异构无线网络中基于信任度的接入选择算法

针对异构无线网络不确定性的特点,提出一种基于信任度的接入选择算法。引入直接信任度、推荐信任度、推荐主体可信度和信任时间戳4个参量计算网络的信任度,利用信任度对网络性能指标进行信任加权。同时,综合考虑用户个人偏好,对网络进行逼近理想解排序,得到最佳接入网络。仿真实验结果表明,该方法综合考虑了网络多种性能指标及其信任度,能提高异构无线网络中用户选择网络的安全性。     

An objective approach to MADM with interval numbers

In ambiguous decision domain, interval numbers are always employed to model multiple attribute decision making （MADM） problems, in which attribute values of alternatives are expressed in the form of intervals. In this study, a new approach is proposed for the interval MADM problems： The interval decision matrix is transformed into definite one by comparing the interval attribute values with the base intervals of attributes; The attribute weights are determined based on the definite decision matrix; the alternatives are assessed based on TOPSIS. An example of assessing the faculty candidates （alternatives） is used to illustrate the proposed approach.     

基于多属性判决的网络选择算法

异构网络中,针对如何根据不同业务的特性选择合适的判决参数并利用这些参数来选择最适合的网络以及通过网络负载均衡来减少切换次数和切换失败可能性等问题,提出了一种基于多属性判决的网络选择算法——TAU-MADM算法.考虑到网络客观属性和用户偏好,进行两次判决:第一次判决采用TOPSIS算法,仅考虑网络客观属性,当备选网络方案相当接近时进行第二次判决;第二次判决采用AHP算法计算权重,并采用ANP网络分析法消除属性之间的依赖性,之后构造效用函数,根据每个网络的效用函数值进行网络选择.仿真结果表明,该算法考虑了网络负载均衡,有效地降低了平均切换率和平均切换阻塞卒.     

制造资源混合粒度优化组合方案求解技术

为实现对云请求端制造需求的快速响应并提供最理想的制造云,在定义制造云服务(manufacturing cloudservice,MCS)的基础上,提出了MCS混合粒度动态优化组合方法.通过对制造服务需求的解析,将MCS按照粒度从大到小的顺序进行匹配,实现了云池资源的初次过滤;然后构建基于总服务成本、服务质量和交易期的制造云多目标优化数学模型,并引入Epsilon-SPEA2优化算法对该优化问题进行求解,从而快速高效地获得Pareto最优解;采用基于改进优劣解距离(technique for order preference by similarity to an ideal solution,TOPSIS)的动态多属性决策方法对Pareto最优解所代表的互为非支配的MCS组合方案进行评价排序,筛选出最优的MCS组合方案.最后结合某区域模具公司群所能提供的制造服务以及相应历史数据,依据客户需求进行MCS的动态优化组合仿真,验证了文中方法的可行性和实用性.     

火电厂建设项目影响评价及其环境因素分析

火电厂建设项目影响评价有利于控制项目风险.对火电厂建设项目影响评价中环境影响要素及指标进行了细致的分析,并对影响状况、相应处理措施及管理水平进行审查评估.利用TOPSIS法对火电机组环境影响状况进行实例评价,提出改进建议.     

基于AHP—TOPSIS的渗透测试工具的综合评价模型

综合TOPSIS和AHP方法,针对网络安全工具难以精确抉择的问题,提出一种简单、易实现且灵活性较强的综合评价模型.首先是从各个工具的功能、使用平台、使用人员期望以及用户评分等4个评判指标进行展开分析,建立出综合评价模型的指标体系;其次,利用AHP法和Matlab软件确定各指标相应的客观权重并进行综合分析并建立判断矩阵;...     

基于NSGA-Ⅱ算法的小型分布式能源系统设计优化

以大连市某小型居民建筑为对象,采用DeST软件,得到该建筑的冷、热、电及生活热水负荷。通过确定建筑在工作日、周末的逐时内、外热扰,计算建筑夏、冬季典型日逐时负荷。以年总费用和年CO₂、NO₂排放量为目标函数,以负荷间的能流平衡、设备的性能为约束,得到系统设备容量配置的Pareto最优解集。通过TOPSIS优选法得到最优容量配置。最后与传统分供系统对比,系统最优方案解集具有运行节能和环保优势。     

TOPSIS‐based approach for network slice selection in 5G mobile systems

Fifth‐generation (5G) mobile networks can be perceived as highly manageable systems that provide increased performance while supporting a variety of services with widely diverse requirements. Recently, network slicing has been proposed by academia and industry as a resource provisioning technique capable to meet these requirements with reduced operating costs while opening new horizons for network efficiency. The aim of network slice selection function (NSSF) is an optimal selection of network instances serving the users, based on local configuration, and other available information including radio access networks (RANs) performances in the registration area. In this paper, NSSF based on Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) is proposed. Here, the network slices are treated as alternatives while their performance indicators are considered as the criteria for decision making. The influences of various alternative techniques, taking into account all the three stages of decision making process, that is, normalization, weighting, and ranking, are analyzed through the rank reversal phenomenon and computational complexity. Simulation results reveal that the proposed techniques can significantly improve the network slice selection procedure.     

边缘计算模式下的电力用户能效评估方法

为提高电力用户能效评估的客观性和准确性，并满足用户对于用电能效及时反馈调整的需求，提出一种在边缘架构下实时动态评估电力用户能效的方法。在构建边缘侧评估框架的基础上，首先，基于“压力-状态-响应”概念模型分析指标间的动态逻辑关系，从多维度选取动态评价指标，构建用户能效评估指标集合。考虑到边缘节点存储资源的受限，从集合中抽象出指标的重要性、均衡性、独立性三重指标属性进行量化，通过影响度和优化度模型对3种属性的量化值进行融合，并采用合作博弈论优选边缘侧精简指标集，从而有效地对边缘侧数据去冗余。其次，基于CRITIC(criteria importance though intercrieria correlation)权重计算法，充分利用指标的数据信息，对本方法所提指标赋予更为客观的权重系数。最后，通过改进灰色TOPSIS(technique for order preference by similarity to an ideal solution)评估方法构造绝对理想解，以有效避免用户数量动态变化时所产生的逆排序问题，引入的灰色关联度可弥补传统方法中欧式判据无法准确衡量用户优劣性的缺陷...     

Adaptive Handover Decision Inspired By Biological Mechanism in Vehicle Ad-hoc Networks

In vehicle ad-hoc networks (VANETs), the proliferation of wireless communication will give rise to the heterogeneous access environment where network selection becomes significant. Motivated by the self-adaptive paradigm of cellular attractors, this paper regards an individual communication as a cell, so that we can apply the revised attractor selection model to induce each connected vehicle. Aiming at improving the Quality of Service (QoS), we presented the bio-inspired handover decision-making mechanism. In addition, we employ the Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS) for any vehicle to choose an access network. This paper proposes a novel framework where the bio-inspired mechanism is combined with TOPSIS. In a dynamic and random mobility environment, our method achieves the coordination of performance of heterogeneous networks by guaranteeing the efficient utilization and fair distribution of network resources in a global sense. The experimental results confirm that the proposed method performs better when compared with conventional schemes.