基于高能效及公平性的移动设备定位算法

通过分析校园师生基于GPS的真实活动轨迹,以及何种算法才最适合具有自私性的移动用户展开合作,提出一种高能效及用户公平定位技术.通过采用代理设备合作思想,提出一种集中式最优算法,在保证固定精度界限和设备公平的基础上,实现移动设备GPS时间平均功率最小化.通过控制退避时间和GPS关闭时间,提出一种分布式准最优算法.最后,基于多种拓扑结构进行全面的仿真实验,验证了算法的高能效性和公平性.     

IEEE802．11MAC协议中退避算法的研究

无线信道固有的特点,使得无线局域网面临比有线局域网更多的困难。发展合适的介质访问控制协议（MAC）是无线局域网一个关键,而其中退避算法又是MAC协议考虑的重点。本文介绍了退避机制在IEEE802．11MAC层中的作用．指出了二进制指数退避算法存在的不足。对当前已提出的多种典型退避算法进行了介绍,对各类算法的设计思想进行了分类。最后阐明了退避算法研究的发展趋势。     

Equilibrium analysis through separation of user and network behavior

Internet complexity makes reasoning about traffic equilibrium difficult, partly because users react to congestion. This difficulty calls for an analytic technique that is simple, yet have enough details to capture user behavior and flexibly address a broad range of issues.This paper presents such a technique. It treats traffic equilibrium as a balance between an inflow controlled by users, and an outflow controlled by the network (link capacity, congestion avoidance, etc.). This decomposition is demonstrated with a surfing session model, and validated with a traffic trace and NS2 simulations.The technique’s accessibility and breadth are illustrated through an analysis of several issues concerning the location, stability, robustness and dynamics of traffic equilibrium.     

一种无线传感器网络信道接入自适应慢速退避算法

无线传感器网络是一种特殊的无固定控制中心的多跳网络.由于其特殊性,传统CSMA协议直接应用于无线传感器网络中会带来数据包冲突增加和时延增大等问题.针对信道接入层已有退避算法,提出了一种自适应慢速退避算法.分析与仿真结果表明,与传统的IEEE 802.11标准BEB算法和普通退避算法相比,该算法更为简单实用,能有效提高网络吞吐量,特别是在网路拥塞状况变化剧烈时,可减小额外开销并保持稳定的网络吞吐量.     

Ad Hoc网络中增强TCP性能的MAC退避算法

针对TCP在Ad Hoc网络环境中性能急剧下降的问题,提出一种基于侦听信道连续空闲时隙数的负载自适应退避（LAB）算法。LAB算法通过测量无线信道连续空闲时隙数自适应调节退避窗口,达到优化网络吞吐量的目的。共享一条信道的各节点能在侦听连续空闲时隙数后,收敛到一致的退避窗口。仿真结果表明,与BEB等算法相比,该算法具有更高的网络吞吐量和流间公平性。     

一种基于CoMP的随机接入方案

提出了一种新的基于协作多点传输和接收（CoMP）技术的多发随机接入流程,并根据 随机接入的目的和业务类型设计了接入优先级,在此基础上设计了一种新的随机接入方案, 对 不同类型的随机接入请求提供不同的接入机制,以保证边缘用户的接入性能和满足不同业务 的QoS需求。仿真结果表明,与LTE标准随机接入方案相比,该方案对系统整体接入性能略有 提高,且大大提高了边缘高优先级用户的接入性能。     

Ad Hoc网络基于地理位置的双信道功率退避策略

在地理位置信息的基础上,提出一种双信道功率退避的Ad Hoc网络节能方案。基本思想是控制信道功率由大到小退避,数据信道功率由小到大“退避”。并利用地理位置提供的便利,较好地解决了链路的不对称问题。此外,介绍了功率退避算法,简要分析了成功传输的概率。仿真结果表明,该协议能够满足Ad Hoc网络近距离节点优先通信的设计需求。     

基于子类的汉语动词SCF获取回退

研究证明基于动词子类的回退方法能够改进次范畴化(SCF)自动获取的性能,不同的子类划分方法起到重要的作用。本文利用《同义词词林》、《知网1.2版》和《现代汉语动词大词典》分别对30个测试动词进行分类,并以分类结果来改进汉语动词SCF自动获取的性能,实验结果证明:一、回退后的获取性能有了较为明显的提高;二、涉及句法成分较多的分类方法更适合汉语SCF自动获取;三、随机组合相关动词来构造回退子类是不合理的;四、上述分类都不是适合汉语动词SCF获取回退的最优方法。     

一种新的紫外光自组织通信网络MAC层避退算法

紫外光自组织通信网络是把紫外光与自组织网络相结合的,能够利用自组织网络的多跳特性来克服紫外光距离有限性的通信网络。为了使紫外光自组织通信网络中各个节点能够对有限的信道资源进行充分与公平的利用,需要对网络协议栈中的第二层——媒介接入控制层上的传统算法进行优化。本文以媒质接入控制层(MAC,Media Access Control)传统上采用的二进制指数退避算法为基础,以提高公平性为目的,提出了依据退避计数器值的随机选取是否合理,继而采取相应的奖励惩罚机制的新算法。研究结果表明:新算法提高了无线紫外光自组织通信网络中各节点接入信道的公平性,并在信道吞吐量和信道接入公平性之间达到了一个较好的折衷。     

A backoff strategy for model‐based experiment design under parametric uncertainty

Model‐based experiment design techniques are an effective tool for the rapid development and assessment of dynamic deterministic models, yielding the most informative process data to be used for the estimation of the process model parameters. A particular advantage of the model‐based approach is that it permits the definition of a set of constraints on the experiment design variables and on the predicted responses. However, uncertainty in the model parameters can lead the constrained design procedure to predict experiments that turn out to be, in practice, suboptimal, thus decreasing the effectiveness of the experiment design session. Additionally, in the presence of parametric mismatch, the feasibility constraints may well turn out to be violated when that optimally designed experiment is performed, leading in the best case to less informative data sets or, in the worst case, to an infeasible or unsafe experiment. In this article, a general methodology is proposed to formulate and solve the experiment design problem by explicitly taking into account the presence of parametric uncertainty, so as to ensure both feasibility and optimality of the planned experiment. A prediction of the system responses for the given parameter distribution is used to evaluate and update suitable backoffs from the nominal constraints, which are used in the design session to keep the system within a feasible region with specified probability. This approach is particularly useful when designing optimal experiments starting from limited preliminary knowledge of the parameter set, with great improvement in terms of design efficiency and flexibility of the overall iterative model development scheme. The effectiveness of the proposed methodology is demonstrated and discussed by simulation through two illustrative case studies concerning the parameter identification of physiological models related to diabetes and cancer care. © 2009 American Institute of Chemical Engineers AIChE J, 2010