LS-SDV: Virtual Network Management in Large-Scale Software-Defined IoT

Li, He; Ota, Kaoru; Dong, Mianxiong

doi:10.1109/jsac.2019.2927099

Cited by 28 publications

(5 citation statements)

References 40 publications

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“…The control plane is responsible for configuring the rules on network devices and controlling the network behavior. The SDN helps to simplify the control and management of next-generation networks, most importantly the IoT, Cloud Computing, and Cyber-Physical Systems [18]. These technologies have caused exponential growth in the connectivity of heterogeneous devices to the internet [19], [20].…”

Section: Software Defined Networkmentioning

confidence: 99%

A Secured Framework for SDN-Based Edge Computing in IoT-Enabled Healthcare System

et al. 2020

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The Internet of Things (IoT) consists of resource-constrained smart devices capable to sense and process data. It connects a huge number of smart sensing devices, i.e., things, and heterogeneous networks. The IoT is incorporated into different applications, such as smart health, smart home, smart grid, etc. The concept of smart healthcare has emerged in different countries, where pilot projects of healthcare facilities are analyzed. In IoT-enabled healthcare systems, the security of IoT devices and associated data is very important, whereas Edge computing is a promising architecture that solves their computational and processing problems. Edge computing is economical and has the potential to provide low latency data services by improving the communication and computation speed of IoT devices in a healthcare system. In Edge-based IoT-enabled healthcare systems, load balancing, network optimization, and efficient resource utilization are accurately performed using artificial intelligence (AI), i.e., intelligent software-defined network (SDN) controller. SDN-based Edge computing is helpful in the efficient utilization of limited resources of IoT devices. However, these low powered devices and associated data (private sensitive data of patients) are prone to various security threats. Therefore, in this paper, we design a secure framework for SDN-based Edge computing in IoT-enabled healthcare system. In the proposed framework, the IoT devices are authenticated by the Edge servers using a lightweight authentication scheme. After authentication, these devices collect data from the patients and send them to the Edge servers for storage, processing, and analyses. The Edge servers are connected with an SDN controller, which performs load balancing, network optimization, and efficient resource utilization in the healthcare system. The proposed framework is evaluated using computer-based simulations. The results demonstrate that the proposed framework provides better solutions for IoT-enabled healthcare systems.

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Section: Software Defined Networkmentioning

confidence: 99%

A Secured Framework for SDN-Based Edge Computing in IoT-Enabled Healthcare System

et al. 2020

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“…Satellite [1], terrestrial base station (TBS) [2], and aerial base station (ABS) [3] both play critical roles in the IoT. The inherent limitations of terrestrial infrastructure and economic reasons prohibit the deployment of terrestrial networks in remote or inaccessible areas, such as rural areas, deserts, and oceans [4]. Since remote terminals cannot access TBSs, terminal services are mainly provided by satellite and ABS in the above areas [5].…”

Section: Introductionmentioning

confidence: 99%

“…FIGURE4 Total quality of service (QoS) F without aerial base stations (ABSs) versus minimum request R min under P SAT tol = 33 dBW.…”

mentioning

confidence: 99%

Time‐space‐power allocation for enhanced IoT‐terminal services in cognitive satellite‐aerial networks

Yao

Fan

et al. 2023

IET Communications

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In remote and inaccessible areas, the traffic request for Internet-of-Things (IoT) terminals is growing. This paper proposes a cognitive satellite-aerial network (CSAN) to provide sufficient access services. The proposed CSAN consists of the primary beam-hopping (BH) satellite and secondary aerial-based station (ABS) systems. Since the two systems share spectrums, co-channel interference (CCI) between the two systems is complicated, and the quality of service (QoS) is seriously degraded. To improve the QoS, the dynamic BH (DBH) pattern, ABS access in the time domain, and ABS power control in the power domain are studied. First, based on the sparsity of the DBH pattern, the greedy quick tracking (GAT) algorithm is proposed to design the DBH pattern quickly. Then, subject to the DBH pattern, a greedy access monitor (GAM) algorithm is determined for timely ABS access and power control. Since each ABS only serves terminals within a suitable distance, the placement and terminal cluster of multi-ABSs in the space domain are required to ensure full terminal coverage. Thus, the mutual selection K algorithm is proposed to save required ABS numbers and improve service fairness among terminal clusters. Simulation results demonstrate the efficacy of time-space-power allocation for enhanced IoT-terminal services in the proposed CSAN.

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“…The delay associated with 802.11 networks is introduced in [11]. As one of the essential concerns in SDVN, the delay affects the state synchronization between network devices [14]. The load-balancing metric [15] is another critical metric used to balance and distribute the load of the whole network into multiple operable units.…”

Section: Introductionmentioning

confidence: 99%

A Novel Cost-Effective Controller Placement Scheme for Software-Defined Vehicular Networks

Lin

Zhao

et al. 2021

IEEE Internet Things J.

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Energy costs have dramatically increased in data center networks as an increasing number of large-scale Internet applications are used. In software-defined vehicular networks (SDVN), the communication delay between two vehicles and between vehicles and the controller will dramatically climb up as the number of vehicles increases. This requires more controllers to provide communication service to minimize the latency. More controllers lead to high energy costs. Therefore, the number of controllers and their placement, the so-called controller placement problem (CPP), should be addressed. The appropriate placement of controllers can decrease the energy cost, enabling green communication in SDVN. Although CPP has been studied for static networks, it has not been effectively solved in highly dynamic and complex networks. In this paper, a novel cost-effective CPP scheme for SDVN is proposed. First, our proposed minimum controller selection mechanism (MOSA) can reduce the number of controllers and guarantee the coverage of the area. Besides, an improved multi-objective artificial bee colony algorithm (IMABC) is proposed based on the original artificial bee colony algorithm. The IMABC can judge which controller should be switched on for data transmission based on real-time traffic flow. A route computation mechanism is proposed to evaluate the performance of our CPP scheme. The experimental results confirm that compared to other existing CPP schemes, our scheme can achieve a higher packet delivery ratio while greatly reducing energy consumption and latency.

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LS-SDV: Virtual Network Management in Large-Scale Software-Defined IoT

Cited by 28 publications

References 40 publications

A Secured Framework for SDN-Based Edge Computing in IoT-Enabled Healthcare System

A Secured Framework for SDN-Based Edge Computing in IoT-Enabled Healthcare System

Time‐space‐power allocation for enhanced IoT‐terminal services in cognitive satellite‐aerial networks

A Novel Cost-Effective Controller Placement Scheme for Software-Defined Vehicular Networks

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