Sequencing games without initial order

In this note we study uncertainty sequencing situations, i.e., one-machine sequencing situations in which no initial order is specified. We associate cooperative games with these sequencing situations, study their core, and provide links with the classic sequencing games introduced by Curiel et al. (Eur J Oper Res 40:344–351, 1989). Moreover, we propose and characterize two simple cost allocation rules for uncertainty sequencing situations with equal processing times.     

Cooperative games of choosing partners and forming coalitions in the marketplace

Two games of interacting between a coalition of players in a marketplace and the residual players acting there are discussed, along with two approaches to fair imputation of gains of coalitions in cooperative games that are based on the concepts of the Shapley vector and core of a cooperative game. In the first game, which is an antagonistic one, the residual players try to minimize the coalition's gain, whereas in the second game, which is a noncooperative one, they try to maximize their own gain as a coalition. A meaningful interpretation of possible relations between gains and Nash equilibrium strategies in both games considered as those played between a coalition of firms and its surrounding in a particular marketplace in the framework of two classes of n-person games is presented. A particular class of games of choosing partners and forming coalitions in which models of firms operating in the marketplace are those with linear constraints and utility functions being sums of linear and bilinear functions of two corresponding vector arguments is analyzed, and a set of maximin problems on polyhedral sets of connected strategies which the problem of choosing a coalition for a particular firm is reducible to are formulated based on the firm models of the considered kind.     

Kinetics of cooperative conformational transitions of lineal biopolymers

Cooperative conformational transitions of proteins and nucleic acids are of decisive importance to many processes of molecular biology, and particularly to their regulation. They proceed via numerous interdependent elementary processes, and their kinetics are therefore often complicated. They are frequently also very fast. However, kinetic analyses can be carried out by chemical relaxation methods. The theoretical interpretation is comparatively simple in the case of linear biopolymers. When the linear Ising model extended for kinetics was applied to model peptides and polynucleotides, it provided an insight into the fundamental principles of cooperative transformations.     

On the population monotonicity of independent set games

An independent set game is a cooperative game dealing with profit sharing in the maximum independent set problem. A population monotonic allocation scheme is a rule specifying how to share the profit of each coalition among its participants such that every participant is better off when the coalition expands. In this paper, we provide a necessary and sufficient characterization for independent set games admitting population monotonic allocation schemes. Moreover, our characterization can be verified efficiently.     

A new approach to agglomeration problems

In this paper, we study a location problem with positive externalities. We define a new transferable utility game, considering there is no restriction on the transfer of benefits between firms. We prove that the core of this game is non-empty, provide an expression for it, and an axiomatic characterization. We also study several core allocations, selected by means of a certain bankruptcy problem.     

Cooperative Competition Clustering for Gene Selection

Clustering analysis of data from DNA microarray hybridization studies is an essential task for identifying biologically relevant groups of genes. Attribute cluster algorithm (ACA) has provided an attractive way to group and select meaningful genes. However, ACA needs much prior knowledge about the genes to set the number of clusters. In practical applications, if the number of clusters is misspecified, the performance of the ACA will deteriorate rapidly. We propose the Cooperative Competition Cluster Algorithm (CCCA) in this paper. In the algorithm, we assume that both cooperation and competition exist simultaneously between clusters in the process of clustering. By using this principle of Cooperative Competition, the number of clusters can be found in the process of clustering. Experimental results on a synthetic and gene expression data are demonstrated. The results show that CCCA can choose the number of clusters automatically and get excellent performance with respect to other competing methods.     

基于中断概率的多跳混合协作地理路由算法

为了减小无线传感器网络中路由的路径长度,该文提出基于中断概率的多跳混合协作地理路由(MHCGR)算法。首先对不同协作机制的链路进行分析,理论分析表明,在一定中断概率要求下,采用译码放大转发混合协作机制可以进一步扩大传输距离,并推导了每跳协作链路的理想最大协作传输距离和理想中继的位置。在无信标地理路由(BLGR)算法的基础上,MHCGR算法结合节点位置信息为每跳选择最佳的中继节点和转发节点,建立从源节点到目的节点的多跳协作路由。仿真表明,与ENBGCR算法和基于DF协作机制的MPCR算法两种协作地理路由算法相比,MHCGR算法可明显减少路由的跳数,改善路由的整体发射功率。     

基于删除的协作频谱感知分析与优化

能量消耗是协作频谱感知中一个需要重点考虑的问题。为了降低信息上传能耗以延长认知无线网络中能量受限次用户的寿命,该文提出一种新的基于删除的协作频谱感知方案,其核心思想是各次用户仅当感知结果与其前一次不同时才向融合中心发送一个指示信号,否则不发送。对比分析了该方案中的上传能耗问题,并以保证主用户利益为约束条件,给出了频谱感知周期和能量检测门限的优化过程。理论分析和仿真结果表明,相比现有研究,提出的方案可以有效降低次用户的上传能耗而不带来任何感知性能的损失。     

基于OFDM-IM的认知无线电协作中继性能分析

该文针对协作认知无线电网络场景,提出一种基于索引调制正交频分复用(OFDM-IM)的新型协作中继设计方法。该方法将OFDM-IM技术应用于从用户发送端,将从用户的传输空间划分为信号空间和索引空间。从用户在其信号空间上转发主用户的信息,同时在索引空间传输从用户信息。通过这种方式,主、从用户之间不存在相互干扰。针对此模型,该文分析了主、从用户的误码率,理论推导了相关表达式,并讨论了从用户的位置对主、从用户性能的影响。仿真结果表明,该文所提设计方法能够同时提升主、从用户的误码率性能,且均优于传统的基于OFDM的协作中继方式。     

一种基于博弈的联盟组网方法

针对缺乏有效联盟收益分配机制,导致发送端拒绝协作,同时发送信号,造成接收端信号重叠,该文提出一种基于博弈的安全联盟组网方法。首先,将协作博弈机制中的收益分摊机制引入安全联盟组网自适应形成方法,建立发送端联盟组网模型。然后,为实现联盟方式组网,基于博弈方法将联盟组网相比非联盟时增加的总安全速率作为可转移的收益函数,平均分配给组网内各个发送端;之后,发送端遍历所有可能形成的联盟组网,得到均摊收益最大的联盟组网方式;最后,发送端自适应形成该联盟组网,无需发送信号或相同需求下窃听信道条件最坏的发送端发信号,其余所有发送端通过发送人工噪声进行协作。仿真分析验证了该方法的公平性和有效性,当发送端功率等于20 mW时,高斯信道下的网络平均安全速率相比初始状态提高1.8 。