718 research outputs found

    A New Method of User Association in Wireless Mesh Networks

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    The IEEE 802.11 based wireless mesh networks (WMNs) are becoming the promising technology to provide last-mile broadband Internet access to the users. In order to access the Internet through the pre-deployed WMN, the user has to associate with one of the access points (APs) present in the network. In WMN, it is very common that the user device can have multiple APs in its vicinity. Since the user performance majorly depends on the associated AP, how to select the best AP is always remaining as a challenging research problem in WMN. The traditional method of AP selection is based on received signal strength (RSS) and it is proven inefficient in the literature as the method does not consider AP load, channel conditions, etc. This paper proposes a new method of user association in WMN such that the user selects the AP based on achievable end-to-end throughput measured in the presence of other interfering APs. The proposed association metric is independent of routing protocol and routing metric used in WMN. The simulation results show that our method outperforms the RSS based AP selection method in WMN

    IEEE 802.11 ๊ธฐ๋ฐ˜ Enterprise ๋ฌด์„  LAN์„ ์œ„ํ•œ ์ž์› ๊ด€๋ฆฌ ๊ธฐ๋ฒ•

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    ํ•™์œ„๋…ผ๋ฌธ (๋ฐ•์‚ฌ)-- ์„œ์šธ๋Œ€ํ•™๊ต ๋Œ€ํ•™์› : ๊ณต๊ณผ๋Œ€ํ•™ ์ „๊ธฐยท์ปดํ“จํ„ฐ๊ณตํ•™๋ถ€, 2019. 2. ์ „ํ™”์ˆ™.IEEE 802.11์ด ๋ฌด์„  LAN (wireless local area network, WLAN)์˜ ์‹ค์งˆ์ ์ธ ํ‘œ์ค€์ด ๋จ์— ๋”ฐ๋ผ ์ˆ˜ ๋งŽ์€ ์—‘์„ธ์Šค ํฌ์ธํŠธ(access points, APs)๊ฐ€ ๋ฐฐ์น˜๋˜์—ˆ๊ณ , ๊ทธ ๊ฒฐ๊ณผ WLAN ๋ฐ€์ง‘ ํ™˜๊ฒฝ์ด ์กฐ์„ฑ๋˜์—ˆ๋‹ค. ์ด๋Ÿฌํ•œ ํ™˜๊ฒฝ์—์„œ๋Š”, ์ด์›ƒํ•œ AP๋“ค์— ๋™์ผํ•œ ์ฑ„๋„์„ ํ• ๋‹นํ•˜๋Š” ๋ฌธ์ œ๋ฅผ ํ”ผํ•  ์ˆ˜ ์—†์œผ๋ฉฐ, ์ด๋Š” ํ•ด๋‹น AP๋“ค์ด ๊ฐ™์€ ์ฑ„๋„์„ ๊ณต์œ ํ•˜๊ฒŒ ํ•˜๊ณ  ๊ทธ๋กœ ์ธํ•œ ๊ฐ„์„ญ์„ ์•ผ๊ธฐํ•œ๋‹ค. ๊ฐ„์„ญ์œผ๋กœ ์ธํ•œ ์„ฑ๋Šฅ ์ €ํ•˜๋ฅผ ์ค„์ด๊ธฐ ์œ„ํ•ด ์ฑ„๋„ ํ• ๋‹น(channelization) ๊ธฐ๋ฒ•์ด ์ค‘์š”ํ•˜๋‹ค. ๋˜ํ•œ, ํ•œ ์กฐ์ง์ด ํŠน์ • ์ง€์—ญ์— ๋ฐ€์ง‘ ๋ฐฐ์น˜๋œ AP๋“ค์„ ๊ด€๋ฆฌํ•œ๋‹ค๋ฉด ํŠน์ • ์‚ฌ์šฉ์ž๋ฅผ ์„œ๋น„์Šคํ•  ์ˆ˜ ์žˆ๋Š” AP๊ฐ€ ์—ฌ๋Ÿฟ์ผ ์ˆ˜ ์žˆ๋‹ค. ์ด ๊ฒฝ์šฐ, ์‚ฌ์šฉ์ž ์ ‘์†(user association, UA) ๊ธฐ๋ฒ•์ด ์ค€์ •์ (quasi-static) ํ™˜๊ฒฝ๊ณผ ์ฐจ๋Ÿ‰ ํ™˜๊ฒฝ ๋ชจ๋‘์—์„œ ๋„คํŠธ์›Œํฌ ์„ฑ๋Šฅ์— ํฐ ์˜ํ–ฅ์„ ๋ฏธ์นœ๋‹ค. ๋ณธ ๋…ผ๋ฌธ์—์„œ๋Š” ๋ฐ€์ง‘ ๋ฐฐ์น˜๋œ WLAN ํ™˜๊ฒฝ์—์„œ ์™€์ดํŒŒ์ด(WiFi) ์„ฑ๋Šฅ ํ–ฅ์ƒ์„ ์œ„ํ•ด ์ฑ„๋„ ํ• ๋‹น ๊ธฐ๋ฒ•์„ ์ œ์•ˆํ•œ๋‹ค. ๋จผ์ €, ์ œ์•ˆํ•œ ๊ธฐ๋ฒ•์—์„œ๋Š” ๊ฐ๊ฐ์˜ AP์— ์ฑ„๋„์„ ํ• ๋‹นํ•˜๊ธฐ ์œ„ํ•ด ๊ฐ„์„ญ ๊ทธ๋ž˜ํ”„(interference graph)๋ฅผ ์ด์šฉํ•˜๋ฉฐ ์ฑ„๋„ ๊ฒฐํ•ฉ(channel bonding)์„ ๊ณ ๋ คํ•œ๋‹ค. ๋‹ค์Œ์œผ๋กœ, ์ฃผ์–ด์ง„ ์ฑ„๋„ ๊ฒฐํ•ฉ ๊ฒฐ๊ณผ๋ฅผ ๊ธฐ๋ฐ˜์œผ๋กœ ํ•ด๋‹น AP๊ฐ€ ๋™์  ์ฑ„๋„ ๊ฒฐํ•ฉ์„ ์ง€์›ํ•˜๋Š”์ง€ ์—ฌ๋ถ€์— ๋”ฐ๋ผ ์ฃผ ์ฑ„๋„(primary channel)์„ ๊ฒฐ์ •ํ•œ๋‹ค. ํ•œํŽธ, ์ค€์ •์  ํ™˜๊ฒฝ๊ณผ ์ฐจ๋Ÿ‰ ํ™˜๊ฒฝ์—์„œ์˜ UA ๋ฌธ์ œ๋Š” ๋‹ค์†Œ ์ฐจ์ด๊ฐ€ ์žˆ๋‹ค. ๋”ฐ๋ผ์„œ ๋ณธ ๋…ผ๋ฌธ์—์„œ๋Š” ๊ฐ๊ฐ์˜ ํ™˜๊ฒฝ์— ๋”ฐ๋ผ ์„œ๋กœ ๋‹ค๋ฅธ UA ๊ธฐ๋ฒ•์„ ์„ค๊ณ„ํ•˜์˜€๋‹ค. ์ค€์ •์  ํ™˜๊ฒฝ์—์„œ์˜ UA ๊ธฐ๋ฒ•์€ ๋ฉ€ํ‹ฐ์บ์ŠคํŠธ ์ „์†ก, ๋‹ค์ค‘ ์‚ฌ์šฉ์ž MIMO (multi-user multiple input multiple output), ๊ทธ๋ฆฌ๊ณ  AP ์ˆ˜๋ฉด๊ณผ ๊ฐ™์€ ๋‹ค์–‘ํ•œ ๊ธฐ์ˆ ๊ณผ ํ•จ๊ป˜ AP๊ฐ„์˜ ๋ถ€ํ•˜ ๋ถ„์‚ฐ(load balancing)๊ณผ ์—๋„ˆ์ง€ ์ ˆ์•ฝ์„ ๊ณ ๋ คํ•œ๋‹ค. ์ œ์•ˆํ•˜๋Š” ๊ธฐ๋ฒ•์—์„œ UA ๋ฌธ์ œ๋Š” ๋‹ค๋ชฉ์ ํ•จ์ˆ˜ ์ตœ์ ํ™” ๋ฌธ์ œ๋กœ ์ •์‹ํ™”ํ•˜์˜€๊ณ  ๊ทธ ํ•ด๋ฅผ ๊ตฌํ•˜์˜€๋‹ค. ์ฐจ๋Ÿ‰ ํ™˜๊ฒฝ์—์„œ์˜ UA ๊ธฐ๋ฒ•์€ ํ•ธ๋“œ์˜ค๋ฒ„(handover, HO) ์Šค์ผ€์ค„ ๋ฌธ์ œ๋กœ ๊ท€๊ฒฐ๋œ๋‹ค. ๋ณธ ๋…ผ๋ฌธ์—์„œ๋Š” ๋„๋กœ์˜ ์ง€ํ˜•์„ ๊ณ ๋ คํ•˜์—ฌ ์‚ฌ์šฉ์ž๊ฐ€ ์ ‘์†ํ•  AP๋ฅผ ๊ฒฐ์ •ํ•˜๋Š” HO ์Šค์ผ€์ค„ ๊ธฐ๋ฒ•์„ ์ œ์•ˆํ•œ๋‹ค. ์‚ฌ์šฉ์ž๋Š” ๋‹จ์ง€ ๋‹ค์Œ AP๋กœ ์—ฐ๊ฒฐ์„ ๋งบ์„ ์‹œ๊ธฐ๋งŒ ๊ฒฐ์ •ํ•˜๋ฉด ๋˜๊ธฐ ๋•Œ๋ฌธ์—, ์ฐจ๋Ÿ‰ ํ™˜๊ฒฝ์—์„œ์˜ ๋งค์šฐ ๋น ๋ฅด๊ณ  ํšจ์œจ์ ์ธ HO ๊ธฐ๋ฒ•์„ ๊ตฌํ˜„ํ•  ์ˆ˜ ์žˆ๋‹ค. ์ด๋ฅผ ์œ„ํ•ด, ๊ทธ๋ž˜ํ”„ ๋ชจ๋ธ๋ง ๊ธฐ๋ฒ•(graph modeling technique)์„ ํ™œ์šฉํ•˜์—ฌ ๋„๋กœ๋ฅผ ๋”ฐ๋ผ ๋ฐฐ์น˜๋œ AP์‚ฌ์ด์˜ ๊ด€๊ณ„๋ฅผ ํ‘œํ˜„ํ•œ๋‹ค. ํ˜„์‹ค์ ์ธ ์‹œ๋‚˜๋ฆฌ์˜ค๋ฅผ ์œ„ํ•ด ์ง์„  ๊ตฌ๊ฐ„, ์šฐํšŒ ๊ตฌ๊ฐ„, ๊ต์ฐจ๋กœ, ๊ทธ๋ฆฌ๊ณ  ์œ ํ„ด ๊ตฌ๊ฐ„ ๋“ฑ์„ ํฌํ•จํ•˜๋Š” ๋ณต์žกํ•œ ๋„๋กœ ๊ตฌ์กฐ๋ฅผ ๊ณ ๋ คํ•œ๋‹ค. ๋„๋กœ ๊ตฌ์กฐ๋ฅผ ๊ณ ๋ คํ•˜์—ฌ ๊ฐ ์‚ฌ์šฉ์ž์˜ ์ด๋™ ๊ฒฝ๋กœ๋ฅผ ์˜ˆ์ธกํ•˜๊ณ , ๊ทธ์— ๊ธฐ๋ฐ˜ํ•˜์—ฌ ๊ฐ ์‚ฌ์šฉ์ž ๋ณ„ HO์˜ ๋ชฉ์  AP ์ง‘ํ•ฉ์„ ์„ ํƒํ•œ๋‹ค. ์ œ์•ˆํ•˜๋Š” HO ์Šค์ผ€์ค„ ๊ธฐ๋ฒ•์˜ ์„ค๊ณ„ ๋ชฉ์ ์€ HO ์ง€์—ฐ ์‹œ๊ฐ„์˜ ํ•ฉ์„ ์ตœ์†Œํ™”ํ•˜๊ณ  ๊ฐ AP์—์„œ ํ•ด๋‹น ์ฑ„๋„์„ ์‚ฌ์šฉํ•˜๋ ค๋Š” ์‚ฌ์šฉ์ž ์ˆ˜๋ฅผ ์ค„์ด๋ฉด์„œ WiFi ์—ฐ๊ฒฐ ์‹œ๊ฐ„์„ ์ตœ๋Œ€ํ™”ํ•˜๋Š” ๊ฒƒ์ด๋‹ค. ๋งˆ์ง€๋ง‰์œผ๋กœ, ๋ณธ ๋…ผ๋ฌธ์—์„œ๋Š” ์ค€์ •์  ํ™˜๊ฒฝ์—์„œ ์ œ์•ˆํ•œ ์ฑ„๋„ ํ• ๋‹น ๊ธฐ๋ฒ•๊ณผ UA ๊ธฐ๋ฒ•์˜ ํ˜„์‹ค์„ฑ์„ ์ฆ๋ช…ํ•˜๊ธฐ ์œ„ํ•œ ์‹œํ—˜๋Œ€(testbed)๋ฅผ ๊ตฌ์„ฑํ•˜์˜€๋‹ค. ๋˜ํ•œ, ๊ด‘๋ฒ”์œ„ํ•œ ์‹œ๋ฎฌ๋ ˆ์ด์…˜์„ ํ†ตํ•ด ์ค€์ •์  ํ™˜๊ฒฝ๊ณผ ์ฐจ๋Ÿ‰ ํ™˜๊ฒฝ์—์„œ ์ œ์•ˆํ•œ ๊ธฐ๋ฒ•๋“ค๊ณผ ๊ธฐ์กด์˜ ๊ธฐ๋ฒ•๋“ค์˜ ์„ฑ๋Šฅ์„ ๋น„๊ตํ•˜์˜€๋‹ค.As the IEEE 802.11 (WiFi) becomes the defacto global standard for wireless local area network (WLAN), a huge number of WiFi access points (APs) are deployed. This condition leads to a densely deployed WLANs. In such environment, the conflicting channel allocation between the neighboring access points (APs) is unavoidable, which causes the channel sharing and interference between APs. Thus, the channel allocation (channelization) scheme has a critical role to tackle this issue. In addition, when densely-deployed APs covering a certain area are managed by a single organization, there can exist multiple candidate APs for serving a user. In this case, the user association (UA), i.e., the selection of serving AP, holds a key role in the network performance both in quasi-static and vehicular environments. To improve the performance of WiFi in a densely deployed WLANs environment, we propose a channelization scheme. The proposed channelization scheme utilizes the interference graph to assign the channel for each AP and considers channel bonding. Then, given the channel bonding assignment, the primary channel location for each AP is determined by observing whether the AP supports the static or dynamic channel bonding. Meanwhile, the UA problem in the quasi-static and vehicular environments are slightly different. Thus, we devise UA schemes both for quasi-static and vehicular environments. The UA schemes for quasi-static environment takes account the load balancing among APs and energy saving, considering various techniques for performance improvement, such as multicast transmission, multi-user MIMO, and AP sleeping, together. Then, we formulate the problem into a multi-objective optimization and get the solution as the UA scheme. On the other hand, the UA scheme in the vehicular environment is realized through handover (HO) scheduling mechanism. Specifically, we propose a HO scheduling scheme running on a server, which determines the AP to which a user will be handed over, considering the road topology. Since a user only needs to decide when to initiate the connection to the next AP, a very fast and efficient HO in the vehicular environment can be realized. For this purpose, we utilize the graph modeling technique to map the relation between APs within the road. We consider a practical scenario where the structure of the road is complex, which includes straight, curve, intersection, and u-turn area. Then, the set of target APs for HO are selected for each user moving on a particular road based-on its moving path which is predicted considering the road topology. The design objective of the proposed HO scheduling is to maximize the connection time on WiFi while minimizing the total HO latency and reducing the number of users which contend for the channel within an AP. Finally, we develop a WLAN testbed to demonstrate the practicality and feasibility of the proposed channelization and UA scheme in a quasi-static environment. Furthermore, through extensive simulations, we compare the performance of the proposed schemes with the existing schemes both in quasi-static and vehicular environments.1 Introduction 1.1 Background and Motivation 1.2 Related Works 1.3 Research Scope and Proposed Schemes 1.3.1 Centralized Channelization Scheme for Wireless LANs Exploiting Channel Bonding 1.3.2 User Association for Load Balancing and Energy Saving in Enterprise WLAN 1.3.3 A Graph-Based Handover Scheduling for Heterogenous Vehicular Networks 1.4 Organization 2 Centralized Channelization Scheme for Wireless LANs Exploiting Channel Bonding 2.1 System Model 2.2 Channel Sharing and Bonding 2.2.1 Interference between APs 2.2.2 Channel Sharing 2.2.3 Channel Bonding 2.3 Channelization Scheme 2.3.1 Building Interference Graph 2.3.2 Channel Allocation 2.3.3 Primary Channel Selection 2.4 Implementation 3 User Association for Load Balancing and Energy Saving in Enterprise Wireless LANs 3.1 System Model 3.1.1 IEEE 802.11 ESS-based Enterprise WLAN 3.1.2 Downlink Achievable Rate for MU-MIMO Groups 3.1.3 Candidate MU-MIMO Groups 3.2 User Association Problem 3.2.1 Factors of UA Objective 3.2.2 Problem Formulation 3.3 User Association Scheme 3.3.1 Equivalent Linear Problem 3.3.2 Solution Algorithm 3.3.3 Computational Complexity (Execution Time) 3.4 Implementation 4 A Graph-Based Handover Scheduling for Heterogenous Vehicular Networks 4.1 System Model 4.2 Graph-Based Modeling 4.2.1 Division of Road Portion into Road Segments 4.2.2 Relation between PoAs on a Road Segment 4.2.3 Directed Graph Representation 4.3 Handover Scheduling Problem 4.3.1 Problem Formulation 4.3.2 Weight of Edge 4.3.3 HO Scheduling Algorithm 4.4 Handover Scheduling Operation 4.4.1 HO Schedule Delivery 4.4.2 HO Triggering and Execution 4.4.3 Communication Overhead 5 Performance Evaluation 5.1 CentralizedChannelizationSchemeforWirelessLANsExploitingChannel Bonding 5.1.1 Experiment Settings 5.1.2 Comparison Schemes 5.1.3 Preliminary Experiment for Building Interference Graph 5.1.4 Experiment Results 5.2 User Association for Load Balancing and Energy Saving in Enterprise Wireless LANs 5.2.1 Performance Metrics 5.2.2 Experiment Settings 5.2.3 Experiment Results 5.2.4 Simulation Settings 5.2.5 Comparison Schemes 5.2.6 Simulation Results 5.2.7 Simulation for MU-MIMO System 5.3 A Graph-BasedHandover Scheduling for Heterogenous Vehicular Networks 5.3.1 Performance Metrics 5.3.2 Simulation Settings 5.3.3 Simulation Results 6 Conculsion Bibliography AcknowledgementsDocto

    A novel multipath-transmission supported software defined wireless network architecture

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    The inflexible management and operation of today\u27s wireless access networks cannot meet the increasingly growing specific requirements, such as high mobility and throughput, service differentiation, and high-level programmability. In this paper, we put forward a novel multipath-transmission supported software-defined wireless network architecture (MP-SDWN), with the aim of achieving seamless handover, throughput enhancement, and flow-level wireless transmission control as well as programmable interfaces. In particular, this research addresses the following issues: 1) for high mobility and throughput, multi-connection virtual access point is proposed to enable multiple transmission paths simultaneously over a set of access points for users and 2) wireless flow transmission rules and programmable interfaces are implemented into mac80211 subsystem to enable service differentiation and flow-level wireless transmission control. Moreover, the efficiency and flexibility of MP-SDWN are demonstrated in the performance evaluations conducted on a 802.11 based-testbed, and the experimental results show that compared to regular WiFi, our proposed MP-SDWN architecture achieves seamless handover and multifold throughput improvement, and supports flow-level wireless transmission control for different applications

    Frequency-aware rate adaptation and MAC protocol

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    There has been burgeoning interest in wireless technologies that can use wider frequency spectrum. Technology advances, such as 802.11n and ultra-wideband (UWB), are pushing toward wider frequency bands. The analog-to-digital TV transition has made 100-250 MHz of digital whitespace bandwidth available for unlicensed access. Also, recent work on WiFi networks has advocated discarding the notion of channelization and allowing all nodes to access the wide 802.11 spectrum in order to improve load balancing. This shift towards wider bands presents an opportunity to exploit frequency diversity. Specifically, frequencies that are far from each other in the spectrum have significantly different SNRs, and good frequencies differ across sender-receiver pairs. This paper presents FARA, a combined frequency-aware rate adaptation and MAC protocol. FARA makes three departures from conventional wireless network design: First, it presents a scheme to robustly compute per-frequency SNRs using normal data transmissions. Second, instead of using one bit rate per link, it enables a sender to adapt the bitrate independently across frequencies based on these per-frequency SNRs. Third, in contrast to traditional frequency-oblivious MAC protocols, it introduces a MAC protocol that allocates to a sender-receiver pair the frequencies that work best for that pair. We have implemented FARA in FPGA on a wideband 802.11-compatible radio platform. Our experiments reveal that FARA provides a 3.1x throughput improvement in comparison to frequency-oblivious systems that occupy the same spectrum.Industrial Technology Research InstituteNational Science Foundation (U.S.)
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