动态Web服务组合的选择策略

为了提高光网络资源的利用率,提出一种基于Petri网的Web服务组合最优化选择的方法.根据用户需求使用Petri网对服务组合之间的数据依赖关系建模,利用Petri网的T-不变量得到各种可能组合方案,并对于每种组合方案使用广义随机Petri网分析其性能.实验结果表明：该方法充分利用Petri网善于描述、分析、评价分布式系统的优点,得到性能最优的基于光网络资源的服务组合方案.     

一种基于模糊逻辑的物联网访问控制框架研究

访问控制协议是网络中资源安全访问与共享的重要研究内容。为了提高物联网中访问控制协议的可扩展性和能源利用率,提出了一种基于模糊逻辑的访问控制协议。首先通过模糊的信任值对设备间的访问控制权限进行定义。其次,基于经验、知识和推荐的语言模型及其成员函数定义进行信任值的计算。最后提出了一种物联网访问控制框架。最后通过模拟实验表明,随着网络节点个数的增加,平均能量消耗逐渐增大,提出的方法在相同的网络环境下其平均能量消耗小于经典的访问控制方法,而且提出的方法在节点规模增大的情况下,平均能量消耗的增加率逐渐减小,这些表明了提出的方法与传统的访问控制协议相比,可扩展性好,能量利用率高,因而更适用于物联网环境下的访问控制。     

On retrial queueing model with fuzzy parameters

This work constructs the membership functions of the system characteristics of a retrial queueing model with fuzzy customer arrival, retrial and service rates. The α-cut approach is used to transform a fuzzy retrial-queue into a family of conventional crisp retrial queues in this context. By means of the membership functions of the system characteristics, a set of parametric non-linear programs is developed to describe the family of crisp retrial queues. A numerical example is solved successfully to illustrate the validity of the proposed approach. Because the system characteristics are expressed and governed by the membership functions, more information is provided for use by management. By extending this model to the fuzzy environment, fuzzy retrial-queue is represented more accurately and analytic results are more useful for system designers and practitioners.     

Swarmtrust: A swarm optimization-based approach to enhance trustworthiness in smart homes

As smart home networks become increasingly complex and dynamic, maintaining trust between the various devices and services is crucial. Existing trust management approaches face challenges such as high computational overhead and difficulty in selecting optimal parameters. To address these challenges, we propose a new method for trust management in smart home networks based on swarm optimization, a principle of swarm intelligence. Our proposed approach is based on swarm optimization, which is a principle of swarm intelligence that optimizes communication patterns and manages trust values within the network. In SwarmTrust, the nodes in the smart home network are represented by particles, and the positions and velocities of these particles are adjusted to optimize communication patterns and reduce the computational burden on nodes. This optimization is achieved by evaluating the trust values of each node and adjusting the communication patterns accordingly. The proposed method integrates trust management with several distinct parameters and selects the parameters optimally to maintain efficiency. The proposed approach also addresses optimization challenges by monitoring communication patterns and managing trust values in a distributed manner, which reduces the computational burden on nodes and maintains efficiency. To evaluate the effectiveness of our proposed approach, we conducted simulation experiments and compared the performance of our approach with existing methods. Our results showed notable improvements in terms of computational efficiency and optimized computation.     

A Novel MAGDM Method Based on Hesitant Picture Fuzzy Schweizer–Sklar Maclaurin Symmetric Mean Operators and Their Application

Multiple attribute group decision making (MAGDM) issues play important roles in our daily life. In order to solve the problem that decision makers (DMs) may feel hesitant to select the appropriate evaluation values from several possible values in the process of providing evaluations, fuzzy theory and its extensions are widely applied in MAGDM problems. In this study, we first proposed hesitant picture fuzzy sets (HPFSs), which is a combination of the hesitant fuzzy set and picture fuzzy set. Subsequently, we introduced a novel Schweizer–Sklar t-norm and t-conorm operation rules of HPFSs and proposed a family of hesitant picture fuzzy Schweizer–Sklar Maclaurin symmetric mean operators. To show the application procedure of the proposed method to practical MAGDM issues, a numerical example about enterprise informatization level evaluation was employed to elaborate the calculation process with the proposed method. Finally, through the parameter analysis, validity analysis, and comparative analysis with some existing methods, we found that our method is more superior in providing DMs a greater decision-making freedom and relaxing the constraints on expressing personal preferences. This study provides a general framework of the proposed method to MAGDM problems under hesitant picture fuzzy environment, which enriches the fuzzy theory and its applications.     

A Bootstrap Framework for Aggregating within and between Feature Selection Methods

In the past decade, big data has become increasingly prevalent in a large number of applications. As a result, datasets suffering from noise and redundancy issues have necessitated the use of feature selection across multiple domains. However, a common concern in feature selection is that different approaches can give very different results when applied to similar datasets. Aggregating the results of different selection methods helps to resolve this concern and control the diversity of selected feature subsets. In this work, we implemented a general framework for the ensemble of multiple feature selection methods. Based on diversified datasets generated from the original set of observations, we aggregated the importance scores generated by multiple feature selection techniques using two methods: the Within Aggregation Method (WAM), which refers to aggregating importance scores within a single feature selection; and the Between Aggregation Method (BAM), which refers to aggregating importance scores between multiple feature selection methods. We applied the proposed framework on 13 real datasets with diverse performances and characteristics. The experimental evaluation showed that WAM provides an effective tool for determining the best feature selection method for a given dataset. WAM has also shown greater stability than BAM in terms of identifying important features. The computational demands of the two methods appeared to be comparable. The results of this work suggest that by applying both WAM and BAM, practitioners can gain a deeper understanding of the feature selection process.     

A robust decentralized reputation management system for service selection

Reputation mechanism is a novel approach to automate QoS-aware service selection in service oriented computing. The reputation system collects ratings on QoS that consumers feedback and aggregates them to derive a reputation value, which can in turn assist other consumers in service selection in future. However, current approaches fail to combat the malicious ratings and hence the calculated reputation values can be biased severely or even manipulated. Moreover, the centralized management of rating data restricts its application to large open environment. In this paper, we present a robust decentralized reputation system which can resist various unfair ratings and manipulation behaviours. It can evolve and become more mature against malicious ratings with the system running continuously. At last, we experimentally verify the robustness of the proposed approach through a simulation study.     

The Extended Linguistic Hellwig’s Methods Based on Oriented Fuzzy Numbers and Their Application to the Evaluation of Negotiation Offers

This study proposes a novel fuzzy framework for eliciting and organizing the preference information of the negotiator to allow for the evaluation of negotiation offers. The approach is based on verbal evaluation of negotiation options that operates with linguistic variables to handle vague preferences and operationalizes them through oriented trapezoidal fuzzy numbers. Two variants of the linguistic method based on Hellwig’s approach and oriented fuzzy numbers are proposed, which can be applied to building a scoring system for the negotiation template. Then, an example of determining such a scoring system and using it to evaluate the negotiation offers in typical multi-issue negotiation is shown. The results are discussed and compared with other methods known from the literature, in which the preference information is organized similarly but processed differently. The comparison shows that the presented methods can be an alternative to Simple Additive Weighting or TOPSIS methods that may also operate with oriented fuzzy numbers, but some of their characteristics may be problematic from the viewpoint of data interpretation. The former requires defuzzification of the global scores determined, while the latter requires the compulsory use of two reference points derived mechanically out of the negotiation space. By applying modified Hellwig’s approaches, the former and the latter may be easily avoided.     

A spectrum handoff scheme for optimal network selection in Cognitive Radio vehicular networks: A game theoretic auction theory approach

The recent strides in vehicular networks have emerged as a convergence of multi radio access networks having different user preferences, multiple application requirements and multiple device types. In future Cognitive Radio (CR) vehicular networks deployment, multiple radio access networks may coexist in the overlapping areas having different characteristics in terms of multiple attributes. Hence, it becomes a challenge for CR vehicular node to select the optimal network for the spectrum handoff decision. A game theoretic auction theory approach is interdisciplinary effective approach to select the optimal network for spectrum handoff. The competition between different CR vehicular node and access networks can be formulated as multi-bidder bidding to provide its services to CR vehicular node. The game theory is the branch of applied mathematics which make intelligent decision to select the optimal alternative from predetermined alternatives. Hence, this paper investigates a spectrum handoff scheme for optimal network selection using game theoretic auction theory approach in CR vehicular networks. The paper has also proposed a new cost function based multiple attribute decision making method which outperforms other existing methods. Numerical results revel that the proposed scheme is effective for spectrum handoff for optimal network selection among multiple available networks.     

A New Group Decision-Making Technique under Picture Fuzzy Soft Expert Information

As an extension of intuitionistic fuzzy sets, the theory of picture fuzzy sets not only deals with the degrees of rejection and acceptance but also considers the degree of refusal during a decision-making process; therefore, by incorporating this competency of picture fuzzy sets, the goal of this study is to propose a novel hybrid model called picture fuzzy soft expert sets by combining picture fuzzy sets with soft expert sets for dealing with uncertainties in different real-world group decision-making problems. The proposed hybrid model is a more generalized form of intuitionistic fuzzy soft expert sets. Some novel desirable properties of the proposed model, namely, subset, equality, complement, union and intersection, are investigated together with their corresponding examples. Two well-known operations AND and OR are also studied for the developed model. Further, a decision-making method supporting by an algorithmic format under the proposed approach is presented. Moreover, an illustrative application is provided for its better demonstration, which is subjected to the selection of a suitable company of virtual reality devices. Finally, a comparison of the initiated method is explored with some existing models, including intuitionistic fuzzy soft expert sets.     

Social-aware relay selection and energy-efficient resource allocation for relay-aided D2D communication

How to improve the flexibility of limited communication resources to meet the increasing requirements of data services has become one of the research hotspots of the modern wireless communication network. In this paper, a novel social-aware motivated relay selection method is put forward to allocate the energy efficiency (EE) resources for the device-to-device (D2D) communication. To improve system flexibility, a D2D user is selected to act as a relay named D2D-relay instead of the traditional cellular relay. The optimal relay selection strategy is formulated by searching the maximum trust value that is obtained by assessing the link stability and social connections between two users. Then, the resource allocation problem, which turns out to be a mixed-integer nonlinear fractional programming (MINLFP) problem, is solved by maximizing the total EE under physical constraint and social constraint synthetically. To improve the solution efficiency, a novel iterative algorithm is proposed by integrating the Dinkelbach theory and Lagrange dual decomposition method. Simulation results demonstrate the effectiveness of the proposed scheme. Compared with the existing social-blind and social-aware schemes, it significantly improves the probability of successful relay selection and total EE of the D2D pairs.     

New assembly route for three-dimensional metamaterials obtained through effective medium theory

In this study,we illustrate the effective medium theories in the designs of three-dimensional composite metamaterials of both negative permittivity and negative permeability.The proposed metamaterial consists of random coated spheres with sizes smaller compared to the wavelength embedded in a dielectric host.Simple design rules and formulas following the effective medium models are numerically and analytically presented.We demonstrate that the revised Maxwell-Garnett effective medium theory enables us to design three-dimensional composite metamaterials through the assembly of coated spheres which are random and much smaller than the wavelength of the light.The proposed approach allows for the precise control of the permittivity and the permeability and guides a facile,flexible,and versatile way for the fabrication of composite metamaterials.     

大数据服务深度需求与SOA协作集成的异构系统融合机制

大数据服务需求的认知深度和服务架构的融合度直接影响多业务大数据应用的资源管理和服务质量,本文提出了一种基于大数据服务深度需求分析和面向服务的协作集成架构的异构系统融合机制。该机制,一方面,在分析大数据源多样化、差异化大数据组织形式及其存储方式,结合不同类型用户的需求差异化特征,建立了大数据服务需求分析模型。另一方面,对于多态异构的移动互联网大数据服务,经过结构化和开放性处理后,给出大数据通信和服务调用描述定义,提出了SOA协作集成的异构系统融合架构。仿真实验结果表明,所提出的算法在大数据服务响应成功率、执行时间和代价比等方面具有明显优势。     

Information Theory for Agents in Artificial Intelligence,Psychology, and Economics

This review looks at some of the central relationships between artificial intelligence, psychology, and economics through the lens of information theory, specifically focusing on formal models of decision-theory. In doing so we look at a particular approach that each field has adopted and how information theory has informed the development of the ideas of each field. A key theme is expected utility theory, its connection to information theory, the Bayesian approach to decision-making and forms of (bounded) rationality. What emerges from this review is a broadly unified formal perspective derived from three very different starting points that reflect the unique principles of each field. Each of the three approaches reviewed can, in principle at least, be implemented in a computational model in such a way that, with sufficient computational power, they could be compared with human abilities in complex tasks. However, a central critique that can be applied to all three approaches was first put forward by Savage in The Foundations of Statistics and recently brought to the fore by the economist Binmore: Bayesian approaches to decision-making work in what Savage called ‘small worlds’ but cannot work in ‘large worlds’. This point, in various different guises, is central to some of the current debates about the power of artificial intelligence and its relationship to human-like learning and decision-making. Recent work on artificial intelligence has gone some way to bridging this gap but significant questions remain to be answered in all three fields in order to make progress in producing realistic models of human decision-making in the real world in which we live in.     

An optimal protection and restoration scheme (OPARS) for optical networks

Protection and restoration are critical network design issues for optical networks since even a single failure for a short duration may result in huge data loss due to the large capacity of optical fibers. However, few studies have been done on these issues for optical burst switching (OBS) networks. Protection and restoration are essential mechanisms for guaranteeing more reliable traffic delivery services. But it is not easy to apply existing mechanisms to optical burst switching (OBS) networks due to its one-way reservation signaling and the statistical burst multiplexing. Thus, to achieve the high transmission performance and reliability simultaneously, unique properties of OBS must be considered in the design of protection scheme. In this paper, an optimal protection and restoration scheme (OPARS) has been introduced that not only optimizes the number of provisioned protection wavelengths adaptively based on the traffic load as well as the quality of service (QoS) requirements of bursts in high speed networks but also minimizes burst loss rates. In addition, the proposed scheme has been used as an efficient contention resolution technique. The simulation results verify that the proposed scheme improve the network resource and channel utilization while guaranteeing the targeted protection reliability and QoS requirements of bursts.     

Migration to Broadband and Ubiquitous Environments by Using Fiber-Optic Technologies in Access/Home Areas

ABSTRACT

The recent dramatic advances in information and communication technologies have yielded new environments. However, adoption still differs area by area. To realize the future broadband environment that everyone can enjoy everywhere, several technical issues have to be resolved before network penetration becomes ubiquitous. One such key is the use of fiber optics for the home and mobile services. This article overviews initial observations drawn from numerical survey data gathered over the last decade in several countries/regions, and gives some example scenarios for network/service evolution. One result implies that implementing new/future services must consider the gross domestic product impact.     

Fuzzy Representation of Principal’s Preferences in Inspire Negotiation Support System

We consider the negotiation problem, in which an agent negotiates on behalf of a principal. Our considerations are focused on the Inspire negotiation support system in which the principal’s preferences are visualised by circles. In this way, the principal describes the importance of each negotiation issue and the relative utility of each considered option. The paper proposes how this preference information may be implemented by the agent for determining a scoring function used to support decisions throughout the negotiation process. The starting point of our considerations is a discussion regarding the visualisation of the principal’s preferences. We assume here that the importance of each issue and the utility of each option increases with the size of the circle representing them. The imprecise meaning of the notion of “circle size” implies that in a considered case, the utility of an option should be evaluated by a fuzzy number. The proposed utility fuzzification is justified by a simple analysis of results obtained from the empirical prenegotiation experiment. A novel method is proposed to determine trapezoidal fuzzy numbers, which evaluates an option’s utility using a series of answers given by the participants of the experiment. The utilities obtained this way are applied to determine the fuzzy scoring function for an agent. By determining such a common generalised fuzzy scoring system, our approach helps agents handle the differences in human cognitive processes associated with understanding the principal’s preferences. This work is the first approach to fuzzification of the preferences in the Inspire negotiation support system.     

Composite adaptive fuzzy control for synchronizing generalized Lorenz systems

This paper presents a methodology of asymptotically synchronizing two uncertain generalized Lorenz systems via a single continuous composite adaptive fuzzy controller (AFC). To facilitate controller design, the synchronization problem is transformed into the stabilization problem by feedback linearization. To achieve asymptotic tracking performance, a key property of the optimal fuzzy approximation error is exploited by the Mean Value Theorem. The composite AFC, which utilizes both tracking and modeling error feedbacks, is constructed by introducing a series-parallel identification model into an indirect AFC. It is proved that the closed-loop system achieves asymptotic stability under a sufficient gain condition. Furthermore, the proposed approach cannot only synchronize two different chaotic systems but also significantly reduce computational complexity and implemented cost. Simulation studies further demonstrate the effectiveness of the proposed approach.     

An adaptive nonlocal means filter based on fuzzy domain for laser speckle reduction

A new speckle reduction method, i.e., an adaptive nonlocal means based on fuzzy domain (FANLM), is proposed for polarization imaging despeckling. With this method, speckle is removed by an adaptive nonlocal means in Laplacian pyramid domain. The proposed FANLM method calculates the similarity measure in the fuzzy domain, which can make the similarity measure more precise and accurate. In view of the similarity neighborhood selection problem, an adaptive selection algorithm is proposed. The performance of the proposed FANLM method has been compared with the classic methods. Experimental results show that the visual quality and evaluation indexes outperform the other methods. The researches have important reference values in removing speckle noise.     

基于社交网络的观点传播动力学研究

社交网络和微博是重要的Web2.0应用模式, 其观点传播模式与其他网络媒体以及传统媒体相比有很大差异. 本文提出一种基于在线社交网络的观点传播模型, 研究社交网络中舆论观点扩散的形式与特征. 仿真结果表明: 模型中信息传播的速度与六度分割理论的结论十分符合; 一个带强烈倾向性的观点在固有观点均匀分布的网络中传播的情况下, 稳定时网络中不会出现相反的观点; 稳定时的观点分布与源节点的度和回溯深度有关, 并不受信任界限的限制, 这与Deffuant模型和Hegselmann-Krause模型不同. 同时, 本文还分析了传播意愿、观点变更率和信任界限对弛豫时间的影响.