移动数据分流(Mobile Data Offloading)是近年来一个比较新的研究热点。为了解决用户日益增长的移动数据需求给蜂窝网络运营商造成的流量负载和网络拥塞等问题,移动数据分流被提出来,即将蜂窝网络的数据分流到无处不在的用户间本地机会...移动数据分流(Mobile Data Offloading)是近年来一个比较新的研究热点。为了解决用户日益增长的移动数据需求给蜂窝网络运营商造成的流量负载和网络拥塞等问题,移动数据分流被提出来,即将蜂窝网络的数据分流到无处不在的用户间本地机会通信。其基本思想是通过蜂窝网络分发数据对象到一部分订阅用户(称为种子用户),再由种子用户通过本地机会通信(如Bluetooth、WiFi Direct、DSRC、Device-to-Device in LTE等)或基于WiFi AP辅助的方式传送给其他订阅的用户。首先从总体上概述了当前对数据分流研究的背景、意义和具体的研究进展。然后针对当前国内外学术界对这方面的研究内容和趋势,按照形式和技术路线对数据分流的方案进行了归类,并对各种类型的分流方案进行了综述。最后结合现实环境进行总结。展开更多
设备到设备(device to device,D2D)通信允许邻近用户使用蜂窝网络频段直接通信,既能分流部分蜂窝数据,减轻基站负担,又能提升服务质量。但由于信息不对称,蜂窝网络不知道用户的类型参数,无法准确提供合理补偿,以激励用户参与数据分流。...设备到设备(device to device,D2D)通信允许邻近用户使用蜂窝网络频段直接通信,既能分流部分蜂窝数据,减轻基站负担,又能提升服务质量。但由于信息不对称,蜂窝网络不知道用户的类型参数,无法准确提供合理补偿,以激励用户参与数据分流。基于契约理论设计了一种分流补偿机制,首先设计蜂窝网络收益函数和分流用户代价函数及其二者的效用;然后基于用户类型参数服从均匀分布设计补偿机制,验证了该机制能满足个人理性和激励相容条件,分析了该机制的最优性能;最后与正比例补偿机制和完全信息补偿机制进行对比仿真,结果表明,本文设计的分流补偿机制既能保证用户愿意参与数据分流,也鼓励用户报告自身真实的类型参数,还能获得接近于完全信息补偿机制下的效用和性能。展开更多
随着移动设备和无线应用爆炸式增长,蜂窝网络流量迅速增加,许可频段蜂窝网络容量难以满足用户日益增长的数据速率需求.WLAN(Wireless Local Area Network,无线局域网)与LTE(Long Term Evolution,长期演进)蜂窝异构网络中的数据卸载技术...随着移动设备和无线应用爆炸式增长,蜂窝网络流量迅速增加,许可频段蜂窝网络容量难以满足用户日益增长的数据速率需求.WLAN(Wireless Local Area Network,无线局域网)与LTE(Long Term Evolution,长期演进)蜂窝异构网络中的数据卸载技术能有效缓解蜂窝无线访问的频谱资源紧缺问题.然而,现有LTE-WLAN数据卸载方案并未考虑密集部署问题,也未考虑基于IEEE 802.11ax协议的下一代高效WLAN针对密集部署提出的提速新技术所带来优势.本文利用下一代WLAN的多用户传输特性来缓解蜂窝的资源竞争,通过将部分蜂窝用户卸载到IEEE 802.11ax WLAN网络来保障蜂窝网络的单用户吞吐率.提出的卸载方案建立WLAN和LTE异构密集网络的吞吐率形式化表达式,根据网络系统容量查找蜂窝网络中的最优卸载数,以解决有限的蜂窝网络资源与海量高速业务需求的矛盾.仿真结果表明:在密集部署的异构网络中,所提的方案在保证WLAN用户服务质量的同时,最大限度地提高了LTE网络单用户吞吐率,提升了LTE网络的用户体验.展开更多
In next generation networks, multiradio networks are emerging in order to deal with exponential data traffic increasing. Integrated Femto-WiFi(IFW) small cells have been introduced by 3GPP to offload data from cellula...In next generation networks, multiradio networks are emerging in order to deal with exponential data traffic increasing. Integrated Femto-WiFi(IFW) small cells have been introduced by 3GPP to offload data from cellular networks recently. These IFW cells are multi-mode capable(i.e., both licensed bands via cellular interface and unlicensed bands via WiFi interface). Therefore how to offload data effectively has become one of the most significant discussions in 5G Multi-Radio Heterogeneous Network. So far, most researches mainly focus on the generality of UEs, few attention has been paid to UEs' individual requirements. Considering UE's preference vary from individual to individual, in this paper, we present an UE preference-aware network selection scheme for mobile data offloading. It intelligently supports the distribution of heterogeneous classes of services, considers different types of UEs and delay-tolerant flows, and handles the mobility of UEs. The simulation results show the superiority of the proposed algorithm in user fairness, enhanced capacity and energy saving maximization.展开更多
Machine-type communication (MTC) devices provide a broad range of data collection especially on the massive data generated environments such as urban, industrials and event-enabled areas. In dense deployments, the dat...Machine-type communication (MTC) devices provide a broad range of data collection especially on the massive data generated environments such as urban, industrials and event-enabled areas. In dense deployments, the data collected at the closest locations between the MTC devices are spatially correlated. In this paper, we propose a k-means grouping technique to combine all MTC devices based on spatially correlated. The MTC devices collect the data on the event-based area and then transmit to the centralized aggregator for processing and computing. With the limitation of computational resources at the centralized aggregator, some grouped MTC devices data offloaded to the nearby base station collocated with the mobile edge-computing server. As a sensing capability adopted on MTC devices, we use a power exponential function model to compute a correlation coefficient existing between the MTC devices. Based on this framework, we compare the energy consumption when all data processed locally at centralized aggregator or offloaded at mobile edge computing server with optimal solution obtained by the brute force method. Then, the simulation results revealed that the proposed k-means grouping technique reduce the energy consumption at centralized aggregator while satisfying the required completion time.展开更多
随着输配电网的快速发展,输配电业务对时延、能效、可靠性等差异化通信指标提出了更高的的要求。为此,基于5G高速率大连接和卫星灵活广覆盖的特点,结合边缘计算高效处理数据的优势,构建了面向输配电场景的5G卫星融合组网架构。然后以最...随着输配电网的快速发展,输配电业务对时延、能效、可靠性等差异化通信指标提出了更高的的要求。为此,基于5G高速率大连接和卫星灵活广覆盖的特点,结合边缘计算高效处理数据的优势,构建了面向输配电场景的5G卫星融合组网架构。然后以最大化输配电业务数据传输平均能效与总时延的加权差为优化目标,构建了5G卫星融合组网数据卸载优化问题,并提出基于差异化业务需求感知的5G卫星融合组网数据卸载算法(Differentiated Service Requirement-aware Learning-based Data Offloading algorithm for 5G satellite integrated networking,DSRL-DO)求解。仿真结果表明,所提算法能够降低数据卸载时延的同时保证较高的能效,有效满足输配电业务的差异化需求。展开更多
车辆的高机动性和复杂的无线环境对6G车联网数据传输提出了巨大挑战。基于高吞吐量毫米波通信,车辆可将数据流量机会式卸载到相邻近路侧设备(Road Side Unit,RSU)。针对下一代车路协同业务场景,分析了RSU位置部署问题,提出了一种改进的...车辆的高机动性和复杂的无线环境对6G车联网数据传输提出了巨大挑战。基于高吞吐量毫米波通信,车辆可将数据流量机会式卸载到相邻近路侧设备(Road Side Unit,RSU)。针对下一代车路协同业务场景,分析了RSU位置部署问题,提出了一种改进的贪婪算法。使用真实出租车轨迹集综合仿真RSU部署方案,在预算限制内提高RSU利用率并减少车辆的接入等待时间。展开更多
提出了移动代理数据卸载策略,对无线传感器网络中现有移动代理规划路径进行优化,根据卸载规则决定是否将数据分组分离通过优化的卸载路径传递,卸载数据的移动代理通过原路径访问数据源节点。使用移动代理经典算法IEMF(itinerary energy ...提出了移动代理数据卸载策略,对无线传感器网络中现有移动代理规划路径进行优化,根据卸载规则决定是否将数据分组分离通过优化的卸载路径传递,卸载数据的移动代理通过原路径访问数据源节点。使用移动代理经典算法IEMF(itinerary energy minimum for first-source-selection)进行大量的仿真实验,结果显示,提出的数据卸载策略能有效地解决数据源节点能量消耗过快的问题,延长数据源节点的生存期。展开更多
The rapid growth of 3G/4G enabled devices such as smartphones and tablets in large numbers has created increased demand for mobile data services. Wi-Fi offloading helps satisfy the requirements of data-rich applicatio...The rapid growth of 3G/4G enabled devices such as smartphones and tablets in large numbers has created increased demand for mobile data services. Wi-Fi offloading helps satisfy the requirements of data-rich applications and terminals with improved multi- media. Wi-Fi is an essential approach to alleviating mobile data traffic load on a cellular network because it provides extra capacity and improves overall performance. In this paper, we propose an integrated LTE/Wi-Fi architecture with software-defined networking （SDN） abstraction in mobile baekhaul and enhanced components that facilitate the move towards next-generation 5G mo- bile networks. Our proposed architecture enables programmable offloading policies that take into account real-time network conditions as well as the status of devices and applications. This mechanism improves overall network performance by deriving real- time policies and steering traffic between cellular and Wi-Fi networks more efficiently.展开更多
文摘移动数据分流(Mobile Data Offloading)是近年来一个比较新的研究热点。为了解决用户日益增长的移动数据需求给蜂窝网络运营商造成的流量负载和网络拥塞等问题,移动数据分流被提出来,即将蜂窝网络的数据分流到无处不在的用户间本地机会通信。其基本思想是通过蜂窝网络分发数据对象到一部分订阅用户(称为种子用户),再由种子用户通过本地机会通信(如Bluetooth、WiFi Direct、DSRC、Device-to-Device in LTE等)或基于WiFi AP辅助的方式传送给其他订阅的用户。首先从总体上概述了当前对数据分流研究的背景、意义和具体的研究进展。然后针对当前国内外学术界对这方面的研究内容和趋势,按照形式和技术路线对数据分流的方案进行了归类,并对各种类型的分流方案进行了综述。最后结合现实环境进行总结。
文摘设备到设备(device to device,D2D)通信允许邻近用户使用蜂窝网络频段直接通信,既能分流部分蜂窝数据,减轻基站负担,又能提升服务质量。但由于信息不对称,蜂窝网络不知道用户的类型参数,无法准确提供合理补偿,以激励用户参与数据分流。基于契约理论设计了一种分流补偿机制,首先设计蜂窝网络收益函数和分流用户代价函数及其二者的效用;然后基于用户类型参数服从均匀分布设计补偿机制,验证了该机制能满足个人理性和激励相容条件,分析了该机制的最优性能;最后与正比例补偿机制和完全信息补偿机制进行对比仿真,结果表明,本文设计的分流补偿机制既能保证用户愿意参与数据分流,也鼓励用户报告自身真实的类型参数,还能获得接近于完全信息补偿机制下的效用和性能。
文摘随着移动设备和无线应用爆炸式增长,蜂窝网络流量迅速增加,许可频段蜂窝网络容量难以满足用户日益增长的数据速率需求.WLAN(Wireless Local Area Network,无线局域网)与LTE(Long Term Evolution,长期演进)蜂窝异构网络中的数据卸载技术能有效缓解蜂窝无线访问的频谱资源紧缺问题.然而,现有LTE-WLAN数据卸载方案并未考虑密集部署问题,也未考虑基于IEEE 802.11ax协议的下一代高效WLAN针对密集部署提出的提速新技术所带来优势.本文利用下一代WLAN的多用户传输特性来缓解蜂窝的资源竞争,通过将部分蜂窝用户卸载到IEEE 802.11ax WLAN网络来保障蜂窝网络的单用户吞吐率.提出的卸载方案建立WLAN和LTE异构密集网络的吞吐率形式化表达式,根据网络系统容量查找蜂窝网络中的最优卸载数,以解决有限的蜂窝网络资源与海量高速业务需求的矛盾.仿真结果表明:在密集部署的异构网络中,所提的方案在保证WLAN用户服务质量的同时,最大限度地提高了LTE网络单用户吞吐率,提升了LTE网络的用户体验.
文摘In next generation networks, multiradio networks are emerging in order to deal with exponential data traffic increasing. Integrated Femto-WiFi(IFW) small cells have been introduced by 3GPP to offload data from cellular networks recently. These IFW cells are multi-mode capable(i.e., both licensed bands via cellular interface and unlicensed bands via WiFi interface). Therefore how to offload data effectively has become one of the most significant discussions in 5G Multi-Radio Heterogeneous Network. So far, most researches mainly focus on the generality of UEs, few attention has been paid to UEs' individual requirements. Considering UE's preference vary from individual to individual, in this paper, we present an UE preference-aware network selection scheme for mobile data offloading. It intelligently supports the distribution of heterogeneous classes of services, considers different types of UEs and delay-tolerant flows, and handles the mobility of UEs. The simulation results show the superiority of the proposed algorithm in user fairness, enhanced capacity and energy saving maximization.
文摘Machine-type communication (MTC) devices provide a broad range of data collection especially on the massive data generated environments such as urban, industrials and event-enabled areas. In dense deployments, the data collected at the closest locations between the MTC devices are spatially correlated. In this paper, we propose a k-means grouping technique to combine all MTC devices based on spatially correlated. The MTC devices collect the data on the event-based area and then transmit to the centralized aggregator for processing and computing. With the limitation of computational resources at the centralized aggregator, some grouped MTC devices data offloaded to the nearby base station collocated with the mobile edge-computing server. As a sensing capability adopted on MTC devices, we use a power exponential function model to compute a correlation coefficient existing between the MTC devices. Based on this framework, we compare the energy consumption when all data processed locally at centralized aggregator or offloaded at mobile edge computing server with optimal solution obtained by the brute force method. Then, the simulation results revealed that the proposed k-means grouping technique reduce the energy consumption at centralized aggregator while satisfying the required completion time.
文摘随着输配电网的快速发展,输配电业务对时延、能效、可靠性等差异化通信指标提出了更高的的要求。为此,基于5G高速率大连接和卫星灵活广覆盖的特点,结合边缘计算高效处理数据的优势,构建了面向输配电场景的5G卫星融合组网架构。然后以最大化输配电业务数据传输平均能效与总时延的加权差为优化目标,构建了5G卫星融合组网数据卸载优化问题,并提出基于差异化业务需求感知的5G卫星融合组网数据卸载算法(Differentiated Service Requirement-aware Learning-based Data Offloading algorithm for 5G satellite integrated networking,DSRL-DO)求解。仿真结果表明,所提算法能够降低数据卸载时延的同时保证较高的能效,有效满足输配电业务的差异化需求。
文摘车辆的高机动性和复杂的无线环境对6G车联网数据传输提出了巨大挑战。基于高吞吐量毫米波通信,车辆可将数据流量机会式卸载到相邻近路侧设备(Road Side Unit,RSU)。针对下一代车路协同业务场景,分析了RSU位置部署问题,提出了一种改进的贪婪算法。使用真实出租车轨迹集综合仿真RSU部署方案,在预算限制内提高RSU利用率并减少车辆的接入等待时间。
文摘提出了移动代理数据卸载策略,对无线传感器网络中现有移动代理规划路径进行优化,根据卸载规则决定是否将数据分组分离通过优化的卸载路径传递,卸载数据的移动代理通过原路径访问数据源节点。使用移动代理经典算法IEMF(itinerary energy minimum for first-source-selection)进行大量的仿真实验,结果显示,提出的数据卸载策略能有效地解决数据源节点能量消耗过快的问题,延长数据源节点的生存期。
文摘The rapid growth of 3G/4G enabled devices such as smartphones and tablets in large numbers has created increased demand for mobile data services. Wi-Fi offloading helps satisfy the requirements of data-rich applications and terminals with improved multi- media. Wi-Fi is an essential approach to alleviating mobile data traffic load on a cellular network because it provides extra capacity and improves overall performance. In this paper, we propose an integrated LTE/Wi-Fi architecture with software-defined networking （SDN） abstraction in mobile baekhaul and enhanced components that facilitate the move towards next-generation 5G mo- bile networks. Our proposed architecture enables programmable offloading policies that take into account real-time network conditions as well as the status of devices and applications. This mechanism improves overall network performance by deriving real- time policies and steering traffic between cellular and Wi-Fi networks more efficiently.
