Airtime-based resource control in wireless LANs for wireless network virtualization

Nakauchi, Kiyohide; Shoji, Yozo; Nishinaga, Nozomu

doi:10.1109/icufn.2012.6261686

Cited by 35 publications

(31 citation statements)

References 9 publications

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“…On the other hand, the node manager has an interface for the network virtualization manager, and initiates and removes the virtual Network virtualization has been widely used in traditional wireless technologies. For example, the authors of [14] applied network virtualization on a WLAN system adopting the IEEE 802.11e EDCA (Enhanced Distributed Channel Access). The authors focused their study on controlling the air-time usage rather than controlling the bandwidth usage.…”

Section: Related Workmentioning

confidence: 99%

SD-CRN: Software Defined Cognitive Radio Network Framework

Jararweh

Ayyoub

Doulat

et al. 2014

2014 IEEE International Conference on Cloud Engineering

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Software defined networking (SDN) provides a novel network resource management framework that overcomes several challenges related to network resources management. On the other hand, Cognitive Radio (CR) technology is a promising paradigm for addressing the spectrum scarcity problem through efficient dynamic spectrum access (DSA). CR provides unlicensed secondary users with the ability to coexist with licensed users in non-interfering mode. In this paper, we introduce a virtualization based SDN resource management framework for cognitive radio networks (CRNs). The framework uses the concept of multilayer hypervisors for efficient resources allocation. It also introduces a semidecentralized control scheme that allows the CRN base station (BS) to delegate some of the management responsibilities to the network users. CRN resource virtualization allows dynamic, infrastructure free and efficient resources allocation to the CR users. The main objectives of the proposed framework is to reduce the CR users' reliance on the CRN BS and physical network resources while improving the network performance by reducing control overhead.

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Section: Related Workmentioning

confidence: 99%

SD-CRN: Software Defined Cognitive Radio Network Framework

Jararweh

Ayyoub

Doulat

et al. 2014

2014 IEEE International Conference on Cloud Engineering

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“…In [50] a mechanism is presented to create virtual APs (VAPs) over a physical AP, in such a way that each VAP has its own MAC transmission queue and virtual machine. Thus, there is a set of EDCA parameters specific to each queue, enabling an air-time-based mechanism to isolate the slices.…”

Section: Ieee 80211 Contextmentioning

confidence: 99%

“…The work in [51] (ViFi) proposes a similar idea to that found in [50] for the uplink traffic, and a slice scheduling mechanism for the downlink traffic. The uplink control mechanism configures two EDCA parameters, the CW min and the transmission opportunity τ for each client.…”

Section: Ieee 80211 Contextmentioning

confidence: 99%

Resource Slicing in Virtual Wireless Networks: A Survey

Richart

Baliosian

Serrat

et al. 2016

IEEE Trans. Netw. Serv. Manage.

338

222

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Abstract-New architectural and design approaches for Radio Access Networks have appeared with the introduction of network virtualization in the wireless domain. One of these approaches splits the wireless network infrastructure into isolated virtual slices under their own management, requirements and characteristics. Despite the advances in wireless virtualization, there are still many open issues regarding the resource allocation and isolation of wireless slices. Because of the dynamics and shared nature of the wireless medium, guaranteeing that the traffic on one slice will not affect the traffic on the others has proven to be difficult. In this work, we focus on the detailed definition of the problem, discussing its challenges. We also provide a review of existing works that deal with the problem, analyzing how new trends such as SDN and NFV can assist in the slicing. We will finally describe some research challenges on this topic.

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“…Constraints in (13b) guarantee the minimum airtime reservations for all ISPs (i.e., i∈S k ,a∈A T a air,i ≥ η k ) based on (12). This set of constraints enable controlling ISPs' share of access airtime regardless of their number of STAs.…”

Section: A Optimization Problemmentioning

confidence: 99%

“…There are a few works addressing only airtime control in the literature. Considering a virtualized single-AP WLAN, heuristic algorithms [12] and control theory [13] are employed to tune the airtime usage by controlling the minimum contention window (CW) of each STA. But, as the discussion is limited to controlling minimum CW, the optimality of the result might be sacrificed.…”

Section: Introductionmentioning

confidence: 99%