面向云计算环境的动态公平性度量方法

针对云计算环境资源动态性特点,给出了一种资源分配算法公平性动态度量模型——DFE (dynamic fairness evaluation)。模型引入了公平、效率和时间参数,通过将资源分配结果进行量化处理,定量地描述不同分配算法的公平性。首先考虑了云环境下的2种典型动态因素：1）节点资源需求动态变化;2）虚拟节点动态变化,并分别对这2种场景建立子模型,通过这2种模型导出了公平性动态度量模型DFE。分析了2种子模型以及DFE,通过DFE对几种典型资源分配算法进行度量,验证了在资源需求以及虚拟节点动态变化的情况下,DFE能够有效度量分配算法公平性,为云计算平台资源分配算法的选择提供了重要的参考。     

一种基于 SLA 的 WDM EPON 动态波长带宽分配算法简

波分复用技术结合时分复用形成了混合WDM EPON,如何提高系统的带宽利用率和用户服务质量成为关键技术。结合已有算法的优缺点,提出一种新的动态波长带宽分配算法。该算法结合业务等级分类和用户服务等级协议的权重为光网络单元分配相应的带宽和波长,以达到提高服务质量、带宽分配公平性,提高上行带宽利用率和改善网络性能的目的。     

Core‐stateless fair rate estimation fair queuing

Core‐stateless mechanisms, such as core‐stateless fair queuing (CSFQ), reduce the complexity of fair queuing, which usually need to maintain states, manage buffers, and perform flow scheduling on a per‐flow basis. However, they require executing label rewriting and dropping decision on a per‐packet basis, thus preventing them from being widely deployed. In this paper, we propose a novel architecture based on CSFQ without per‐packet labelling. Similarly, we distinguish between edge routers and core routers. Edge routers maintain the per‐flow state by employing a fair queuing mechanism to allocate each flow a fair bandwidth share locally and a token bucket mechanism to regulate those flows with feedback packets sent from egress edge routers. Core routers do not maintain per‐flow state; they use FIFO packet scheduling extended by a fare rate alarm mechanism by estimating the arrival rate and the number of flows using a matching–mismatching algorithm. The novel scheme is called core‐stateless fair rate estimation fair queuing (CSFREFQ). CSFREFQ is proven to be capable of achieving max–min fairness. Furthermore, we present and discuss simulations and experiments on the performance under different traffic scenarios. Copyright © 2005 John Wiley & Sons, Ltd.     

CDMA系统中基于公平性考虑的博弈功率控制算法

为解决CDMA系统中各用户与基站间距离的远近公平问题,提出了一种基于公平性考虑的非合作博弈功率控制算法。该算法综合考虑用户路径增益与发射功率等,设计了一种新的且存在唯一纳什均衡的代价函数,进而能够改善系统中的远近公平问题。仿真结果表明,与传统的功率控制算法相比,提出的功率控制算法具有用户发射功率降低,而且用户获得的SIR是远近公平的,并且用户获得的收益也是远近公平的优势。系统的远近公平问题得到了很好的改善。     

弹性分组环MAC公平性评价指标研究

鉴于目前大多数公平算法只有评价准则,而无评价指标,论文在RIAS公平性评价准则的基础上提出关于流传送速率和BE类流的公平效果的公平性评价指标。通过仿真验证,该公平性评价指标能很好地检验算法的公平性,能为各具体的MAC协议公平性算法提供很好的依据。     

A fast‐convergent fairness scheme for resource allocation in RPR networks

In this paper, we propose a fast‐convergent fairness scheme in IEEE 802.17 resilient packet ring (RPR) networks. In the proposed scheme, each station could rapidly approach fair rate by estimating the number of unbounded flows at each link. In addition, the fast‐convergent scheme could prevent rate oscillations in the RPR aggressive mode scheme under unbalanced traffic. The estimation mechanism is simple and scalable since it is stateless without per‐flow management. Through analytical and simulation evaluations our scheme was found to be stable and speedy when compared with 802.17 RPR fairness scheme or the proposed distributed virtual‐time scheduling in rings scheme. Our scheme could allocate bandwidth fairly and smoothly among flows and achieve high utilization at the same time in the RPR network. Copyright © 2008 John Wiley & Sons, Ltd.     

Revisited Progressive Second Price Auction for Charging Telecommunication Networks

Flat-rate charging of telecommunication networks does not seem relevant anymore as it creates congestion (like in the Internet). Among usage-based charging schemes, auctionning for bandwidth looks very promising. We review here the tremendous work called progressive second price auction and give some new results about users' behaviour in order to prove the results published in the literature.     

脏纸编码的多用户MIMO-OFDM系统中基于纳什公平的资源分配算法

MIMO-OFDM技术是实现大容量无线数据传输的一项关键技术。多用户系统中,在最大化系统资源利用率的同时保证用户间资源分配的公平性是系统设计的一个重要问题。该文首先分析了MIMO系统中最大化吞吐量的一种实现方式脏纸编码(DPC),然后基于纳什公平性准则提出了一种用于DPC的多用户MIMO-OFDM系统中的自适应资源分配算法。仿真结果表明,该算法在损失较小系统吞吐量的前提下,很好地保证了用户间资源分配的公平性。     

小区间动态干扰协调的改进方案

对下一代移动通信系统的小区间动态干扰协调算法进行研究,通过分析干扰水平,负载状况,基站的调节能力以及用户的位置,通过负载因子变化来接纳控制,提高边缘用户的数据传输速度,保证小区用户的公平性。通过上行功率控制及接纳算法改进方案;同时对小区用户划分区域设定,提出了小区间干扰协调的改进算法(ICPF), 并进行系统仿真计算分析,结果表明和以往传统算法相比,系统性能得到有效改进,进一步提高了系统公平性并增加小区边缘用户的吞吐量。     

Distributed congestion control strategy using network utility maximization theory in VANET

Cooperative vehicle safety system (CVSS) rely on periodical beacons to track neighboring vehicles.High traffic density often causes channel congestion,seriously damaging the performance of CVSS.Existing congestion control strategies aim to ensure the performance in network layer,without considering the service requirements of vehicles in different driving contexts.To solve the problem,a distributed congestion control strategy using network utility maximization (NUM) theory was proposed.First of all,the NUM model for channel resource allocation was introduced.A utility function reflecting vehicle’s safety requirements was proposed in the model.Then under the condition of fixed transmit powers,a optimization problem of channel resource allocation was proposed.Lastly,to solve the optimization problem,a distributed congestion control algorithm named utility-based rate congestion control (UBRCC) algorithm was designed,the algorithm worked out the optimal beaconing rate by updating vehicle’s congestion price,realizing the resource allocation according to vehicle’s safety requirements.Simulation results validate that UBRCC algorithm can efficiently control channel congestion,reduce transmission delay,ensure reliable data transmission and satisfies the requirements of safety applications.