Game‐Based Valley‐Fill Charging Coordination for Large‐Population Plug‐in Electric Vehicles

Charging coordination of large‐population autonomous plug‐in electric vehicles (PEVs) in the power grid can be formulated as a class of constrained optimization problems. To overcome the computational complexity, a game‐based method is proposed for the charging problems of the PEV population, which is composed of homogeneous subpopulations, such that individuals update their best charging strategies simultaneously with respect to a common electricity price determined by the total demand. To mitigate the oscillation behavior caused by the greedy behavior for the cheap electricity by individuals, a deviation cost is introduced to penalize against the deviation of the individual strategy from the average value of the homogeneous subpopulation. By adopting a proper deviation cost and following a best strategy update mechanism, the game systems may converge to the socially optimal valley‐fill Nash equilibrium. Simulation examples are studied to illustrate the results.     

基于Web的办公自动化系统研究与设计

针对传统办公方式存在效率低下和数据不能共享且处理繁琐的缺点,提出了一种基于Web的办公自动化管理方式。介绍了办公自动化系统的设计目标、总体设计及主要模块组成,针对各模块特点进行了详细描述,解决了传统办公方式中存在的纸张浪费和各级各部门间信息资源不能共享等固有缺点,降低了办公费用,实现了多人协同办公,提高了工作效率。最后,通过实例验证了基于Web的办公自动化软件的高效性及数据共享性。     

自主-合作教学模式在C＋＋程序设计教学改革中的应用

针对在C＋＋程序设计课程教学中存在的问题,结合对自主-合作教学模式的研究,提出以自主学习教学模式贯穿教学始终;案例驱动的精讲与泛读相结合;手写程序与机器调试相结合;自主学习与合作学习相结合的教学新思路。并阐述了上述方法在教学改革实践中的具体应用及效果。     

An analysis on decentralized adaptive MAC protocols for cognitive radio networks

The scarcity of bandwidth in the radio spectrum has become more vital since the demand for more and more wireless applications has increased. Most of the spectrum bands have been allocated although many studies have shown that these bands are significantly underutilized most of the time. The problem of unavailability of spectrum and inefficiency in its utilization has been smartly addressed by the cognitive radio (CR) technology which is an opportunistic network that senses the environment, observes the network changes, and then uses knowledge gained from the prior interaction with the network to make intelligent decisions by dynamically adapting their transmission characteristics. In this paper, some of the decentralized adaptive medium access control (MAC) protocols for CR networks have been critically analyzed, and a novel adaptive MAC protocol for CR networks, decentralized non-global MAC (DNG-MAC), has been proposed. The results show the DNG-MAC outperforms other CR-MAC protocols in terms of time and energy efficiency.     

A suboptimal joint bandwidth and power allocation for cooperative relay networks＂ a cooperative game theoretic approach

In commercial networks, user nodes operating on batteries are assumed to be selfish to consume their resources (i.e., bandwidth and power) solely maximizing their own benefits (e.g., the received signal-to-noise ratios (SNRs) and datarates). In this paper, a cooperative game theoretical framework is proposed to jointly perform the bandwidth and power allocation for selfish cooperative relay networks. To ensure a fair and efficient resource sharing between two selfish user nodes, we assume that either node can act as a source as well as a potential relay for each other and either node is willing to seek cooperative relaying only if the datarate achieved through cooperation is not lower than that achieved through noncooperation (i.e., direct transmission) by consuming the same amount of bandwidth and power resource. Define the cooperative strategy of a node as the number of bandwidth and power that it is willing to contribute for relaying purpose. The two node joint bandwidth and power allocation (JBPA) problem can then be formulated as a cooperative game. Since the Nash bargaining solution (NBS) to the JBPA game (JBPAG) is computationally difficult to obtain, we divide it into two subgames, i.e., the bandwidth allocation game (BAG) and the power allocation game (PAG). We prove that both the subgames have unique NBS. And then the suboptimal NBS to the JBPAG can be achieved by solving the BAG and PAG sequentially. Simulation results show that the proposed cooperative game scheme is efficient in that the performance loss of the NBS result to that of the maximal overall data-rate scheme is small while the maximal-rate scheme is unfair. The simulation results also show that the NBS result is fair in that both nodes could experience better performance than they work independently and the degree of cooperation of a node only depends on how much contribution its partner can make to improve its own performance.     

Fair relay selection in decode-and-forward cooperation based on outage priority

The opportunistic cooperation schemes,where only the "best" relay is selected to forward the message,have been widely investigated recently for their good performance in terms of outage probability.However,the unfair selections of relays may cause unbalance power consumptions among relays,which reduces the lifetime of energy constrained networks.In this paper,we introduce a novel concept of outage priority based fairness(OPF),aiming at improving the selection fairness among relays appropriately without outage performance deterioration.Then,a cooperation scheme is proposed to meet this concept,and corresponding theoretical analysis is also provided.Afterward,based on OPF,the achievable upper bound of the fairness is derived,and an optimal cross-layer designed scheme is also provided to achieve the bound.Numerical simulations are carried out finally,which not only validate the theoretical analysis,but also show that taking advantages of the proposed schemes,the fairness among all relays,as well as the network lifetime,can be greatly improved without any loss of outage performance,especially in high SNR regime.     

灾害中生活类物资的供应分析——以汶川地震重灾区物资供应为例

救灾生活类物资在供应中面临着优化运输路线、降低运输成本、缩短运输时间3个难题。文章采用相关机会多目标规划模型,以汶川地震为例,总结并完善了自然灾害救助中的多物资的协作供应模式,为突发性重大灾害中多物资的协作供应的组织、实施、管理提供参考支持。     

一个基于XCS的同质团队学习模型

同质团队学习是实现多Agent协作的一种方法。但是,传统方法仅在系统运行的前后对目标Agent进行修改,系统运行过程没有直接对Agent的改进做出贡献。本文利用合作策略,在学习分类器系统XCS的基础上提出了一种同质团队学习模型,弥补了传统方法的上述不足。文中还在模型的基础上实验分析了相关因素,如规则积累、通信以及发现新规则等对多Agent协作效率的影响。     

一种MANET环境下基于兴趣度的协同缓存策略

MANET网络中由于节点移动的随机性和无线链路的断连性,导致网络拓扑变化频繁,从而降低了数据可访问能力.提出一种基于兴趣度的协同缓存策略(IBCC).其主要思想是:针对节点转发的数据请求消息,引入ω-稳定节点集定义和兴趣度概念,定期挖掘ω-稳定节点集中具有相同兴趣度的数据形成预取集;针对回复的数据消息形成数据定位表,通过查找数据定位表将请求发送给同样拥有该数据但路由跳数较少的节点.该策略提高了在出现链路断接时节点对数据的访问能力.仿真实验结果证明该策略的有效性.     

网络随机延时的双端协同拥塞控制策略

针对ABR业务流在传输过程中存在随机延时导致网络节点不能得到平稳控制的问题,提出一种网络源端和节点端同时参与控制的双端协同拥塞控制策略。OPNET网络仿真环境下的试验结果表明,该控制策略能够有效地克服随机延时对信息传输的影响,实现节点队列长度的有效平稳控制,降低节点端信元的丢弃概率,改善网络服务质量和传输效率。