Opt-ACM: An Optimized load balancing based Admission Control Mechanism for Software Defined Hybrid Wireless based IoT (SDHW-IoT) network

Kumar, Rohit; Udutalapally, Venkanna; Tiwari, Vivek

doi:10.1016/j.comnet.2021.107888

Cited by 19 publications

(13 citation statements)

References 29 publications

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“…Although there have been various resource allocation methods using the results of traffic prediction, load balancing algorithms and their related service reconfiguration mechanism have been the focus of network research in recent years. Specifically, load balancing resource allocation scheme has been studied in a wireless network, SDN IP network, and transmission control protocol (TCP) network [13], [15], [16], [27], [28], [29]. However, to the best of our knowledge, few load balancing schemes consider the traffic prediction results based on edge-cloud collaboration in integrated radio and optical networks.…”

Section: Related Workmentioning

confidence: 99%

Resource Allocation With Edge-Cloud Collaborative Traffic Prediction in Integrated Radio and Optical Networks

et al. 2023

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By integrating communications in different domains, integrated radio and optical networks can serve a wider range of applications and services. Integrated radio and optical network scenarios will involve more weak-computation-ability network nodes, such as small-cell base stations. To pursue efficient integrated radio and optical networks, more efficient ways to conduct transmission under the demand of edge and cloud collaboration are required. The lack of forward-looking resource allocation may easily lead to a waste of network resources without an expected return. Therefore, an efficient resource allocation scheme needs to consider certain issues: 1) a comprehensive perspective of traffic prediction; 2) a release of pressure on the transmission pipeline during the prediction process; and 3) a reduction of loss of edge nodes due to the computation. In this paper, benefiting from machine learning, we propose a resource allocation with edgecloud collaborative traffic prediction (TP-ECC) in integrated radio and optical networks, where an efficient resource allocation scheme (ERAS) is designed based on the prediction results with the gated recurrent unit model. We maximize the utilization of limited resources to improve the awareness of network status. We present three evaluation indicators and build a network architecture to evaluate our resource allocation scheme. Through edge-cloud collaboration, our proposal can improve traffic prediction accuracy by 9.5% compared with single-point traffic prediction, and resource utilization is also improved by edge-cloud collaborative traffic prediction.INDEX TERMS Integrated radio and optical networks, resource allocation, edge-cloud collaboration, traffic prediction.

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Section: Related Workmentioning

confidence: 99%

Resource Allocation With Edge-Cloud Collaborative Traffic Prediction in Integrated Radio and Optical Networks

et al. 2023

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“…It is calculated using the Packet Error Rate (PER) and the Received Signal Strength Indicator (RSSI). If the LQI is high, the quality of the connection is good as well [35].…”

Section: ))mentioning

confidence: 99%

Gateway selection and placement for Multi-radio multi-channel Wireless Mesh Networks with Garter Snake Optimization algorithm

Naghdiani,

Jahanshahi,

Matin

2023

Preprint

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Wireless mesh networks facilitate the provision of Intranet and Internet connectivity across diverse environments, catering to a wide range of applications. It is anticipated that there will be a significant volume of traffic on these networks. The selection and placement of gateway nodes is a significant research concern due to their responsibility for transmitting traffic load. This issue holds importance as it has the potential to optimize network capacity utilization and mitigate congestion effects. Furthermore, the implementation of a multi-radio multi-channel architecture is regarded as a highly promising approach to enhance performance and mitigate interference. Channel assignment is the process of determining the optimal associations between channels and radios for the purpose of transmitting and receiving data concurrently across multiple channels. In order to maximize throughput in multi-radio multi-channel wireless mesh networks, this research investigates the problem of gateway selection and location. Our solution is distinct from the many others described in the literature because it explicitly models the delay overhead associated with channel switching. In addition, we factor in the latency problem while developing our processes. In our research, a Garter Snake Optimization Algorithm (GSO) is used to strategically place gateways. Based on our research, we know that the suggested scheme performs within a constant factor of the best solution as measured by the achieved throughput. The simulation results show that compared to random deployment, fixed deployment, and grid-based techniques, our suggested mechanism makes better use of available resources and delivers much higher network performance.

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“…In [31] an optimized load balancing-based Admission Control Mechanism (Opt-ACM) is proposed for effective network flow management to decrease network congestion. To validate the efficiency of Opt-ACM, an optimization problem based on Mixed-Integer Linear Programming (MILP)-is formulated and tested using a well-known mathematical optimization solver called Gurobi.…”

Section: Related Workmentioning

confidence: 99%

A Mechanism for Load Balancing Routing and Virtualization Based on SDWSN for IoT Applications

2022

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Wireless sensor networks (WSN) are important communication components of an internet of things (IoT). With the development of IoT and the increasing number of connected devices, network structure management and maintenance face the serious challenge of energy consumption. By balancing the network load, the energy consumption can be improved effectively. In the conventional WSN architecture, the two prerequisites of the load-balancing mechanism, flexibility and adaptability, are difficult to achieve. softwaredefined networking (SDN) is a novel network architecture that can promote flexibility and adaptability using a centralized controller. In this paper, a novel SDN architecture aimed at reducing load distribution and prolonging lifetime is proposed, which consists of different components such as topology, BS and controller discovery, link, and virtual routing. Accordingly, a new mechanism is proposed for load-balancing routing through SDN and virtualization. Through direct monitoring of the link load information and the network running status, the employed OpenFlow protocol can determine load-balancing routing for every flow in different IoT applications. The flows in different resource applications can be directed to a base station (BS) via various routes. This implementation reduces the exchange of network status and other relevant information. Virtual routing aims to weigh forward nodes and select the best node for each IoT application. The simulation results show the distribution of load over the network in the proposed algorithm and are characterized by the balanced network energy consumption, but also it prolongs network lifetime in comparison to the LEACH, improved LEACH, and LEACH-C algorithms. IoT, load balancing, routing, SDN, WSN. INDEX TERMS

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Opt-ACM: An Optimized load balancing based Admission Control Mechanism for Software Defined Hybrid Wireless based IoT (SDHW-IoT) network

Cited by 19 publications

References 29 publications

Resource Allocation With Edge-Cloud Collaborative Traffic Prediction in Integrated Radio and Optical Networks

Resource Allocation With Edge-Cloud Collaborative Traffic Prediction in Integrated Radio and Optical Networks

Gateway selection and placement for Multi-radio multi-channel Wireless Mesh Networks with Garter Snake Optimization algorithm

A Mechanism for Load Balancing Routing and Virtualization Based on SDWSN for IoT Applications

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