泛在网关联控制问题研究
|
摘要
泛在网扩展了传统通信网络的概念,突破了不同通信网络之间的界限,将封闭的网络个体融合贯通为一个整体,这不仅是网络区域的叠加,还是终端的汇集以及网络业务、数据和协议等的融合。在泛在网中,一方面各个异构子网彼此融会相互协调,联合提供了透明的无缝移动接入环境；另一方面各种业务自动适配充分交互,一同创造了丰富的业务资源。这些极大地提高了网络服务能力,并给终端提供了更广泛的选择外延。但是,网络和业务环境所呈现的复杂性和扩展的选择空间也给网络资源管理带来了许多新的挑战。这其中的一个突出困难就是如何智能有效地配置终端和网络间的关联关系,该配置过程即为网络关联控制机制。
对于网络关联控制机制的研究,已有众多切实可行的解决方案。但泛在网的出现为网络环境引入了更多新的特性并且给网络服务提出了新的要求,因此泛在网关联控制机制不会局限于既有的边界,而将在一个更大问题维度上进行解决。这不仅包括如何将终端关联到接入条件满足的网络中,还将面对在复杂的网络和业务环境中的协同优化问题。为此本文对泛在网关联控制问题进行了研究,以提出行之有效解决方案提高网络资源的利用率,保证终端的业务体验。具体来说,本文分别针对泛在网下不同的网络场景提出了基于链路稳定、内容感知、传输时效以及移动支持的关联控制机制,以解决不同场景下的突出问题。本文主要研究内容如下：
●基于链路稳定的关联控制问题研究
本文首先考虑了泛在网的低速移动网络场景中的关联控制问题。当终端在泛在网中停留或低速移动时,由于网络间迁移和链路质量下降而引起的频繁的重关联会导致延迟的增长,另外泛在网终端分布的不均衡性也会导致网络负载失衡进而影响整个网络效率。由频繁切换带来的延迟和网络过载引起的链路拥塞是影响链路稳定的两个主要因素。已有的关联控制研究工作主要关注于如何减少终端单次切换延迟和增加关联时长,很少有研究将移动终端切换延迟和网络负载均衡等影响链路稳定的主要因素进行联合考虑。为此,我们研究了基于链路稳定的泛在网关联控制问题,该问题的目标是通过智能的接入点和用户间的配对来降低终端切换次数并均衡负载。由于此问题具有NP-hard复杂性,我们分别提出一个集中式近似算法和一个分布式近似算法将问题加以解决。最后,基于真实轨迹数据的仿真实验验证了算法的性能。
●基于内容感知的关联控制问题研究
本文接着考虑了泛在网的准静态网络场景中关联控制问题。泛在网业务环境极其复杂,其关联控制机制需亟待解决的问题是如何满足异构业务差异化的服务质量需求并同时均衡网络负载。由于传统网络环境中业务的单一性,已有的关联控制研究工作主要关注与如何提高网络吞吐量并在终端间建立公平性,很少有工作将不同业务具有差异化的QOS需求这个因素引入其中,以及进一步将业务差异化QoS需求和网络负载均衡联合考虑。为此,我们研究了基于内容感知的泛在网关联控制问题,以满足不同业务的差异化QOS需求并同时均衡网络的负载。由于该问题具有NP-hard复杂性,我们提出两个近似算法将问题加以解决。最后,算法在多种业务并存的网络中进行仿真验证,仿真结果证明了算法的性能。
●基于传输时效的关联控制问题研究
同样是在泛在网的准静态网络场景中,由于泛在网中数据量的激增以及对数据传输时效性要求的提高,其关联控制机制还需解决如何提高数据传输量以及如何减少数据传输延迟的问题。这对泛在网中广泛存在的实时类业务尤为重要。一方面受传统网络业务规模和容量的限制,已有的致力于提高传输时效性的研究工作主要针对单个网络接入点或单条链路；另一方面受传统网络业务单一性的影响,已有的关联控制研究工作主要关注提高网络的吞吐量和负载均衡,很少有研究将传输时效性考虑其中,以及进一步对各个实时类业务进行联合资源配置。为此,我们研究了基于传输时效的泛在网关联控制问题,该问题目的在于设计一种根据业务传输时效将网络接入点和终端智能匹配以来提高业务传输时效,保证实时业务的连续性。由于该问题被证明为具有NP-hard复杂性。我们提出两个近似算法将问题加以解决。我们最后对算法进行了网络仿真实验,仿真结果证明了算法的性能。
●基于移动支持的关联控制问题研究
本文最后考虑了泛在网的高速移动网络场景中关联控制问题。由于高速移动网络的网络拓扑变化迅速,负载均衡不是其主要目标。高速移动网络场景的典型代表是车载网,本文以车载网为例研究泛在网中此场景下关联控制问题。过多的切换次数会给车载终端业务带来很高的传输延迟,同时无线信道的不稳定性随着车载终端位置的剧烈变化也会进一步恶化,导致网络链接频频中断。另一方面,不同于传统无线网络环境,车载网的间歇性特征使得一切力图获得长期稳定传输带宽的努力落空。当前很少有关于车载网关联管制机制的研究工作,这使得车载网一直饱受链路不稳定以及低吞吐量的困扰,很大程度上影响了其商业部署。为此,我们研究了基于移动支持的关联控制问题,该问题目标为利用有效的算法减少终端切换次数,降低链路中断频率以及提高网络吞吐量。我们提出两个在线启发式算法来解决此问题。这两个算法实现简单,利于部署。最后,通过车载网仿真环境的实验验证了算法的性能。
Ubiquitous network extends the traditional concept of a communication network, breaks the boundaries between different communication networks and combines individual closed networks as a whole. Ubiquitous network is not only in the area of overlay networks, but also a complex of many things, such as terminals, services, data and protocols.On the one hand, each heterogeneous subnet in ubiquitous network coordinates with each other to jointly provide a transparent and seamless mobile network access environment. On the other hand, various services are fully interactive and adaptable automatically, which together create a wealth of service resources. These functions of ubiquitous network greatly improve the network service capabilities and provide terminals greater choices. However, the complexity and extensiveness of network and service bring many new challenges for network resource management. One of these challenges is how to effectively configure intelligent association relationship between the terminal and the network which is called network association control mechanisms.
There have been lots of researches of network association control mechanisms that produce many practical solutions. However, the introductions of ubiquitous network appear as a network environment with more new features and services with new requirements. Therefore, the association control mechanisms of ubiquitous network are not confined to the existing boundaries, and will solve the problem on a larger dimension. This includes not only how to associate the terminals to available networks, but also encountering the collaborative optimization problems in a complex networks and services environment. In this thesis, the association control mechanisms of ubiquitous network are intensively studies to effectively improve the utilization of network resources and the service experiences of terminals. Specifically, this thesis proposes link stability based, content-aware based, transmission timeliness based and mobility supporting based association control mechanisms respectively in order to resolve the outstanding problems for different network scenarios. The main contents are as follows.
Link stability based association control in ubiquitous network
To begin with, this thesis studies the association control problem in low-speed mobile scenarios of ubiquitous network. When the terminals stay or move slowly in the ubiquitous network, the re-association due to the network migration and the degradation of link quality will lead to the increase of delay. Apart from that, the distribution imbalance of terminals in ubiquitous network will cause the imbalance load of networks and in turn affect the entire network efficiency. The delay caused by frequent handoffs and link congestion due to network overload are two main factors that damage the stability of the link. Existing research works on association control problems are mainly focus on reducing the delay of a single terminal handoff and increasing the duration of association, few of them take into account the joint effects of terminal handoff latency and network load balancing. To this end, we have studied the link stability based association control in ubiquitous network with the purposes of reducing terminal handoff frequency and balancing the network load through intelligent match between networks and terminals. Since the target problem is NP-hard, two constant approximation algorithms are presented to resolve it. Finally, trace based evaluations are conducted to demonstrate the effectiveness of our algorithms.
Content-aware based association control in ubiquitous network
Besides, this thesis explores the association control problem in quasi-static scenarios of ubiquitous network. Ubiquitous network has a extremely complex service environment, and its key problems needed to resolve by association control are meeting the differential requirements of heterogeneous services while balancing the network load. Because of the lacking variety of services in traditional networks, existing research works on association control problems are chiefly concentrate on improving the throughput of network and establishing a fair resource allocation scheme among terminals. There is few effort to investigate the diversity of QoS requirements of heterogeneous services, and further consider jointly on the optimization between differential QoS requirements of services and network load balancing. In this respect, we have studied the content-aware based association control in ubiquitous network with the goal of meeting the differential QoS requirements for every individual service and balancing the network load. Since this problem belongs to NP hard, we then propose two approximation algorithms to resolve it. Finally, algorithms are evaluated in a network allowed several services. The results verify the performance of our algorithm.
Transmission timeliness based association control in ubiquitous network
Also in quasi-static scenarios of ubiquitous network, as the surge in the amount of data and higher requirement of improving the timeliness of data transmission, the association control mechanisms need to increase the throughput and reduce transmission delay. This is particularly important for widespread real time services in ubiquitous network. Due to the restricted size and capacity of traditional network services, the efforts committed to improving the timeliness of transmission mainly aim at a single access point or a single link. Apart from this, real time services are not widely deployed in traditional networks, with the results that existing research works on association control problems are chiefly concentrate on improving the throughput of network and balancing the network load. Few of the methods are conducted to incorporate transmission timeliness, and take another step forward in joint resource allocation for real time services. For this reason, we have explored the transmission timeliness based association control in ubiquitous network which targets at increasing the timeliness of service transmission and thus guaranteeing the continuity of service. After proof that the target problem is NP hard, we put forward two approximation algorithms to solve it. Finally, extensive evaluations show that the proposed algorithms have good performance.
Mobility supporting based association control in ubiquitous network
Last, this thesis studies the association control problem in high-speed mobile scenarios of ubiquitous network. Since the topology of high-speed mobile network changes rapidly, load balancing is not a primary objective. The typical representative of high-speed mobile network scenario is vehicular network. In this thesis, we take vehicular network for example in studying the association control problems in high-speed mobile scenario of ubiquitous network. Excessive handoff frequency will bring high transmission delay to vehicular terminal services, while the instability of radio channel as well as the dramatic changes in vehicular terminal location will further deteriorate, leading to frequent interruptions for network links. In addition to this, unlike traditional wireless networks, the intermittent feature of vehicular network makes every work that tries to get long-term stability of the bandwidth nothing. There is little research on the association control mechanisms in vehicular network, which makes the vehicular network plagued by link instability and low throughput, and further handicaps the commercial deployments of vehicular networks. With regards to this, we have studied the mobility supporting based association control in ubiquitous network with the objective of decreasing the number of terminal handoffs, reducing the frequency of link interruptions and improving the network throughput. Two heuristic online algorithms are presented to resolve the target problem. Finally, comprehensive evaluations are conducted in vehicular simulation network to demonstrate the effectiveness of our algorithms.
对于网络关联控制机制的研究,已有众多切实可行的解决方案。但泛在网的出现为网络环境引入了更多新的特性并且给网络服务提出了新的要求,因此泛在网关联控制机制不会局限于既有的边界,而将在一个更大问题维度上进行解决。这不仅包括如何将终端关联到接入条件满足的网络中,还将面对在复杂的网络和业务环境中的协同优化问题。为此本文对泛在网关联控制问题进行了研究,以提出行之有效解决方案提高网络资源的利用率,保证终端的业务体验。具体来说,本文分别针对泛在网下不同的网络场景提出了基于链路稳定、内容感知、传输时效以及移动支持的关联控制机制,以解决不同场景下的突出问题。本文主要研究内容如下：
●基于链路稳定的关联控制问题研究
本文首先考虑了泛在网的低速移动网络场景中的关联控制问题。当终端在泛在网中停留或低速移动时,由于网络间迁移和链路质量下降而引起的频繁的重关联会导致延迟的增长,另外泛在网终端分布的不均衡性也会导致网络负载失衡进而影响整个网络效率。由频繁切换带来的延迟和网络过载引起的链路拥塞是影响链路稳定的两个主要因素。已有的关联控制研究工作主要关注于如何减少终端单次切换延迟和增加关联时长,很少有研究将移动终端切换延迟和网络负载均衡等影响链路稳定的主要因素进行联合考虑。为此,我们研究了基于链路稳定的泛在网关联控制问题,该问题的目标是通过智能的接入点和用户间的配对来降低终端切换次数并均衡负载。由于此问题具有NP-hard复杂性,我们分别提出一个集中式近似算法和一个分布式近似算法将问题加以解决。最后,基于真实轨迹数据的仿真实验验证了算法的性能。
●基于内容感知的关联控制问题研究
本文接着考虑了泛在网的准静态网络场景中关联控制问题。泛在网业务环境极其复杂,其关联控制机制需亟待解决的问题是如何满足异构业务差异化的服务质量需求并同时均衡网络负载。由于传统网络环境中业务的单一性,已有的关联控制研究工作主要关注与如何提高网络吞吐量并在终端间建立公平性,很少有工作将不同业务具有差异化的QOS需求这个因素引入其中,以及进一步将业务差异化QoS需求和网络负载均衡联合考虑。为此,我们研究了基于内容感知的泛在网关联控制问题,以满足不同业务的差异化QOS需求并同时均衡网络的负载。由于该问题具有NP-hard复杂性,我们提出两个近似算法将问题加以解决。最后,算法在多种业务并存的网络中进行仿真验证,仿真结果证明了算法的性能。
●基于传输时效的关联控制问题研究
同样是在泛在网的准静态网络场景中,由于泛在网中数据量的激增以及对数据传输时效性要求的提高,其关联控制机制还需解决如何提高数据传输量以及如何减少数据传输延迟的问题。这对泛在网中广泛存在的实时类业务尤为重要。一方面受传统网络业务规模和容量的限制,已有的致力于提高传输时效性的研究工作主要针对单个网络接入点或单条链路；另一方面受传统网络业务单一性的影响,已有的关联控制研究工作主要关注提高网络的吞吐量和负载均衡,很少有研究将传输时效性考虑其中,以及进一步对各个实时类业务进行联合资源配置。为此,我们研究了基于传输时效的泛在网关联控制问题,该问题目的在于设计一种根据业务传输时效将网络接入点和终端智能匹配以来提高业务传输时效,保证实时业务的连续性。由于该问题被证明为具有NP-hard复杂性。我们提出两个近似算法将问题加以解决。我们最后对算法进行了网络仿真实验,仿真结果证明了算法的性能。
●基于移动支持的关联控制问题研究
本文最后考虑了泛在网的高速移动网络场景中关联控制问题。由于高速移动网络的网络拓扑变化迅速,负载均衡不是其主要目标。高速移动网络场景的典型代表是车载网,本文以车载网为例研究泛在网中此场景下关联控制问题。过多的切换次数会给车载终端业务带来很高的传输延迟,同时无线信道的不稳定性随着车载终端位置的剧烈变化也会进一步恶化,导致网络链接频频中断。另一方面,不同于传统无线网络环境,车载网的间歇性特征使得一切力图获得长期稳定传输带宽的努力落空。当前很少有关于车载网关联管制机制的研究工作,这使得车载网一直饱受链路不稳定以及低吞吐量的困扰,很大程度上影响了其商业部署。为此,我们研究了基于移动支持的关联控制问题,该问题目标为利用有效的算法减少终端切换次数,降低链路中断频率以及提高网络吞吐量。我们提出两个在线启发式算法来解决此问题。这两个算法实现简单,利于部署。最后,通过车载网仿真环境的实验验证了算法的性能。
Ubiquitous network extends the traditional concept of a communication network, breaks the boundaries between different communication networks and combines individual closed networks as a whole. Ubiquitous network is not only in the area of overlay networks, but also a complex of many things, such as terminals, services, data and protocols.On the one hand, each heterogeneous subnet in ubiquitous network coordinates with each other to jointly provide a transparent and seamless mobile network access environment. On the other hand, various services are fully interactive and adaptable automatically, which together create a wealth of service resources. These functions of ubiquitous network greatly improve the network service capabilities and provide terminals greater choices. However, the complexity and extensiveness of network and service bring many new challenges for network resource management. One of these challenges is how to effectively configure intelligent association relationship between the terminal and the network which is called network association control mechanisms.
There have been lots of researches of network association control mechanisms that produce many practical solutions. However, the introductions of ubiquitous network appear as a network environment with more new features and services with new requirements. Therefore, the association control mechanisms of ubiquitous network are not confined to the existing boundaries, and will solve the problem on a larger dimension. This includes not only how to associate the terminals to available networks, but also encountering the collaborative optimization problems in a complex networks and services environment. In this thesis, the association control mechanisms of ubiquitous network are intensively studies to effectively improve the utilization of network resources and the service experiences of terminals. Specifically, this thesis proposes link stability based, content-aware based, transmission timeliness based and mobility supporting based association control mechanisms respectively in order to resolve the outstanding problems for different network scenarios. The main contents are as follows.
Link stability based association control in ubiquitous network
To begin with, this thesis studies the association control problem in low-speed mobile scenarios of ubiquitous network. When the terminals stay or move slowly in the ubiquitous network, the re-association due to the network migration and the degradation of link quality will lead to the increase of delay. Apart from that, the distribution imbalance of terminals in ubiquitous network will cause the imbalance load of networks and in turn affect the entire network efficiency. The delay caused by frequent handoffs and link congestion due to network overload are two main factors that damage the stability of the link. Existing research works on association control problems are mainly focus on reducing the delay of a single terminal handoff and increasing the duration of association, few of them take into account the joint effects of terminal handoff latency and network load balancing. To this end, we have studied the link stability based association control in ubiquitous network with the purposes of reducing terminal handoff frequency and balancing the network load through intelligent match between networks and terminals. Since the target problem is NP-hard, two constant approximation algorithms are presented to resolve it. Finally, trace based evaluations are conducted to demonstrate the effectiveness of our algorithms.
Content-aware based association control in ubiquitous network
Besides, this thesis explores the association control problem in quasi-static scenarios of ubiquitous network. Ubiquitous network has a extremely complex service environment, and its key problems needed to resolve by association control are meeting the differential requirements of heterogeneous services while balancing the network load. Because of the lacking variety of services in traditional networks, existing research works on association control problems are chiefly concentrate on improving the throughput of network and establishing a fair resource allocation scheme among terminals. There is few effort to investigate the diversity of QoS requirements of heterogeneous services, and further consider jointly on the optimization between differential QoS requirements of services and network load balancing. In this respect, we have studied the content-aware based association control in ubiquitous network with the goal of meeting the differential QoS requirements for every individual service and balancing the network load. Since this problem belongs to NP hard, we then propose two approximation algorithms to resolve it. Finally, algorithms are evaluated in a network allowed several services. The results verify the performance of our algorithm.
Transmission timeliness based association control in ubiquitous network
Also in quasi-static scenarios of ubiquitous network, as the surge in the amount of data and higher requirement of improving the timeliness of data transmission, the association control mechanisms need to increase the throughput and reduce transmission delay. This is particularly important for widespread real time services in ubiquitous network. Due to the restricted size and capacity of traditional network services, the efforts committed to improving the timeliness of transmission mainly aim at a single access point or a single link. Apart from this, real time services are not widely deployed in traditional networks, with the results that existing research works on association control problems are chiefly concentrate on improving the throughput of network and balancing the network load. Few of the methods are conducted to incorporate transmission timeliness, and take another step forward in joint resource allocation for real time services. For this reason, we have explored the transmission timeliness based association control in ubiquitous network which targets at increasing the timeliness of service transmission and thus guaranteeing the continuity of service. After proof that the target problem is NP hard, we put forward two approximation algorithms to solve it. Finally, extensive evaluations show that the proposed algorithms have good performance.
Mobility supporting based association control in ubiquitous network
Last, this thesis studies the association control problem in high-speed mobile scenarios of ubiquitous network. Since the topology of high-speed mobile network changes rapidly, load balancing is not a primary objective. The typical representative of high-speed mobile network scenario is vehicular network. In this thesis, we take vehicular network for example in studying the association control problems in high-speed mobile scenario of ubiquitous network. Excessive handoff frequency will bring high transmission delay to vehicular terminal services, while the instability of radio channel as well as the dramatic changes in vehicular terminal location will further deteriorate, leading to frequent interruptions for network links. In addition to this, unlike traditional wireless networks, the intermittent feature of vehicular network makes every work that tries to get long-term stability of the bandwidth nothing. There is little research on the association control mechanisms in vehicular network, which makes the vehicular network plagued by link instability and low throughput, and further handicaps the commercial deployments of vehicular networks. With regards to this, we have studied the mobility supporting based association control in ubiquitous network with the objective of decreasing the number of terminal handoffs, reducing the frequency of link interruptions and improving the network throughput. Two heuristic online algorithms are presented to resolve the target problem. Finally, comprehensive evaluations are conducted in vehicular simulation network to demonstrate the effectiveness of our algorithms.
引文
[1]Meng X, Dodson A, Moore T, et al. Ubiquitous Positioning:Anyone. Anything:Anytime, Anywhere [J]. GPS WORLD,2007,18(6):60.
[2]Damnjanovic A, Montojo J, Wei Y, et al. A survey on 3GPP heterogeneous networks [J]. Wireless Communications, IEEE.2011.18(3):10-21.
[3]Chowdhury N M, Boutaba R. A survey of network virtualization [J]. Computer Networks, 2010,54(5):862-876.
[4]Barakat C, Altman E, Dabbous W. On TCP performance in a heterogeneous network:a survey [J]. Communications Magazine, IEEE,2000,38(1):40-46.
[5]Yan X, Ahmet Sekercioglu Y, Narayanan S. A survey of vertical handover decision algorithms in Fourth Generation heterogeneous wireless networks [J]. Computer Networks. 2010,54(11):1848-1863.
[6]Chinnappen-Rimer S, Hancke G P. An XML model for use across heterogeneous client-server applications [J]. Instrumentation and Measurement, IEEE Transactions on,2008. 57(10):2128-2135.
[7]Raghuveer A, Kang N. Du D H C.1 Techniques for Efficient Streaming of Layered Video in Heterogeneous Client Environments [J].2005.
[8]Allen G R, Hochmuth R M, Laser M, et al. Highly secure computer system architecture for a heterogeneous client environment:U.S. Patent 7.055,171 [P].2006-5-30.
[9]Eager D L, Ferris M C, Vernon M K. Optimized caching in systems with heterogeneous client populations [J]. Performance Evaluation,2000,42(2):163-185.
[10]Ramani I, Savage S. SyncScan:practical fast handoff for 802.11 infrastructure networks [C] INFOCOM 2005.24th Annual Joint Conference of the IEEE Computer and Communications Societies. Proceedings IEEE. IEEE.2005,1:675-684.
[11]Pack S, Choi Y. Fast inter-AP handoff using predictive-authentication scheme in a public wireless LAN [J]. Networks,2002,1:15-26.
[12]Mishra A, Shin M, Arbaush W A. Context caching using neighbor graphs for fast handoffs in a wireless network [C] INFOCOM 2004. Twenty-third AnnualJoint Conference of the IEEE Computer and Communications Societies. IEEE,2004. 1
[13]Shin M, Mishra A, Arbaugh W A. Improving the latency of 802.11 hand-offs using neighbor graphs [C] Proceedings of the 2nd international conference on Mobile systems, applications, and services. ACM.2004:70-83.
[14]Kim M, Liu Z, Parthasarathy S, et al. Association control in mobile wireless networks [C] INFOCOM 2008. The 27th Conference on Computer Communications. IEEE. IEEE,2008.
[15]Kim M, Liu Z, Parthasarathy S, et al. Association control algorithms for handoff frequency minimization in mobile wireless networks [J]. Wireless Networks,2012,18(5):535-550.
[16]Zhao Y, Li W, Hong J, et al. On handoff minimization in wireless networks:from a navigation perspective [C] Wireless Communications and Networking Conference (WCNC), 2010 IEEE. IEEE,2010:1-6.
[17]Balachandran A, Voelker G M, Bahl P, et al. Characterizing user behavior and network performance in a public wireless LAN [C] ACM SIGMETRICS Performance Evaluation Review. ACM,2002,30(1):195-205.
[18]Proxim Wireless Networks. Data sheet:ORINOCO AP-600 access point [EB/OL]. http://www.proxim.com.
[19]Gong H, Nahm K, Kim J. Distributed fair access point selection for multi-rate IEEE 802.11 WLANs [C] Consumer Communications and Networking Conference,2008. CCNC 2008. 5th IEEE. IEEE,2008:528-532.
[20]Kasbekar G S, Nuggehalli P, Kuri J. Online client-AP association in WLANs [C] Modeling and Optimization in Mobile, Ad Hoc and Wireless Networks,2006 4th International Symposium on. IEEE,2006:1-8.
[21]Papaoulakis N, Patrikakis C Z. A proactive, terminal based best Access Point selection mechanism for Wireless LANs [C] GLOBECOM Workshops,2008 IEEE. IEEE,2008:1-4.
[22]Ercetin O. Association games in IEEE 802.11 wireless local area networks [J]. Wireless Communications, IEEE Transactions on,2008,7(12):5136-5143.
[23]Gong D, Yang Y. Ap association in 802.11 n wlans with heterogeneous clients [C] INFOCOM,2012 Proceedings IEEE. IEEE,2012:1440-1448.
[24]Du L, Bai Y, Chen L. Access point selection strategy for large-scale wireless local area networks [C] 2007 IEEE Wireless Communications and Networking Conference.2007: 2161-2166.
[25]Bonald T, Ibrahim A, Roberts J. The impact of association on the capacity of WLANs [C] Modeling and Optimization in Mobile, Ad Hoc, and Wireless Networks,2009. WiOPT 2009. 7th International Symposium on. IEEE,2009:1-10.
[26]Bejerano Y, Han S J, Li L E. Fairness and load balancing in wireless LANs using association control [C] Proceedings of the 10th annual international conference on Mobile computing and networking. ACM,2004:315-329.
[27]Li L, Pal M, Yang Y R. Proportional fairness in multi-rate wireless LANs [C] INFOCOM 2008. The 27th Conference on Computer Communications. IEEE. IEEE,2008.
[28]Dhar S, Ray A, Bera R. Design and simulation of vertical handover algorithm for vehicular communication [J]. International Journal of Engineering Science and Technology.2010, 2(10):5509-5525.
[29]Deshpande P, Kashyap A, Sung C, et al. Predictive methods for improved vehicular WiFi access [C] Proceedings of the 7th international conference on Mobile systems, applications, and services. ACM,2009:263-276.
[30]Xie L, Li Q, Mao W, et al. Achieving efficiency and fairness for association control in vehicular networks [C] Network Protocols,2009. ICNP 2009.17th IEEE International Conference on. IEEE,2009:324-333.
[31]Xie L, Li Q, Mao W, et al. Association control for vehicular wifi access:Pursuing efficiency and fairness [J]. Parallel and Distributed Systems, IEEE Transactions on,2011,22(8): 1323-1331.
[32]Chen M. Zhou L. Hara T, et al. Advances in multimedia communications [J]. International Journal of Communication Systems.2011,24(10):1243.
[33]Mishra A, Shin M, Arbaugh W. An empirical analysis of the IEEE 802.11 MAC layer handoff process [J]. ACM SIGCOMM Computer Communication Review,2003,33(2):93-102.
[34]Wu H, Tan K, Zhang Y, et al. Proactive scan:Fast handoff with smart triggers for 802.11 wireless LAN [C] INFOCOM 2007.26th IEEE International Conference on Computer Communications. IEEE. IEEE,2007:749-757.
[35]Zhang Y, Liu Y, Xia Y, et al. Leapfrog:Fast, timely wifi handoff [C] Global Telecommunications Conference,2007. GLOBECOM'07. IEEE. IEEE,2007:5170-5174.
[36]Ma X, Liu J, Jiang H. On the design of algorithms for mobile multimedia systems:a survey [J]. International Journal of Communication Systems.2011,24(10):1330-1339.
[37]Papanikos I, Logothetis M. A study on dynamic load balance for IEEE 802.11 b wireless LAN [C] Proc. COMCON.2001,2001.
[38]Balachandran A, Bahl P, Voelker G M. Hot-spot congestion relief and service guarantees in public-area wireless networks [J]. ACM SIGCOMM Computer Communication Review, 2002,32(1):59-59.
[39]Bortnikov E, Khuller S, Li J, et al. The load-distance balancing problem [J]. Networks.2012, 59(1):22-29.
[40]Ahuja R K, Magnanti T L, Orlin J B. Network flows:theory, algorithms and applications [M]. Prentice Hall,1994.
[41]Kutten S, Peleg D. Fault-local distributed mending [C] Proceedings of the fourteenth annual ACM symposium on Principles of distributed computing. ACM,1995:20-27.
[42]Birk Y, Keidar I, Liss L, et al. Veracity radius:capturing the locality of distributed computations [C] Proceedings of the twenty-fifth annual ACM symposium on Principles of distributed computing. ACM,2006:102-111.
[43]Bortnikov E, Cidon I, Keidar I. Scalable Load-Distance Balancing in Large Networks [C] CCIT, EE Department Pub No.1539, Technion IIT.2006.
[44]Awerbuch B. Complexity of network synchronization [J]. Journal of the ACM (JACM),1985, 32(4):804-823.
[45]Niedermeier R, Reinhardt K, Sanders P. Towards optimal locality in mesh-indexings [C] Fundamentals of Computation Theory. Springer Berlin Heidelberg,1997:364-375.
[46]Tuduce C, Gross T. A mobility model based on wlan traces and its validation C] INFOCOM 2005.24th Annual Joint Conference of the IEEE Computer and Communications Societies. Proceedings IEEE. IEEE,2005,1:664-674.
[47]McNett M, Voelker G M. Access and mobility of wireless PDA users [J]. ACM SIGMOBILE Mobile Computing and Communications Review,2005,9(2):40-55.
[48]Cisco System Inc:Aironet 802.11 a/b/g WLAN Client Adapter Data Sheet [EB/OL]. http://www.cisco.com.
[49]Vazirani V V. Approximation algorithms [M]. springer,2001.
[50]Symbol Technologies, Wireless Networker CF Radio Card Data Sheet [EB/OL] http://www.symboltech.net
[51]Chen X, Zhai H, Tian X, et al. Supporting QoS in IEEE 802.11 e wireless LANs [J]. Wireless Communications, IEEE Transactions on,2006,5(8):2217-2227.
[52]Liu J, Niu Z. A dynamic admission control scheme for QoS supporting in IEEE 802.11 e EDCA [C] Wireless Communications and Networking Conference,2007. WCNC 2007. IEEE IEEE,2007:3697-3702.
[53]Kuo Y L, Lu C H, Wu E H K, et al. An admission control strategy for differentiated services in IEEE 802.11 [C] Global Telecommunications Conference,2003. GLOBECOM'03. IEEE. IEEE,2003,2:707-712.
[54]Tartarelli S, Nunzi G. Qos management and congestion control in wireless hotspots [C] Network Operations and Management Symposium,2006. NOMS 2006.10th IEEE/IFIP. IEEE,2006:95-105.
[55]Bortnikov. E, Khuller, S., Mansour. I, Naor. S. The Load-Distance Balancing Problem [C] Internation Network Optimization Conference (INOC), Pisa, Italy.2009.
[56]Han B, Lee S. Efficient packet error rate estimation in wireless networks [C] Testbeds and Research Infrastructure for the Development of Networks and Communities,2007. TridentCom 2007.3rd International Conference on. IEEE,2007:1-9.
[57]Sripanidkulchai K, Ganjam A, Maggs B. et al. The feasibility of supporting large-scale live streaming applications with dynamic application end-points [J]. ACM SIGCOMM Computer Communication Review,2004,34(4):107-120.
[58]Hei X. Liang C, Liang J, et al. A measurement study of a large-scale P2P IPTV system [J]. Multimedia, IEEE Transactions on,2007,9(8):1672-1687.
[59]Balazinska M, Castro P. Characterizing mobility and network usage in a corporate wireless local-area network [C] Proceedings of the 1st international conference on Mobile systems, applications and services. ACM,2003:303-316.
[60]Kotz D, Essien K. Analysis of a campus-wide wireless network [J]. Wireless Networks,2005, 11(1-2):115-133.
[61]Shakkottai S, Shakkottai S G, Srikant R. Network optimization and control [M]. Now Publishers Inc,2008.
[62]Gao Y, Tan C W, Huang Y, et al. Feasibility and optimization of delay guarantees for non-homogeneous flows in IEEE 802.11 WLANs [C] INFOCOM,2011 Proceedings IEEE. IEEE,2011:2660-2668.
[63]Hou I H, Kumar P R. Utility maximization for delay constrained QoS in wireless [C] INFOCOM,2010 Proceedings IEEE. IEEE,2010:1-9.
[64]Gao Y, Tan C W, Huang Y, et al. Feasibility and optimization of delay guarantees for non-homogeneous flows in IEEE 802.11 WLANs [C] INFOCOM,2011 Proceedings IEEE. IEEE,2011:2660-2668.
[65]Li H, Cheng Y. Zhou C, et al. Minimizing end-to-end delay:a novel routing metric for multi-radio wireless mesh networks[C] INFOCOM 2009, IEEE. IEEE.2009:46-54.
[66]Pei G. Kumar V S A, Parthasarathy S, et al. Approximation algorithms for throughput maximization in wireless networks with delay constraints [C] INFOCOM,2011 Proceedings IEEE. IEEE,2011:1116-1124.
[67]Anshelevich E, Dasgupta A, Kleinberg J, et al. The price of stability for network design with fair cost allocation [J]. SIAM Journal on Computing,2008,38(4):1602-1623.
[68]Abusubaih M. Heterogeneous uncoordinated deployment of WLANs:an evolving problem for current and future WiFi access [J]. International Journal of Network Management,2013, 23(1):66-79.
[69]Bychkovsky V, Hull B. Miu A, et al. A measurement study of vehicular internet access using in situ Wi-Fi networks [C] Proceedings of the 12th annual international conference on Mobile computing and networking. ACM,2006:50-61.
[70]Ott J, Kutscher D. Drive-thru Internet:IEEE 802.11 b for" automobile" users [C] INFOCOM 2004. Twenty-third Annual Joint Conference of the IEEE Computer and Communications Societies. IEEE,2004,1.
[71]Chiu K L, Chen Y S, Hwang R H. Seamless session mobility scheme in heterogeneous wireless networks [J]. International Journal of Communication Systems,201.1,24(6): 789-809.
[72]Magagula L A, Chan H A, Falowo O E. Handover approaches for seamless mobility management in next generation wireless networks [J]. Wireless Communications and Mobile Computing,2012,12(16):1414-1428.
[73]Abusubaih M. Heterogeneous uncoordinated deployment of WLANs:an evolving problem for current and future WiFi access [J]. International Journal of Network Management,2013, 23(1):66-79.
[74]Kwak D, Mo J, Kang M. Investigation of handoffs for IEEE 802.11 networks in vehicular environment [C] Ubiquitous and Future Networks,2009. ICUFN 2009. First International Conference on. IEEE,2009:89-94.
[75]Hwang R H, Chang B J, Lin Y M. et al. Adaptive load balancing association handoff approach for increasing utilization and improving GoS in mobile WiMAX networks [J]. Wireless Communications and Mobile Computing,2012,12(14):1251-1265.
[2]Damnjanovic A, Montojo J, Wei Y, et al. A survey on 3GPP heterogeneous networks [J]. Wireless Communications, IEEE.2011.18(3):10-21.
[3]Chowdhury N M, Boutaba R. A survey of network virtualization [J]. Computer Networks, 2010,54(5):862-876.
[4]Barakat C, Altman E, Dabbous W. On TCP performance in a heterogeneous network:a survey [J]. Communications Magazine, IEEE,2000,38(1):40-46.
[5]Yan X, Ahmet Sekercioglu Y, Narayanan S. A survey of vertical handover decision algorithms in Fourth Generation heterogeneous wireless networks [J]. Computer Networks. 2010,54(11):1848-1863.
[6]Chinnappen-Rimer S, Hancke G P. An XML model for use across heterogeneous client-server applications [J]. Instrumentation and Measurement, IEEE Transactions on,2008. 57(10):2128-2135.
[7]Raghuveer A, Kang N. Du D H C.1 Techniques for Efficient Streaming of Layered Video in Heterogeneous Client Environments [J].2005.
[8]Allen G R, Hochmuth R M, Laser M, et al. Highly secure computer system architecture for a heterogeneous client environment:U.S. Patent 7.055,171 [P].2006-5-30.
[9]Eager D L, Ferris M C, Vernon M K. Optimized caching in systems with heterogeneous client populations [J]. Performance Evaluation,2000,42(2):163-185.
[10]Ramani I, Savage S. SyncScan:practical fast handoff for 802.11 infrastructure networks [C] INFOCOM 2005.24th Annual Joint Conference of the IEEE Computer and Communications Societies. Proceedings IEEE. IEEE.2005,1:675-684.
[11]Pack S, Choi Y. Fast inter-AP handoff using predictive-authentication scheme in a public wireless LAN [J]. Networks,2002,1:15-26.
[12]Mishra A, Shin M, Arbaush W A. Context caching using neighbor graphs for fast handoffs in a wireless network [C] INFOCOM 2004. Twenty-third AnnualJoint Conference of the IEEE Computer and Communications Societies. IEEE,2004. 1
[13]Shin M, Mishra A, Arbaugh W A. Improving the latency of 802.11 hand-offs using neighbor graphs [C] Proceedings of the 2nd international conference on Mobile systems, applications, and services. ACM.2004:70-83.
[14]Kim M, Liu Z, Parthasarathy S, et al. Association control in mobile wireless networks [C] INFOCOM 2008. The 27th Conference on Computer Communications. IEEE. IEEE,2008.
[15]Kim M, Liu Z, Parthasarathy S, et al. Association control algorithms for handoff frequency minimization in mobile wireless networks [J]. Wireless Networks,2012,18(5):535-550.
[16]Zhao Y, Li W, Hong J, et al. On handoff minimization in wireless networks:from a navigation perspective [C] Wireless Communications and Networking Conference (WCNC), 2010 IEEE. IEEE,2010:1-6.
[17]Balachandran A, Voelker G M, Bahl P, et al. Characterizing user behavior and network performance in a public wireless LAN [C] ACM SIGMETRICS Performance Evaluation Review. ACM,2002,30(1):195-205.
[18]Proxim Wireless Networks. Data sheet:ORINOCO AP-600 access point [EB/OL]. http://www.proxim.com.
[19]Gong H, Nahm K, Kim J. Distributed fair access point selection for multi-rate IEEE 802.11 WLANs [C] Consumer Communications and Networking Conference,2008. CCNC 2008. 5th IEEE. IEEE,2008:528-532.
[20]Kasbekar G S, Nuggehalli P, Kuri J. Online client-AP association in WLANs [C] Modeling and Optimization in Mobile, Ad Hoc and Wireless Networks,2006 4th International Symposium on. IEEE,2006:1-8.
[21]Papaoulakis N, Patrikakis C Z. A proactive, terminal based best Access Point selection mechanism for Wireless LANs [C] GLOBECOM Workshops,2008 IEEE. IEEE,2008:1-4.
[22]Ercetin O. Association games in IEEE 802.11 wireless local area networks [J]. Wireless Communications, IEEE Transactions on,2008,7(12):5136-5143.
[23]Gong D, Yang Y. Ap association in 802.11 n wlans with heterogeneous clients [C] INFOCOM,2012 Proceedings IEEE. IEEE,2012:1440-1448.
[24]Du L, Bai Y, Chen L. Access point selection strategy for large-scale wireless local area networks [C] 2007 IEEE Wireless Communications and Networking Conference.2007: 2161-2166.
[25]Bonald T, Ibrahim A, Roberts J. The impact of association on the capacity of WLANs [C] Modeling and Optimization in Mobile, Ad Hoc, and Wireless Networks,2009. WiOPT 2009. 7th International Symposium on. IEEE,2009:1-10.
[26]Bejerano Y, Han S J, Li L E. Fairness and load balancing in wireless LANs using association control [C] Proceedings of the 10th annual international conference on Mobile computing and networking. ACM,2004:315-329.
[27]Li L, Pal M, Yang Y R. Proportional fairness in multi-rate wireless LANs [C] INFOCOM 2008. The 27th Conference on Computer Communications. IEEE. IEEE,2008.
[28]Dhar S, Ray A, Bera R. Design and simulation of vertical handover algorithm for vehicular communication [J]. International Journal of Engineering Science and Technology.2010, 2(10):5509-5525.
[29]Deshpande P, Kashyap A, Sung C, et al. Predictive methods for improved vehicular WiFi access [C] Proceedings of the 7th international conference on Mobile systems, applications, and services. ACM,2009:263-276.
[30]Xie L, Li Q, Mao W, et al. Achieving efficiency and fairness for association control in vehicular networks [C] Network Protocols,2009. ICNP 2009.17th IEEE International Conference on. IEEE,2009:324-333.
[31]Xie L, Li Q, Mao W, et al. Association control for vehicular wifi access:Pursuing efficiency and fairness [J]. Parallel and Distributed Systems, IEEE Transactions on,2011,22(8): 1323-1331.
[32]Chen M. Zhou L. Hara T, et al. Advances in multimedia communications [J]. International Journal of Communication Systems.2011,24(10):1243.
[33]Mishra A, Shin M, Arbaugh W. An empirical analysis of the IEEE 802.11 MAC layer handoff process [J]. ACM SIGCOMM Computer Communication Review,2003,33(2):93-102.
[34]Wu H, Tan K, Zhang Y, et al. Proactive scan:Fast handoff with smart triggers for 802.11 wireless LAN [C] INFOCOM 2007.26th IEEE International Conference on Computer Communications. IEEE. IEEE,2007:749-757.
[35]Zhang Y, Liu Y, Xia Y, et al. Leapfrog:Fast, timely wifi handoff [C] Global Telecommunications Conference,2007. GLOBECOM'07. IEEE. IEEE,2007:5170-5174.
[36]Ma X, Liu J, Jiang H. On the design of algorithms for mobile multimedia systems:a survey [J]. International Journal of Communication Systems.2011,24(10):1330-1339.
[37]Papanikos I, Logothetis M. A study on dynamic load balance for IEEE 802.11 b wireless LAN [C] Proc. COMCON.2001,2001.
[38]Balachandran A, Bahl P, Voelker G M. Hot-spot congestion relief and service guarantees in public-area wireless networks [J]. ACM SIGCOMM Computer Communication Review, 2002,32(1):59-59.
[39]Bortnikov E, Khuller S, Li J, et al. The load-distance balancing problem [J]. Networks.2012, 59(1):22-29.
[40]Ahuja R K, Magnanti T L, Orlin J B. Network flows:theory, algorithms and applications [M]. Prentice Hall,1994.
[41]Kutten S, Peleg D. Fault-local distributed mending [C] Proceedings of the fourteenth annual ACM symposium on Principles of distributed computing. ACM,1995:20-27.
[42]Birk Y, Keidar I, Liss L, et al. Veracity radius:capturing the locality of distributed computations [C] Proceedings of the twenty-fifth annual ACM symposium on Principles of distributed computing. ACM,2006:102-111.
[43]Bortnikov E, Cidon I, Keidar I. Scalable Load-Distance Balancing in Large Networks [C] CCIT, EE Department Pub No.1539, Technion IIT.2006.
[44]Awerbuch B. Complexity of network synchronization [J]. Journal of the ACM (JACM),1985, 32(4):804-823.
[45]Niedermeier R, Reinhardt K, Sanders P. Towards optimal locality in mesh-indexings [C] Fundamentals of Computation Theory. Springer Berlin Heidelberg,1997:364-375.
[46]Tuduce C, Gross T. A mobility model based on wlan traces and its validation C] INFOCOM 2005.24th Annual Joint Conference of the IEEE Computer and Communications Societies. Proceedings IEEE. IEEE,2005,1:664-674.
[47]McNett M, Voelker G M. Access and mobility of wireless PDA users [J]. ACM SIGMOBILE Mobile Computing and Communications Review,2005,9(2):40-55.
[48]Cisco System Inc:Aironet 802.11 a/b/g WLAN Client Adapter Data Sheet [EB/OL]. http://www.cisco.com.
[49]Vazirani V V. Approximation algorithms [M]. springer,2001.
[50]Symbol Technologies, Wireless Networker CF Radio Card Data Sheet [EB/OL] http://www.symboltech.net
[51]Chen X, Zhai H, Tian X, et al. Supporting QoS in IEEE 802.11 e wireless LANs [J]. Wireless Communications, IEEE Transactions on,2006,5(8):2217-2227.
[52]Liu J, Niu Z. A dynamic admission control scheme for QoS supporting in IEEE 802.11 e EDCA [C] Wireless Communications and Networking Conference,2007. WCNC 2007. IEEE IEEE,2007:3697-3702.
[53]Kuo Y L, Lu C H, Wu E H K, et al. An admission control strategy for differentiated services in IEEE 802.11 [C] Global Telecommunications Conference,2003. GLOBECOM'03. IEEE. IEEE,2003,2:707-712.
[54]Tartarelli S, Nunzi G. Qos management and congestion control in wireless hotspots [C] Network Operations and Management Symposium,2006. NOMS 2006.10th IEEE/IFIP. IEEE,2006:95-105.
[55]Bortnikov. E, Khuller, S., Mansour. I, Naor. S. The Load-Distance Balancing Problem [C] Internation Network Optimization Conference (INOC), Pisa, Italy.2009.
[56]Han B, Lee S. Efficient packet error rate estimation in wireless networks [C] Testbeds and Research Infrastructure for the Development of Networks and Communities,2007. TridentCom 2007.3rd International Conference on. IEEE,2007:1-9.
[57]Sripanidkulchai K, Ganjam A, Maggs B. et al. The feasibility of supporting large-scale live streaming applications with dynamic application end-points [J]. ACM SIGCOMM Computer Communication Review,2004,34(4):107-120.
[58]Hei X. Liang C, Liang J, et al. A measurement study of a large-scale P2P IPTV system [J]. Multimedia, IEEE Transactions on,2007,9(8):1672-1687.
[59]Balazinska M, Castro P. Characterizing mobility and network usage in a corporate wireless local-area network [C] Proceedings of the 1st international conference on Mobile systems, applications and services. ACM,2003:303-316.
[60]Kotz D, Essien K. Analysis of a campus-wide wireless network [J]. Wireless Networks,2005, 11(1-2):115-133.
[61]Shakkottai S, Shakkottai S G, Srikant R. Network optimization and control [M]. Now Publishers Inc,2008.
[62]Gao Y, Tan C W, Huang Y, et al. Feasibility and optimization of delay guarantees for non-homogeneous flows in IEEE 802.11 WLANs [C] INFOCOM,2011 Proceedings IEEE. IEEE,2011:2660-2668.
[63]Hou I H, Kumar P R. Utility maximization for delay constrained QoS in wireless [C] INFOCOM,2010 Proceedings IEEE. IEEE,2010:1-9.
[64]Gao Y, Tan C W, Huang Y, et al. Feasibility and optimization of delay guarantees for non-homogeneous flows in IEEE 802.11 WLANs [C] INFOCOM,2011 Proceedings IEEE. IEEE,2011:2660-2668.
[65]Li H, Cheng Y. Zhou C, et al. Minimizing end-to-end delay:a novel routing metric for multi-radio wireless mesh networks[C] INFOCOM 2009, IEEE. IEEE.2009:46-54.
[66]Pei G. Kumar V S A, Parthasarathy S, et al. Approximation algorithms for throughput maximization in wireless networks with delay constraints [C] INFOCOM,2011 Proceedings IEEE. IEEE,2011:1116-1124.
[67]Anshelevich E, Dasgupta A, Kleinberg J, et al. The price of stability for network design with fair cost allocation [J]. SIAM Journal on Computing,2008,38(4):1602-1623.
[68]Abusubaih M. Heterogeneous uncoordinated deployment of WLANs:an evolving problem for current and future WiFi access [J]. International Journal of Network Management,2013, 23(1):66-79.
[69]Bychkovsky V, Hull B. Miu A, et al. A measurement study of vehicular internet access using in situ Wi-Fi networks [C] Proceedings of the 12th annual international conference on Mobile computing and networking. ACM,2006:50-61.
[70]Ott J, Kutscher D. Drive-thru Internet:IEEE 802.11 b for" automobile" users [C] INFOCOM 2004. Twenty-third Annual Joint Conference of the IEEE Computer and Communications Societies. IEEE,2004,1.
[71]Chiu K L, Chen Y S, Hwang R H. Seamless session mobility scheme in heterogeneous wireless networks [J]. International Journal of Communication Systems,201.1,24(6): 789-809.
[72]Magagula L A, Chan H A, Falowo O E. Handover approaches for seamless mobility management in next generation wireless networks [J]. Wireless Communications and Mobile Computing,2012,12(16):1414-1428.
[73]Abusubaih M. Heterogeneous uncoordinated deployment of WLANs:an evolving problem for current and future WiFi access [J]. International Journal of Network Management,2013, 23(1):66-79.
[74]Kwak D, Mo J, Kang M. Investigation of handoffs for IEEE 802.11 networks in vehicular environment [C] Ubiquitous and Future Networks,2009. ICUFN 2009. First International Conference on. IEEE,2009:89-94.
[75]Hwang R H, Chang B J, Lin Y M. et al. Adaptive load balancing association handoff approach for increasing utilization and improving GoS in mobile WiMAX networks [J]. Wireless Communications and Mobile Computing,2012,12(14):1251-1265.