The Experts below are selected from a list of 5484 Experts worldwide ranked by ideXlab platform
Alberto Leon-garcia - One of the best experts on this subject based on the ideXlab platform.
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Statistical Multiplexing, admission region, and contention window optimization in multiclass wireless LANs
Wireless Networks, 2007Co-Authors: Yu Cheng, Xinhua Ling, Lin Cai, Wei Song, Weihua Zhuang, Xuemin Shen, Alberto Leon-garciaAbstract:This paper presents an analytical model for evaluating the Statistical Multiplexing effect, admission region, and contention window design in multiclass wireless local area networks (WLANs). We consider distributed medium access control (MAC) which provisions service differentiation by assigning different contention windows to different classes. Mobile nodes belonging to different classes may have heterogeneous traffic arrival processes with different quality of service (QoS) requirements. With bursty input traffic, e.g. on/off sources, our analysis shows that the WLAN admission region under the QoS constraint can be significantly improved, when the Statistical Multiplexing effect is taken into account. We also analyze the MAC resource sharing between the short-range dependent (SRD) on/off sources and the long-range dependent (LRD) fractional Brownian motion (FBM) traffic, where the impact of the Hurst parameter on the admission region is investigated. Moveover, we demonstrate that the proper selection of contention windows plays an important role in improving the WLAN's QoS capability, while the optimal contention window for each class and the maximum admission region can be jointly solved in our analytical model. The analysis accuracy and the resource utilization improvement from Statistical Multiplexing gain and contention window optimization are demonstrated by extensive numerical results.
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QSHINE - Statistical Multiplexing, admission region, and contention window optimization in multiclass wireless LANs
Proceedings of the 3rd international conference on Quality of service in heterogeneous wired wireless networks - QShine '06, 2006Co-Authors: Yu Cheng, Xinhua Ling, Lin Cai, Wei Song, Weihua Zhuang, Xuemin Shen, Alberto Leon-garciaAbstract:This paper presents an analytical model for evaluating the Statistical Multiplexing effect, admission region, and contention window design in multiclass wireless LANs (WLANs). We consider a distributed medium access control (MAC) which provisions service differentiation via contention window differentiation, where mobile nodes belonging to different service classes have different quality of service (QoS) requirements. With bursty input traffic, we show that the WLAN admission region under the QoS constraint can be significantly improved by exploiting the Statistical Multiplexing gain. Moreover, the Statistical Multiplexing gain can be further improved by aggregating the downlink flows at the access point (AP). We also demonstrate that the selection of contention windows plays an important role in improving the WLAN's QoS capability, while the optimal contention window for each class and the maximum admission region can be jointly solved from our analytical model. The analysis accuracy and the resource utilization improvement are demonstrated by extensive numerical results.
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GLOBECOM - Improvement of WLAN QoS Capability via Statistical Multiplexing
2006Co-Authors: Yu Cheng, Xinhua Ling, Lin Cai, Wei Song, Weihua Zhuang, Xuemin Shen, Alberto Leon-garciaAbstract:This paper presents an analytical model for eval- uating the capability of wireless LANs (WLANs) to provision quantitative quality of service (QoS) guarantees. We consider a distributed medium access control (MAC) with class differentia- tion, where mobile nodes belonging to different classes may have heterogeneous traffic arrival processes or different contention windows. With on/off inputs, our analysis shows that the WLAN admission region under the QoS constraint can be significantly improved, when the Statistical Multiplexing effect is taken into account. Moreover, the Statistical Multiplexing gain can be further improved by aggregating the downlink flows at the access point (AP). We also demonstrate that the proper selection of contention windows plays an important role in improving the WLAN QoS capability, while the optimal contention window for each class and the maximum admission region can be jointly solved in our analytical model.
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WLC15-1: Improvement of WLAN QoS Capability via Statistical Multiplexing
IEEE Globecom 2006, 2006Co-Authors: Yu Cheng, Xinhua Ling, Lin Cai, Wei Song, Weihua Zhuang, Xuemin Shen, Alberto Leon-garciaAbstract:This paper presents an analytical model for evaluating the capability of wireless LANs (WLANs) to provision quantitative quality of service (QoS) guarantees. We consider a distributed medium access control (MAC) with class differentiation, where mobile nodes belonging to different classes may have heterogeneous traffic arrival processes or different contention windows. With on/off inputs, our analysis shows that the WLAN admission region under the QoS constraint can be significantly improved, when the Statistical Multiplexing effect is taken into account. Moreover, the Statistical Multiplexing gain can be further improved by aggregating the downlink flows at the access point (AP). We also demonstrate that the proper selection of contention windows plays an important role in improving the WLAN QoS capability, while the optimal contention window for each class and the maximum admission region can be jointly solved in our analytical model.
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Statistical Multiplexing of VBR MPEG sources under credit-based flow control
Multimedia Computing and Networking 1996, 1996Co-Authors: Siavash Khorsandi, Alberto Leon-garciaAbstract:Due to Statistical Multiplexing in ATM networks, a large number of cells may be lost during the periods of network congestion. It is a common perception that feedback congestion control mechanisms do not work well for delay sensitive applications such as video transfer. The proposed approaches to avoid congestion in video applications are mainly based on constant bit-rate transmission. However, these schemes impose a delay in the order of a frame time. Besides, the network utilization is reduced since bandwidth allocation at peak rate is necessary. Variable bit rate (VBR) coding of video signals is more efficient both in terms of coding delay and bandwidth utilization. In this paper, we demonstrate that using credit-based flow control together with a selective cell discarding mechanism, VBR video signals coded according to the MPEG standard can be Statistically multiplexed with a very high efficiency. Both cell delay and cell loss guarantees can be made while achieving a high network utilization. A throughput of up to 83 percent has been achieved with a cell loss rate of under 10-5 and maximum end-to-end cell queuing delay of 15 milliseconds in the Statistical Multiplexing scenarios under consideration. Since credit-based flow control works well for data applications, its successful deployment for video applications will pave the way for an integrated congestion control protocol.© (1996) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.
Yu Cheng - One of the best experts on this subject based on the ideXlab platform.
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Statistical Multiplexing, admission region, and contention window optimization in multiclass wireless LANs
Wireless Networks, 2007Co-Authors: Yu Cheng, Xinhua Ling, Lin Cai, Wei Song, Weihua Zhuang, Xuemin Shen, Alberto Leon-garciaAbstract:This paper presents an analytical model for evaluating the Statistical Multiplexing effect, admission region, and contention window design in multiclass wireless local area networks (WLANs). We consider distributed medium access control (MAC) which provisions service differentiation by assigning different contention windows to different classes. Mobile nodes belonging to different classes may have heterogeneous traffic arrival processes with different quality of service (QoS) requirements. With bursty input traffic, e.g. on/off sources, our analysis shows that the WLAN admission region under the QoS constraint can be significantly improved, when the Statistical Multiplexing effect is taken into account. We also analyze the MAC resource sharing between the short-range dependent (SRD) on/off sources and the long-range dependent (LRD) fractional Brownian motion (FBM) traffic, where the impact of the Hurst parameter on the admission region is investigated. Moveover, we demonstrate that the proper selection of contention windows plays an important role in improving the WLAN's QoS capability, while the optimal contention window for each class and the maximum admission region can be jointly solved in our analytical model. The analysis accuracy and the resource utilization improvement from Statistical Multiplexing gain and contention window optimization are demonstrated by extensive numerical results.
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Statistical Multiplexing admission region and contention window optimization in multiclass wireless lans
Quality of Service in Heterogeneous Wired Wireless Networks, 2006Co-Authors: Yu Cheng, Xinhua Ling, Lin Cai, Wei Song, Weihua Zhuang, Xuemin Shen, Alberto LeongarciaAbstract:This paper presents an analytical model for evaluating the Statistical Multiplexing effect, admission region, and contention window design in multiclass wireless LANs (WLANs). We consider a distributed medium access control (MAC) which provisions service differentiation via contention window differentiation, where mobile nodes belonging to different service classes have different quality of service (QoS) requirements. With bursty input traffic, we show that the WLAN admission region under the QoS constraint can be significantly improved by exploiting the Statistical Multiplexing gain. Moreover, the Statistical Multiplexing gain can be further improved by aggregating the downlink flows at the access point (AP). We also demonstrate that the selection of contention windows plays an important role in improving the WLAN's QoS capability, while the optimal contention window for each class and the maximum admission region can be jointly solved from our analytical model. The analysis accuracy and the resource utilization improvement are demonstrated by extensive numerical results.
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QSHINE - Statistical Multiplexing, admission region, and contention window optimization in multiclass wireless LANs
Proceedings of the 3rd international conference on Quality of service in heterogeneous wired wireless networks - QShine '06, 2006Co-Authors: Yu Cheng, Xinhua Ling, Lin Cai, Wei Song, Weihua Zhuang, Xuemin Shen, Alberto Leon-garciaAbstract:This paper presents an analytical model for evaluating the Statistical Multiplexing effect, admission region, and contention window design in multiclass wireless LANs (WLANs). We consider a distributed medium access control (MAC) which provisions service differentiation via contention window differentiation, where mobile nodes belonging to different service classes have different quality of service (QoS) requirements. With bursty input traffic, we show that the WLAN admission region under the QoS constraint can be significantly improved by exploiting the Statistical Multiplexing gain. Moreover, the Statistical Multiplexing gain can be further improved by aggregating the downlink flows at the access point (AP). We also demonstrate that the selection of contention windows plays an important role in improving the WLAN's QoS capability, while the optimal contention window for each class and the maximum admission region can be jointly solved from our analytical model. The analysis accuracy and the resource utilization improvement are demonstrated by extensive numerical results.
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GLOBECOM - Improvement of WLAN QoS Capability via Statistical Multiplexing
2006Co-Authors: Yu Cheng, Xinhua Ling, Lin Cai, Wei Song, Weihua Zhuang, Xuemin Shen, Alberto Leon-garciaAbstract:This paper presents an analytical model for eval- uating the capability of wireless LANs (WLANs) to provision quantitative quality of service (QoS) guarantees. We consider a distributed medium access control (MAC) with class differentia- tion, where mobile nodes belonging to different classes may have heterogeneous traffic arrival processes or different contention windows. With on/off inputs, our analysis shows that the WLAN admission region under the QoS constraint can be significantly improved, when the Statistical Multiplexing effect is taken into account. Moreover, the Statistical Multiplexing gain can be further improved by aggregating the downlink flows at the access point (AP). We also demonstrate that the proper selection of contention windows plays an important role in improving the WLAN QoS capability, while the optimal contention window for each class and the maximum admission region can be jointly solved in our analytical model.
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WLC15-1: Improvement of WLAN QoS Capability via Statistical Multiplexing
IEEE Globecom 2006, 2006Co-Authors: Yu Cheng, Xinhua Ling, Lin Cai, Wei Song, Weihua Zhuang, Xuemin Shen, Alberto Leon-garciaAbstract:This paper presents an analytical model for evaluating the capability of wireless LANs (WLANs) to provision quantitative quality of service (QoS) guarantees. We consider a distributed medium access control (MAC) with class differentiation, where mobile nodes belonging to different classes may have heterogeneous traffic arrival processes or different contention windows. With on/off inputs, our analysis shows that the WLAN admission region under the QoS constraint can be significantly improved, when the Statistical Multiplexing effect is taken into account. Moreover, the Statistical Multiplexing gain can be further improved by aggregating the downlink flows at the access point (AP). We also demonstrate that the proper selection of contention windows plays an important role in improving the WLAN QoS capability, while the optimal contention window for each class and the maximum admission region can be jointly solved in our analytical model.
Martin Reisslein - One of the best experts on this subject based on the ideXlab platform.
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traffic and Statistical Multiplexing characterization of 3 d video representation formats
IEEE Transactions on Broadcasting, 2013Co-Authors: Akshay Pulipaka, Martin Reisslein, Patrick Seeling, Lina J KaramAbstract:The network transport of 3-D video, which contains two views of a video scene, poses significant challenges due to the increased video data, compared to a conventional single-view video. Addressing these challenges requires a thorough understanding of the traffic and Multiplexing characteristics of the different representation formats of a 3-D video. We examine the average bitrate-distortion (RD) and bitrate variability-distortion characteristics of three main representation formats. Specifically, we compare multiview video (MV) representation and encoding, frame sequential (FS) representation, and side-by-side (SBS) representation, whereby conventional single-view encoding is employed for the FS and SBS representations. Our results for long 3-D videos in the full HD format indicate that the MV representation and encoding achieves the highest RD efficiency, while exhibiting the highest bitrate variabilities. We examine the impact of these bitrate variabilities on network transport through extensive Statistical Multiplexing simulations. We find that when Multiplexing a small number of streams, the MV and FS representations require the same bandwidth. However, when Multiplexing a large number of streams or smoothing traffic, the MV representation and encoding reduces the bandwidth requirement relative to the FS representation.
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the effects of priority levels and buffering on the Statistical Multiplexing of single layer h 264 avc and svc encoded video streams
IEEE Transactions on Broadcasting, 2010Co-Authors: Sudhir Kumar Srinivasan, J Vahabzadehhagh, Martin ReissleinAbstract:H.264/Advanced Video Coding (AVC) employs classical bi-directional encoded (B) frames that depend only on intra-coded (I) and predictive encoded (P) frames. In contrast, H.264 Scalable Video Coding (SVC) employs hierarchical B frames that depend on other B frames. A fundamental question is how many priority levels single-layer H.264 video encodings require when the encoded frames are Statistically multiplexed in transport networks. We conduct extensive simulation experiments with a modular Statistical Multiplexing structure to uncover the impact of priority levels for a wide range of Multiplexing policies. For the bufferless Statistical Multiplexing of both H.264/AVC and SVC we find that prioritizing the frames according to the number of dependent frames can increase the number of supported streams up to approximately 8%. In contrast, for buffered Statistical Multiplexing with a relatively small buffer size, frame prioritization does generally not increase the number of supported streams.
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The Effects of Priority Levels and Buffering on the Statistical Multiplexing of Single-Layer H.264/AVC and SVC Encoded Video Streams
IEEE Transactions on Broadcasting, 2010Co-Authors: Sudhir Kumar Srinivasan, J Vahabzadeh-hagh, Martin ReissleinAbstract:H.264/Advanced Video Coding (AVC) employs classical bi-directional encoded (B) frames that depend only on intra-coded (I) and predictive encoded (P) frames. In contrast, H.264 Scalable Video Coding (SVC) employs hierarchical B frames that depend on other B frames. A fundamental question is how many priority levels single-layer H.264 video encodings require when the encoded frames are Statistically multiplexed in transport networks. We conduct extensive simulation experiments with a modular Statistical Multiplexing structure to uncover the impact of priority levels for a wide range of Multiplexing policies. For the bufferless Statistical Multiplexing of both H.264/AVC and SVC we find that prioritizing the frames according to the number of dependent frames can increase the number of supported streams up to approximately 8%. In contrast, for buffered Statistical Multiplexing with a relatively small buffer size, frame prioritization does generally not increase the number of supported streams.
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implications of smoothing on Statistical Multiplexing of h 264 avc and svc video streams
IEEE Transactions on Broadcasting, 2009Co-Authors: G. Van Der Auwera, Martin ReissleinAbstract:While the hierarchical B frames based scalable video coding (SVC) extension of the H.264/AVC standard achieves significantly improved compression over the initial H.264/AVC codec, the SVC video traffic is significantly more variable than H.264/AVC traffic. The higher traffic variability of the SVC encoder can lead to smaller numbers of streams supported with bufferless Statistical Multiplexing than with the H.264/AVC encoder (and even less streams than with the MPEG-4 Part 2 encoder) for prescribed link capacities and loss constraints. In this paper we examine the implications of video traffic smoothing on the numbers of Statistically multiplexed H.264 SVC, H.264/AVC, and MPEG-4 Part 2 streams, the bandwidth requirements for streaming, and the introduced delay. We identify the levels of smoothing that ensure that more H.264 SVC streams than H.264/AVC streams can be supported. For a basic low-complexity smoothing technique that is readily applicable to both live and prerecorded streams, we identify the levels of smoothing that give (bufferless) Statistical Multiplexing performance close to an optimal off-line smoothing technique. We thus characterize the trade-offs between increased smoothing delay and increased Statistical Multiplexing performance for both H.264/AVC, which employs classical B frames, and H.264 SVC, which employs hierarchical B frames. We similarly identify the buffer sizes for the buffered Multiplexing of unsmoothed H.264 SVC, H.264/AVC, and MPEG-4 Part 2 streams that give close to optimal performance.
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Implications of Smoothing on Statistical Multiplexing of H.264/AVC and SVC Video Streams
IEEE Transactions on Broadcasting, 2009Co-Authors: G. Van Der Auwera, Martin ReissleinAbstract:While the hierarchical B frames based scalable video coding (SVC) extension of the H.264/AVC standard achieves significantly improved compression over the initial H.264/AVC codec, the SVC video traffic is significantly more variable than H.264/AVC traffic. The higher traffic variability of the SVC encoder can lead to smaller numbers of streams supported with bufferless Statistical Multiplexing than with the H.264/AVC encoder (and even less streams than with the MPEG-4 Part 2 encoder) for prescribed link capacities and loss constraints. In this paper we examine the implications of video traffic smoothing on the numbers of Statistically multiplexed H.264 SVC, H.264/AVC, and MPEG-4 Part 2 streams, the bandwidth requirements for streaming, and the introduced delay. We identify the levels of smoothing that ensure that more H.264 SVC streams than H.264/AVC streams can be supported. For a basic low-complexity smoothing technique that is readily applicable to both live and prerecorded streams, we identify the levels of smoothing that give (bufferless) Statistical Multiplexing performance close to an optimal off-line smoothing technique. We thus characterize the trade-offs between increased smoothing delay and increased Statistical Multiplexing performance for both H.264/AVC, which employs classical B frames, and H.264 SVC, which employs hierarchical B frames. We similarly identify the buffer sizes for the buffered Multiplexing of unsmoothed H.264 SVC, H.264/AVC, and MPEG-4 Part 2 streams that give close to optimal performance.
Zhisheng Niu - One of the best experts on this subject based on the ideXlab platform.
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Statistical Multiplexing gain analysis of heterogeneous virtual base station pools in cloud radio access networks
IEEE Transactions on Wireless Communications, 2016Co-Authors: Jingchu Liu, Sheng Zhou, Jie Gong, Zhisheng NiuAbstract:Cloud radio access network (C-RAN) was proposed recently to reduce network cost, enable cooperative communications, and increase system flexibility through centralized baseband processing. By pooling multiple virtual base stations (VBSs) and consolidating their stochastic computational tasks, the overall computational resource can be reduced, achieving the so-called Statistical Multiplexing gain. In this paper, we evaluate the Statistical Multiplexing gain of VBS pools using a multi-dimensional Markov model, which captures the session-level dynamics and the constraints imposed by both radio and computational resources. Based on this model, we derive a recursive formula for the blocking probability and also a closed-form approximation for it in large pools. These formulas are then used to derive the session-level Statistical Multiplexing gain of both real-time and delay-tolerant traffic. Numerical results show that VBS pools can achieve more than 75% of the maximum pooling gain with 50 VBSs, but further convergence to the upper bound (large-pool limit) is slow because of the quickly diminishing marginal pooling gain, which is inversely proportional to a factor between the one-half and three-fourth power of the pool size. We also find that the pooling gain is more evident under light traffic load and stringent quality of service requirement.
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on the Statistical Multiplexing gain of virtual base station pools
Global Communications Conference, 2014Co-Authors: Jingchu Liu, Sheng Zhou, Jie Gong, Zhisheng NiuAbstract:Facing the explosion of mobile data traffic, cloud radio access network (C-RAN) is proposed recently to overcome the efficiency and flexibility problems with the traditional RAN architecture by centralizing baseband processing. However, there lacks a mathematical model to analyze the Statistical Multiplexing gain from the pooling of virtual base stations (VBSs) so that the expenditure on fronthaul networks can be justified. In this paper, we address this problem by capturing the session-level dynamics of VBS pools with a multi-dimensional Markov model. This model reflects the constraints imposed by both radio resources and computational resources. To evaluate the pooling gain, we derive a product-form solution for the stationary distribution and give a recursive method to calculate the blocking probabilities. For comparison, we also derive the limit of resource utilization ratio as the pool size approaches infinity. Numerical results show that VBS pools can obtain considerable pooling gain readily at medium size, but the convergence to large pool limit is slow because of the quickly diminishing marginal pooling gain. We also find that parameters such as traffic load and desired Quality of Service (QoS) have significant influence on the performance of VBS pools.
Xuemin Shen - One of the best experts on this subject based on the ideXlab platform.
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Statistical Multiplexing, admission region, and contention window optimization in multiclass wireless LANs
Wireless Networks, 2007Co-Authors: Yu Cheng, Xinhua Ling, Lin Cai, Wei Song, Weihua Zhuang, Xuemin Shen, Alberto Leon-garciaAbstract:This paper presents an analytical model for evaluating the Statistical Multiplexing effect, admission region, and contention window design in multiclass wireless local area networks (WLANs). We consider distributed medium access control (MAC) which provisions service differentiation by assigning different contention windows to different classes. Mobile nodes belonging to different classes may have heterogeneous traffic arrival processes with different quality of service (QoS) requirements. With bursty input traffic, e.g. on/off sources, our analysis shows that the WLAN admission region under the QoS constraint can be significantly improved, when the Statistical Multiplexing effect is taken into account. We also analyze the MAC resource sharing between the short-range dependent (SRD) on/off sources and the long-range dependent (LRD) fractional Brownian motion (FBM) traffic, where the impact of the Hurst parameter on the admission region is investigated. Moveover, we demonstrate that the proper selection of contention windows plays an important role in improving the WLAN's QoS capability, while the optimal contention window for each class and the maximum admission region can be jointly solved in our analytical model. The analysis accuracy and the resource utilization improvement from Statistical Multiplexing gain and contention window optimization are demonstrated by extensive numerical results.
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Statistical Multiplexing admission region and contention window optimization in multiclass wireless lans
Quality of Service in Heterogeneous Wired Wireless Networks, 2006Co-Authors: Yu Cheng, Xinhua Ling, Lin Cai, Wei Song, Weihua Zhuang, Xuemin Shen, Alberto LeongarciaAbstract:This paper presents an analytical model for evaluating the Statistical Multiplexing effect, admission region, and contention window design in multiclass wireless LANs (WLANs). We consider a distributed medium access control (MAC) which provisions service differentiation via contention window differentiation, where mobile nodes belonging to different service classes have different quality of service (QoS) requirements. With bursty input traffic, we show that the WLAN admission region under the QoS constraint can be significantly improved by exploiting the Statistical Multiplexing gain. Moreover, the Statistical Multiplexing gain can be further improved by aggregating the downlink flows at the access point (AP). We also demonstrate that the selection of contention windows plays an important role in improving the WLAN's QoS capability, while the optimal contention window for each class and the maximum admission region can be jointly solved from our analytical model. The analysis accuracy and the resource utilization improvement are demonstrated by extensive numerical results.
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QSHINE - Statistical Multiplexing, admission region, and contention window optimization in multiclass wireless LANs
Proceedings of the 3rd international conference on Quality of service in heterogeneous wired wireless networks - QShine '06, 2006Co-Authors: Yu Cheng, Xinhua Ling, Lin Cai, Wei Song, Weihua Zhuang, Xuemin Shen, Alberto Leon-garciaAbstract:This paper presents an analytical model for evaluating the Statistical Multiplexing effect, admission region, and contention window design in multiclass wireless LANs (WLANs). We consider a distributed medium access control (MAC) which provisions service differentiation via contention window differentiation, where mobile nodes belonging to different service classes have different quality of service (QoS) requirements. With bursty input traffic, we show that the WLAN admission region under the QoS constraint can be significantly improved by exploiting the Statistical Multiplexing gain. Moreover, the Statistical Multiplexing gain can be further improved by aggregating the downlink flows at the access point (AP). We also demonstrate that the selection of contention windows plays an important role in improving the WLAN's QoS capability, while the optimal contention window for each class and the maximum admission region can be jointly solved from our analytical model. The analysis accuracy and the resource utilization improvement are demonstrated by extensive numerical results.
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GLOBECOM - Improvement of WLAN QoS Capability via Statistical Multiplexing
2006Co-Authors: Yu Cheng, Xinhua Ling, Lin Cai, Wei Song, Weihua Zhuang, Xuemin Shen, Alberto Leon-garciaAbstract:This paper presents an analytical model for eval- uating the capability of wireless LANs (WLANs) to provision quantitative quality of service (QoS) guarantees. We consider a distributed medium access control (MAC) with class differentia- tion, where mobile nodes belonging to different classes may have heterogeneous traffic arrival processes or different contention windows. With on/off inputs, our analysis shows that the WLAN admission region under the QoS constraint can be significantly improved, when the Statistical Multiplexing effect is taken into account. Moreover, the Statistical Multiplexing gain can be further improved by aggregating the downlink flows at the access point (AP). We also demonstrate that the proper selection of contention windows plays an important role in improving the WLAN QoS capability, while the optimal contention window for each class and the maximum admission region can be jointly solved in our analytical model.
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WLC15-1: Improvement of WLAN QoS Capability via Statistical Multiplexing
IEEE Globecom 2006, 2006Co-Authors: Yu Cheng, Xinhua Ling, Lin Cai, Wei Song, Weihua Zhuang, Xuemin Shen, Alberto Leon-garciaAbstract:This paper presents an analytical model for evaluating the capability of wireless LANs (WLANs) to provision quantitative quality of service (QoS) guarantees. We consider a distributed medium access control (MAC) with class differentiation, where mobile nodes belonging to different classes may have heterogeneous traffic arrival processes or different contention windows. With on/off inputs, our analysis shows that the WLAN admission region under the QoS constraint can be significantly improved, when the Statistical Multiplexing effect is taken into account. Moreover, the Statistical Multiplexing gain can be further improved by aggregating the downlink flows at the access point (AP). We also demonstrate that the proper selection of contention windows plays an important role in improving the WLAN QoS capability, while the optimal contention window for each class and the maximum admission region can be jointly solved in our analytical model.
