] or heuristic optimization algorithms [ 4 , 5 , 6 ] for forwarding traffic. However, OSPF and ECMP use fixed forwarding methods, which easily result in link congestion when faced with complex traffic tasks.…”

Section: Related Researchmentioning

confidence: 99%

“…SDN controllers can improve the network performance from a global perspective using artificial intelligence algorithms, including network throughput, packet loss, transmission delay, and load balancing, which is of great significance to ensure the network QoS [ 1 ]. However, most traditional QoS optimization schemes in SDN are based on traditional routing or heuristic algorithms [ 2 , 3 , 4 , 5 , 6 ]. Heuristic algorithms need to build models based on specific real-world problems.…”

Section: Introductionmentioning

confidence: 99%

AQMDRL: Automatic Quality of Service Architecture Based on Multistep Deep Reinforcement Learning in Software-Defined Networking

Chen

Liao

Wang

et al. 2022

Sensors

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Software-defined networking (SDN) has become one of the critical technologies for data center networks, as it can improve network performance from a global perspective using artificial intelligence algorithms. Due to the strong decision-making and generalization ability, deep reinforcement learning (DRL) has been used in SDN intelligent routing and scheduling mechanisms. However, traditional deep reinforcement learning algorithms present the problems of slow convergence rate and instability, resulting in poor network quality of service (QoS) for an extended period before convergence. Aiming at the above problems, we propose an automatic QoS architecture based on multistep DRL (AQMDRL) to optimize the QoS performance of SDN. AQMDRL uses a multistep approach to solve the overestimation and underestimation problems of the deep deterministic policy gradient (DDPG) algorithm. The multistep approach uses the maximum value of the n-step action currently estimated by the neural network instead of the one-step Q-value function, as it reduces the possibility of positive error generated by the Q-value function and can effectively improve convergence stability. In addition, we adapt a prioritized experience sampling based on SumTree binary trees to improve the convergence rate of the multistep DDPG algorithm. Our experiments show that the AQMDRL we proposed significantly improves the convergence performance and effectively reduces the network transmission delay of SDN over existing DRL algorithms.

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“…Many studies have been conducted to resolve this crucial issue faced by SNs. Many techniques have been proposed, some of which affect only one of the four layers of an SN; others tend to have an impact on all four layers combined [7,8,9,10]. In the present work, we propose the use of a technique that acts on the processing and communication layers of an SN to reduce power consumption and, consequently, increase its lifetime.…”

Section: Introductionmentioning

confidence: 99%

Energy Saving Multi-Relay Technique for Wireless Sensor Networks Based on Hw/Sw MPSoC System

Loukil

2023

IEEE Access

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Currently, we are witnessing a wide range of Wireless Sensor Networks (WSNs) in various fields of application. In most cases, these networks contain numerous battery-powered sensor nodes. Therefore, the lifetime of WSNs is intrinsically dependent. For this purpose, different studies have been conducted to reduce the power consumption. We propose a new technique for reducing the power consumption of clustered WSNs. We considered clusters in which sensors transmitted data to a Cluster Head (CH) by cooperative communication based on the Bit Error Probability (BEP) criterion for the multi-relay technique. Therefore, the proposed technique uses a multi-relay to reduce the transmission power to communicate between the source and destination which respects the predefined reliability level. The proof of the described technique was performed using a multiprocessor architecture. Second, we used an efficient software/hardware (Sw/Hw) architecture that utilized accelerator modules. The experimental results demonstrate significant gains in terms of energy consumption and workload compared to the SW implementation.

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LBSMT: Load Balancing Switch Migration Algorithm for Cooperative Communication Intelligent Transportation Systems

Cited by 23 publications

References 29 publications

Stochastic modeling and performance analysis in balancing load and traffic for vehicular ad hoc networks: A review

Stochastic modeling and performance analysis in balancing load and traffic for vehicular ad hoc networks: A review

AQMDRL: Automatic Quality of Service Architecture Based on Multistep Deep Reinforcement Learning in Software-Defined Networking

Energy Saving Multi-Relay Technique for Wireless Sensor Networks Based on Hw/Sw MPSoC System

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