一种基于自适应退避窗口的S-MAC协议改进算法研究

在分析S-MAC协议的工作过程以及退避算法的基础上,针对二进制指数退避机制的缺点进行了改进。通过当前退避窗口值和信道忙计数器来反映当前信道的拥塞状况,使节点自适应地调节退避窗口的大小以减少再次碰撞。仿真结果表明,改进后的S-MAC在高速网络环境中提高了网络的吞吐率,并且减少了能量损耗,表现出更好的网络性能。     

无线传感器SMAC协议竞争退避机制分析及优化

针对无线传感器网络能量受限和退避时采用固定竞争窗口的特点,提出了一种基于节点剩余能量和信道冲突次数的MAC协议（EC—SMAC）．该协议改进了SMAC的竞争退避机制,根据节点剩余能量和信道冲突次数来动态的调整竞争窗口,减少传输节点之间的冲突,从而使全网负载均衡,同时延长网络生命周期．仿真实验表明：在保证网络吞吐量和时延稳定的前提下,平均延长了7％的网络生命周期．     

适用于S-MAC协议的自适应随机退避机制研究

S-MAC协议通过周期性睡眠侦听机制来减少无线传感器网络中节点能量的消耗,但是其在随机退避过程中使用固定竞争窗口,使其在节点碰撞的避免、节点间公平性以及吞吐率上有所欠缺。针对S-MAC的以上不足,基于二进制指数退避算法(BEB)提出自适应指数随机退避算法(AD-BEB)。AD-BEB算法引入了信道竞争能力参数和网络拥挤参数,根据这两个参数对竞争窗口进行调整,并且窗口的调整经过两个阶段来完成。仿真结果表明,AD-BEB算法能够有效地减少节点的碰撞次数,增加网络的吞吐率和节点的公平性。     

一种IEEE 802.11接入机制的新退避算法

无线传感器网络采用类似开放式系统互联模型的协议栈,作为第一个完全针对无线传感网络设计的MAC协议,S-MAC采用了IEEE802.11DCF的接入机制。本文在分析了IEEE802.11协议的二进制指数退避算法(BEB),以及倍数增线性减退避算法(MILD)后,提出了一种基于网络性能指标的新退避算法。新算法将无线信道中的时隙利用率映射网络性能指标传输概率,对网络中连续两次发送的时隙利用率进行平均滤波处理,改变重传节点的发送优先级,来调整节点在竞争使用窗口的退避值,以达到有效减少网络的碰撞、提高无线信道的使用效率和网络吞吐率的目的。仿真结果表明,新退避算法能更准确地估计网络当前的竞争状态,有效地提高了网络吞吐率,获得较好的网络性能。     

面向工业无线汇聚网络的高吞吐率MAC协议

汇聚网络是工业传感器网络的常用拓扑形式。汇聚网络的隐藏终端是影响网络吞吐率的重要因素,目前常用信道预留机制来加以解决。此外,随着物理层数据传输速率的不断提高,相对短报文的现象日渐突出,使得用于信道预留的控制报文的开销相对增加。现有的IEEE802.11 DCF不能同时有效应对这两个现象。提出了取消信道预留方式来克服相对短报文问题,而对于由于信道预约取消所导致的隐藏终端问题,则以随机发送机制解决。为了获得最优的发送概率,设计了APCSMA协议,该协议以最大化节点吞吐率为目标,提出吞吐率最大化的必要条件,基于该必要条件,在主干扰模型下推导出节点均匀分布情况下的最优报文发送概率。从理论上分析了协议的网络吞吐率、延迟和能量效率。仿真结果和分析表明,APCSMA协议对于工业无线汇聚网络具有广泛的适用性。     

无线传感器网络SMAC协议的节能改进

分析SMAC协议的工作过程以及自适应侦听的原理,针对该机制存在的无谓侦听问题提出改进方案。在协议中引入上下节点表,使节点自行判断是否应当被唤醒,避免无谓侦听,减少能量损耗,同时对该改进方案进行仿真。实验结果表明,该方案是有效的。     

一种基于功率控制的无线传感器网络MAC协议

提出了一种基于功率控制的无线传感器网络MAC协议,根据节点接收阈值,计算出节点发送最优功率,在根本上减小发送功率从而节省节点能量。为了减少节点间的碰撞,引入了自适应调整竞争窗口和快速退避机制,减少节点空闲时间,从而进一步减少节点耗能。仿真结果显示在能量和吞吐量上都有显著提高。     

支持服务区分的多智能体Q学习MAC算法

媒体访问控制(MAC)协议负责协调所有认知用户的空闲信道接入服务,是认知 Ad-hoc 网络支持服务质量(QoS)的关键技术之一。在二进制指数退避算法基础上,提出一种支持服务区分的多智能体Q学习MAC算法。实时调整传输概率,使系统信道接入服务达到最优,建立传输概率调节的Markov链模型,导出分组的传输概率与协议参数的关系,给出基于服务区分的信道吞吐率模型,建立基于MAC协议参数学习的多智能体Q学习算法。实验结果表明,该算法能满足高优先级业务的QoS,且吞吐率和时延性能优于IEEE 802.11e EDCA机制。     

基于信道占用及优先级的MAC协议退避算法

针对Ad Hoc网络MAC协议（SPMA协议）的退避时间问题,为降低包与包之间的冲突并提高信道利用率,提出了一种基于信道占用及优先级的自适应退避算法（A-COP算法）。分析了退避时间对系统性能的影响以及现有退避算法的不足;根据SPMA协议的特点以及初等函数模型建立退避算法模型;基于OPNET对该模型进行系统仿真,并与原算法协议模型进行比较。仿真结果表明,基于该算法的SPMA协议通过对低优先级业务的接入控制,可使系统吞吐量更加稳定,并且可满足高优先级业务高通信质量的要求。     

高速飞行器自组织网络MAC协议研究

高速飞行器自组织网络具有节点运行速度快、网络拓扑高度动态变化、多种优先级保障需求等特点。介绍高速飞行器自组织网络的网络组成和协议栈架构，提出一种适用于高动态场景的自组织网络协议栈设计，MAC层采用统计优先级多址接入协议(Statistical Priority-based Multiple Access, SPMA)。针对SPMA协议退避时间问题，提出一种自适应退避时间算法，可以根据优先级等级、门限阈值和信道占用统计值动态调整退避时间以达到更好的退避效果，并利用OPNET平台对SPMA协议进行系统建模与仿真分析。实验结果表明，SPMA协议可以实现多种优先级差异化服务，自适应退避时间算法能有效地提升SPMA协议吞吐量性能，进一步降低高优先级分组的丢包率和平均时延。     

自适应人机界面的新模型机制探讨

当前,自适应界面已成为人机界面研究的一个方向.本文首先介绍了有关人机界面和自适应界面的一些基本概念,并在此基础上提出了一个人机界面的自适应机制,并提出智能Agent是计算机领域中自适应人机界面设计思路之一,给出了基于Agent的用户模型的结构框图,探讨了用户界面Agent及其构建方法.     

A hybrid device for the solution of sampling bias problems in the forecasting of firms’ bankruptcy

This paper proposes a new approach to the forecasting of firms’ bankruptcy. Our proposal is a hybrid method in which sound companies are divided in clusters using Self Organized Maps (SOM) and then each cluster is replaced by a director vector which summarizes all of them. Once the companies in clusters have been replaced by director vectors, we estimate a classification model through Multivariate Adaptive Regression Splines (MARS). For the test of the model we considered a real setting of Spanish enterprises from the construction sector. With this procedure we intend to overcome the sampling-bias problems that matched-pairs models often suffer. We estimated two benchmark models: a back propagation neural network and a simple MARS model. Our results show that the proposed hybrid approach is much more accurate than the benchmark techniques for the identification of the bankrupt companies.     

基于NS2的802.11协议教学实验设计

提出使用NS2设计一个802.11协议的教学实验,并介绍了实验过程。在隐蔽站条件下测量吞吐量和延迟,加深对隐蔽站问题、虚拟载波侦听机制和确认机制的理解。测量节点耗能,并与SMAC协议进行比较,认识802.11协议的耗能性能。该实验使用TCL脚本语言即可完成,无需使用C++,难度适中,为802.11协议的实验教学提出一种方案,有助于学生实践能力的培养。     

饱和状态下IEEE 802.11e EDCA机制的建模分析

建立了一个合适的IEEE 802.11e EDCA信道接入机制的数学分析模型。首先深入研究了IEEE 802.11e EDCA机制;在此基础上提出了一种新型的饱和状态下EDCA分析模型。该模型采用二维Markov链的分析方法,分别考虑了不同业务在进行退避时,检测到信道忙的概率以及不同业务退避到零,发送数据帧时发生冲突的概率在多业务竞争中产生的影响。进一步地,对该模型进行了延迟分析。数学分析和仿真实验的对比表明,该模型能够很好地描述IEEE 802.11e EDCA信道接入机制的MAC接入延迟。     

基于竞争窗口递减因子自适应调整退避算法

包括IEEE802.11、802.15.4标准在内的许多无线网络协议都采用二进制指数退避机制管理数据的重发。在动态分布式的网络环境中,二进制指数退避算法固定的竞争窗口递减方式难以适应动态变化的网络规模。针对这一问题,提出了一种改进的回退机制,该机制通过引入竞争窗口递减因子,自适应地调整无线节点的等待时间,以实现网络吞吐量的最大化。同时,在算法实现上提出一种启发式算法以跟踪网络中竞争节点数量的改变。在IEEE 802.11DCF协议中以相同的物理层参数进行仿真,结果表明改进算法提高了网络吞吐量,降低了分组平均接入时延。     

A New Grid Scheduler with Failure Recovery and Rescheduling Mechanisms: Discussion and Analysis

Computational Grids (CGs) have become an appealing research area. They suggest a suitable environment for developing large scale parallel applications. CGs integrate a huge mount of distributed heterogeneous resources for constituting a powerful virtual supercomputer. Scheduling is the most important issue for enhancing the performance of CGs. Various strategies have been introduced, including static and dynamic behaviors. The former maps tasks to resources at submission time, while the latter operates at run time. While static scheduling is unsuitable for the dynamic Grid environment, scheduling in CGs is still more complex than the proposed dynamic solutions. This paper introduces a decentralized Adaptive Grid Scheduler (AGS) based on a novel rescheduling mechanism. AGS has several salient properties as it is; hybrid, adaptive, decentralized, and efficient. Also, AGS is a robust mechanism as it has the ability to; (i) detect resource failures, (ii) continue its functionality in spite of the failure existence, then (iii) recover back. Moreover, it integrates both static and dynamic scheduling behaviors. An initial static scheduling map is proposed for an input Direct Acyclic Graph (DAG). However, DAG tasks may be rescheduled if the performance of the allocated resources changes in away that may affect the tasks’ response time. AGS overcomes drawbacks of traditional schedulers by utilizing the mobile agent unique features to enhance the resource discovery and monitoring processes. Experimental results have shown that AGS outperforms traditional Grid schedulers as it introduces a better scheduling efficiency.     

Improving the SMAC atmospheric correction code by analysis of Meteosat Second Generation NDVI and surface reflectance data

In order to obtain high quality data, the correction of atmospheric perturbations acting upon land surface reflectance measurements recorded by a space-based sensor is an important topic within remote sensing. For many years the Second Simulation of the Satellite Signal in the Solar Spectrum (6S) radiative transfer model and the Simplified Method for Atmospheric Correction (SMAC) codes have been used for this atmospheric correction, but previous studies have shown that in a number of situations the quality of correction provided by the SMAC is low. This paper describes a method designed to improve the quality of the SMAC atmospheric correction algorithm through a slight increase in its computational complexity. Data gathered from the SEVIRI aboard Meteosat Second Generation (MSG) is used to validate the additions to SMAC, both by comparison to simulated data corrected using the highly accurate 6S method and by comparison to in-situ and 6S corrected SEVIRI data gathered for two field sites in Africa. The additions to the SMAC are found to greatly increase the quality of atmospheric correction performed, as well as broaden the range of atmospheric conditions under which the SMAC can be applied. When examining the Normalised Difference Vegetation Index (NDVI), the relative difference between SMAC and in-situ values decreases by 1.5% with the improvements in place. Similarly, the mean relative difference between SMAC and 6S reflectance values decreases by a mean of 13, 14.5 and 8.5% for Channels 1, 2 and 3 respectively. Furthermore, the processing speed of the SMAC is found to remain largely unaffected, with only a small increase in the time taken to process a full SEVIRI scene. Whilst the method described within this paper is only applicable to SEVIRI data, a similar approach can be applied to other data sources than SEVIRI, and should result in a similar accuracy improvement no matter which instrument supplies the original data.     

Power management in SMAC-based energy-harvesting wireless sensor networks using queuing analysis

One of the most important constraints in traditional wireless sensor networks is the limited amount of energy available at each sensor node. The energy consumption is mainly determined by the choice of media access mechanism. SMAC is a typical access mechanism that has drawn much attention in recent years. In WSNs, sensors are usually equipped with capacity-limited battery sources that can sustain longer or shorter period, depending on the energy usage pattern and the activeness level of sensor nodes. To extend the lifetime of the sensor networks, ambient energy resources have been recently exploited in WSNs. Even though solar radiation is known as the superior candidate, its density varies over time depending on many factors such as solar intensity and cloud states, which makes it difficult to predict and utilize the energy efficiently. As a result, how to design an efficient MAC in a solar energy harvesting based WSN becomes a challenging problem. In this paper, we first incorporate a solar energy-harvesting model into SMAC and conduct its performance analysis from a theoretical aspect. Our research works provide a fundamental guideline to design efficient MAC for energy harvesting based WSNs. Our major contribution includes three folders: firstly, we model solar energy harvesting in a photovoltaic cell and then derive the throughput of SMAC in the energy-harvesting based WSNs. Second, we develop a new model based on queuing theory to calculate the average number of energy packets in battery in terms of both duty cycle and throughput. Finally, we form an optimization problem to find a suitable range for the duty cycle to satisfy both quality of service (QoS) and network lifetime requirements.     

Comparison of methods for developing dynamic reduced models for design optimization

In this paper we compare three methods for forming reduced models to speed up genetic-algorithm-based optimization. The methods work by forming functional approximations of the fitness function which are used to speed up the GA optimization by making the genetic operators more informed. Empirical results in several engineering design domains are presented.This research was funded in part by a sub-contract from the Rutgers-based Self Adaptive Software project supported by the Advanced Research Projects Agency of the Department of Defense and by NASA under grant NAG2-1234.     

基于竞争允许TDMA的无线传感器MAC层协议

无线传感器网络在许多重要领域有着广泛的应用，而传感网的媒体访问控制子层(MAC)协议对传感器网络的运行和性能具有重要影响。该文概述了目前存在的传感网MAC协议的设计思想，在SMAC协议的基础上，将TDMA和CSMA两种思想结合起来并与SMAC协议同步机制相统一，提出了一个新的基于竞争允许TDMA的无线传感器网络MAC协议。模拟结果显示，与SMAC协议相比，该协议在数据包延迟、能量消耗及数据包的接收率等性能上有很大提高。