节点移动处理的高效RPL路由协议

针对低功耗有损网络（low-power and lossy network,LLN）的节点移动问题,提出基于博弈论自适应调整传输速率的移动RPL路由（GT-mRPL）。GT-mRPL路由通过博弈论传输速率,进而获取高的数据分组传递率和吞吐量。在移动环境中,将节点竞争发送数据过程设计成一个游戏。将通过增加传输率所获取的增益（效用函数）与因节点移动而产生的成本（移动函数）的比值看成收益函数。同时,考虑能耗对收益函数的影响。仿真结果表明,在移动环境下,提出的GT-mRPL路由降低了数据分组丢失率,提高了吞吐量。     

基于重叠联盟博弈的无人机侦察时间资源分配优化

在利用多无人机进行多目标侦察时,需要进行合理的任务分配。优化无人机资源与任务重要程度之间的关系,才能充分发挥多无人机侦察的优势。为了实现多无人机协同侦察时的时间资源分配优化,首先根据任务点和无人机的位置分布情况对多无人机进行预分配,然后对预分配后的空闲无人机进行协同时间资源优化。将空闲无人机协同时间资源分配问题建模为重叠联盟博弈模型,通过对所构建模型的求解,得出多无人机的协同侦察时间资源分配方案。仿真结果表明,优化时间资源后侦察系统的收益得到了提升。     

三网融合形势下FTTH规模发展关键问题分析及管理研究

FTTH(光纤到户)是三网融合形势下最具潜力的接入技术。通过博弈论中计算纳什均衡解的方法,揭示了运营企业大规模发展FTTH的内在驱动和经济规律。通过对创新理论的研究,总结出网络互补性资产的最大使用限度是决定FTTH规模化成败的关键,并基于创新扩散模型,提出FTTH二阶段网络建设管理模式。最后,针对FTTH规模发展中ODN(光纤分配网络)的标准化建设和端口造价的控制问题,基于15万FTTH端口建设过程的实证分析,给出了当前ODN设计中两种不同集中分光技术的比较以及每线综合造价的数学模型。     

Defense decision-making method based on incomplete information stochastic game and Q-learning

Most of the existing stochastic games are based on the assumption of complete information,which are not consistent with the fact of network attack and defense.Aiming at this problem,the uncertainty of the attacker’s revenue was transformed to the uncertainty of the attacker type,and then a stochastic game model with incomplete information was constructed.The probability of network state transition is difficult to determine,which makes it impossible to determine the parameter needed to solve the equilibrium.Aiming at this problem,the Q-learning was introduced into stochastic game,which allowed defender to get the relevant parameter by learning in network attack and defense and to solve Bayesian Nash equilibrium.Based on the above,a defense decision algorithm that could learn online was designed.The simulation experiment proves the effectiveness of the proposed method.     

Markov game modeling of mimic defense and defense strategy determination

Network mimic defense technology enhances the robustness of active defense through the redundancy,dynamic and diversity as well as the decision feedback mechanism.However,little work has been done for its security assessment and existing classic game models are not suitable for its dynamic characteristics and lack of universality.A Markov game model was proposed to analyze the transfer relationship between offensive and defensive status and the measurement method of safety and reliability of mimic defense,and calculated the offensive and defensive game equilibrium through non-linear programming algorithm to determine the best defensive strategy considering performance.Experiments give a comparison with the multi-target hiding technique and shows that the mimic defense has a higher defensive effect.Combining with the specific network case,the specific attack and defense path for the exploit of the system vulnerability is given and the effectiveness of the defense strategy algorithm is verified.     

Coverage control algorithm for wireless sensor networks based on non-cooperative game

For the redundancy coverage of nodes leads to the phenomenon of low energy efficiency,Non-cooperative game theory was used to solve it.A revenue function was proposed,which considering the coverage of nodes and the residual energy.The lifetime of the node and network path gain were applied to revenue function.The network topology was built by nodes with the appropriate work strategy.Control algorithm coverage in wireless sensor network was proposed based on Non-cooperative game theory.A Nash equilibrium between the coverage rate and the residual energy was proved,and the return function converged to the Pareto optimal.Experiments show that the algorithm can provide reasonable coverage of network nodes and ensure energy efficiency.     

Game-theoretical analysis of mobile contributors in mobile crowd sourcing network with word of mouth mode

The crowdsourcer who calls for sensing service can recruit enough mobile contributors quickly with the word of mouth mode,improving the quality of sensing tasks.The behavior of mobile contributors in mobile crowdsourcing with the WoM was investigated.It was supposed that each mobile contributor was rational,seeking for the highest utility.The behavior of mobile contributors with a two-level Stackelberg game was formulated.In the first-level game,a mobile contributor who directly worked for the crowdsourcer acted as the leader,while contributors invited by first-level contributors were followers called the second-level contributors.In the second-level game,the second-level contributors were the leaders and contributors invited by them were followers.The Nash equilibrium for each Stackelberg game was proved was existed and unique,and designed an algorithm to reach the equilibrium.Backward induction approach to compute the best response of each game was adopted,and the simulation results show the correctness of theoretical analysis for the interaction among contributors in crowdsoucing with WoM.     

基于博弈模型的互联网低俗内容监管可行性研究

运用博弈工具分析我国互联网低俗内容监管,是为了从理论上真正搞清楚这样一个问题,即通过监管是否能够防止低俗内容在互联网上广泛传播。以博弈的视角对低俗内容的来源——内容提供商、平台服务提供商及以政府为主导的监管方的相关行为进行分析,在三者之间建立博弈模型,通过对其均衡解的分析揭示互联网内容监管的可行性。结论是肯定的,即互联网低俗内容监管机构与内容平台提供商之间能够实现(不检查,不违规)这一理想均衡状态,同时还可以采取措施避免另外两种均衡(不检查,违规)和(检查,违规)的出现。尽管我国互联网低俗内容监管的现状并不如此,但通过多样化的监管措施,防止互联网服务商违规是可实现的。     

高效混合式协同检测方法研究

针对单个节点检测性能容易受多径、阴影效应的影响,提出一种基于模糊聚类和D S证据理论的协同检测方法:首先依据协同节点的拓扑结构和距离信息,采用模糊C均值算法对节点聚类,然后利用OR准则对各聚类内的检测结果进行融合,各聚类之间采用D S证据理论进行融合;最后建立博弈概率分布,根据最大概率原则做出最终判决。仿真结果表明,在可控计算复杂度的情况下,该方法检测性能比传统方法有很大提高,而且在虚警概率为10%时,检测概率能达到90%以上。     

适合中小运营商的网游优化方案

随着互联网应用的爆炸式发展,越来越丰富的网络应用给网络的管理和控制带来了巨大的挑战,其中如何在有限的网络资源下,保证网络游戏等对延时、丢包等指标高度敏感的网络应用的用户体验,成了中小网络运营商的一大难题。为解决此问题,提出了一个结合客户端和网络端的新型的游戏加速解决方案,在不进多线机房或使用DPI技术的情况下,仍能实现对网络游戏加速服务。之后通过实验模拟了一个网络拥堵的环境,并在这个环境下测试了游戏加速服务的效果,实验结果显示,该方案确实可以在不额外扩充网络资源的情况下,确保网络游戏的用户体验。这一方案还可以进一步推广到其他类似的网络应用上去,具有重要的商业价值。