Fairness-aware radio resource management for medical interoperability between WBAN and WLAN

Cho, Byeong-Moon; Park, Kyung‐Joon

doi:10.1007/s12243-016-0499-6

Cited by 3 publications

(1 citation statement)

References 13 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In the SDN design, the network controller acquires the global understanding of the network, opening up innovative opportunities for scalable administration. Not long ago Wi-Fi networks have expanded with SDN capabilities [32]. Researchers have integrated Mininet with NS-3 to develop an Open Net simulator for managing simulations for SD-Wi-Fi [33].…”

Section: Load Balancing In Data Planementioning

confidence: 99%

An Adaptive Symmetrical Load Balancing Scheme for Next Generation Wireless Networks

Manzoor,

Mazhar,

Binaris

et al. 2023

Symmetry

View full text Add to dashboard Cite

In dense Wi-Fi networks, achieving load balancing is critical to optimize network utilization and provide equitable network consumption among the users. Traditional Wi-Fi networks have issues in attaining effective load balancing. Software-Defined Networking (SDN) has presented a viable solution by isolating the data plane and control plane, enabling more agile and cost-effective networks. In this paper we put forward an Adaptive Symmetrical Load Balancing (ASLB) scheme to ensure fairness of load symmetry in Software Defined Wi-Fi Networks (SD-Wi-Fi), while also optimizing the flows transition process using an Analytical Hierarchal Process (AHP). User activity is monitored by access points (APs), which operate under OpenFlow standards. Three essential features, packet volume, packet category and delay hindrance, are used for flow assignment to various controllers. The controllers are arranged in two tiers, universal and regional controllers. The universal controller (UC) handles the workload statistics of regional controllers (RC) in the form of clusters. Extensive simulations using OMNeT++ simulator are performed. The performance parameters taken into consideration are throughput, delay, packet loss rate, network transition count and workload distribution. Our findings demonstrate that the ASLB technique effectively optimizes the network utilization and ensures equitable network consumption among the end users. The proposed scheme outperforms the Mean Probe Delay scheme (MPD), Channel Measurement-based Access Selection scheme (CMAS), Received Signal Strength Indicator-based scheme (RSSI) and Distributed Antenna Selection scheme (DASA), being 40% higher in throughput and 25% lower in delay.

show abstract

Section: Load Balancing In Data Planementioning

confidence: 99%

An Adaptive Symmetrical Load Balancing Scheme for Next Generation Wireless Networks

Manzoor,

Mazhar,

Binaris

et al. 2023

Symmetry

View full text Add to dashboard Cite

show abstract

Understanding Traffic Load in Software Defined WiFi Networks for Healthcare

Manzoor

Zhang

Hei

et al. 2019

2019 IEEE International Conference on Consumer Electronics - Taiwan (ICCE-TW)

View full text Add to dashboard Cite

A Survey on Machine-Learning Based Security Design for Cyber-Physical Systems

Kim

Park

2021

Applied Sciences

View full text Add to dashboard Cite

A cyber-physical system (CPS) is the integration of a physical system into the real world and control applications in a computing system, interacting through a communications network. Network technology connecting physical systems and computing systems enables the simultaneous control of many physical systems and provides intelligent applications for them. However, enhancing connectivity leads to extended attack vectors in which attackers can trespass on the network and launch cyber-physical attacks, remotely disrupting the CPS. Therefore, extensive studies into cyber-physical security are being conducted in various domains, such as physical, network, and computing systems. Moreover, large-scale and complex CPSs make it difficult to analyze and detect cyber-physical attacks, and thus, machine learning (ML) techniques have recently been adopted for cyber-physical security. In this survey, we provide an extensive review of the threats and ML-based security designs for CPSs. First, we present a CPS structure that classifies the functions of the CPS into three layers: the physical system, the network, and software applications. Then, we discuss the taxonomy of cyber-physical attacks on each layer, and in particular, we analyze attacks based on the dynamics of the physical system. We review existing studies on detecting cyber-physical attacks with various ML techniques from the perspectives of the physical system, the network, and the computing system. Furthermore, we discuss future research directions for ML-based cyber-physical security research in the context of real-time constraints, resiliency, and dataset generation to learn about the possible attacks.

show abstract

Fairness-aware radio resource management for medical interoperability between WBAN and WLAN

Cited by 3 publications

References 13 publications

An Adaptive Symmetrical Load Balancing Scheme for Next Generation Wireless Networks

An Adaptive Symmetrical Load Balancing Scheme for Next Generation Wireless Networks

Understanding Traffic Load in Software Defined WiFi Networks for Healthcare

A Survey on Machine-Learning Based Security Design for Cyber-Physical Systems

Contact Info

Product

Resources

About