On developing theory of reservoir computing for sensing applications: the state weaving environment echo tracker (SWEET) algorithm

As a paradigm of computation, reservoir computing has gained an enormous momentum. In principle, any sufficiently complex dynamical system equipped with a readout layer can be used for any computation. This can be achieved by only adjusting the readout layer. Owning to this inherent flexibility of implementation, new applications of reservoir computing are being reported at a constant rate. However, relatively few studies focus on sensing, and in the ones that do, the reservoir is often exploited in a somewhat passive manner. The reservoir is used to post-process the signal from sensing elements that are placed separately, and the reservoir could be replaced by other information processing system without loss of functionality of the sensor (‘reservoir computing and sensing’). An entirely different novel class of sensing approaches is being suggested, to be referred to as ‘reservoir computing for sensing’, where the reservoir plays a central role. In the State Weaving Environment Echo Tracker (SWEET) sensing approach, the reservoir functions as the sensing element if the dynamical states of the reservoir and the environment one wishes to analyze are strongly interwoven. Some distinct characteristics of reservoir computing (in particular the separability and the echo state properties) are carefully exploited to achieve sensing functionality. The SWEET approach is formulated both as a generic device setup, and as an abstract mathematical algorithm. This algorithmic template could be used to develop a theory (or a class of theories) of ‘reservoir computing for sensing’, which could provide guidelines for engineering novel sensing applications. It could also provide ideas for a creative recycling of the existing sensing solutions. For example, the Horizon 2020 project RECORD-IT (Reservoir Computing with Real-time Data for future IT) exploits the SWEET sensing algorithm for ion detection. Accordingly, the terms SWEET sensing algorithm and the RECORD-IT sensing algorithm can be used interchangeably.     

大规模联邦仿真中实体迁移及其时间同步研究(二)--实体迁移中的时间同步

实体迁移技术有利于改善大规模分布式仿真系统的性能,其中迁移期间的时间同步是其关键与难点．基于HLA联邦仿真框架,研究了实体迁移中的时间同步机制;分析了迁移期间邦元的状态变迁情况;给出了旧邦元转发消息以及新邦元接收和处理消息时所需的同步策略;保证了按时戳序处理消息．迁移期间新旧邦元逻辑时间同步,防止了丢失消息或重复处理同一消息等现象,也能撤销消息,以便乐观同步．     

大规模联邦仿真中实体迁移及其时间同步研究(一)--实体迁移协议与实现

实体迁移技术有利于改善大规模分布式仿真系统的性能．首先分析了新一代仿真体系结构HLA／RTI对实体迁移支持上的不足和现有HLA兼容型仿真系统中实体迁移实现方法的缺陷：然后提出了在HLA／RTI下进行实体迁移的协议,设计了实体最新状态传输机制、迁移启动机制、迁移期间的消息转发、处理机制等;给出了协议的执行过程和支持实体迁移的仿真应用程序的实现框架;最后测试了协议的正确性．与相关研究相比,迁移协议解决了迁移过程中时间同步问题。不会丢失消息,且能保证TSO消息按时戳序处理．     

多Agent系统分布式问题求解的代数模型方法(Ⅱ): 群体智能和社会动力学

该文是组合论文中第二篇，讨论多Agent系统分布式问题求解的代数模型中的特性层和动力学层，即没粒度Agent群体的宏观群体智能的形式优化代数模型以及宏观社会智能与Agent个体间微观社会行为之间的社会动力学模型，提出了基于这种新的代数模型方法的超分布超并行社会智能问题求解算法，关于分布式多任务自组织规划和资源自组织分配的仿真实验以及与其它方法的比较分析，表明了该文提出了代数模型和问题求解方法的特点和有效性。     

Energy‐efficient scheduling algorithms for batch‐of‐tasks (BoT) applications on heterogeneous computing systems

One of the major design constraints of a heterogeneous computing system is optimal scheduling, that is, mapping of tasks on the processing nodes in order to optimize the QoS parameters. Because of the huge energy consumption by computing resources, negative environmental effects and reduced system reliability, energy has unavoidably been added as a new parameter to the list of QoS parameters. Energy optimization in scheduling strategies along with makespan makes it an even more challenging combinatorial optimization problem. This work proposes two energy‐aware scheduling algorithms G1 and G2 to schedule a batch‐of‐tasks, made of a collection of independent tasks, on heterogeneous processors in order to minimize the makespan and the energy consumption. The proposed algorithms schedule tasks based on weighted aggregation cost function to the appropriate processors followed by task migration phase designed to further minimize the makespan and the energy consumption. The study evaluates the performance of the proposed algorithms with some of the peers, that is, MinMin, MINSuff on account of makespan, energy consumption, flowtime, and utilization. An experimental study reveals that the proposed algorithm (G2) consistently performs better under various test conditions. Copyright © 2015 John Wiley & Sons, Ltd.     

多Agent系统分布式问题求解的代数模型方法(Ⅰ): 社会行为、社会局势和社会动力学

该组论文提出一种新的代数模型方法，用于多Agent系统超分布超并行社会智能问题求解，该方法通过社会动力学和社会智能，统一地处理各种复杂的并行的社会行为，用于求解用常规方法难以处理的许多社会交互问题，本文是组合论文中第一篇，提出多Agent系统分布式问题求解的代数模型结构，讨论多Agent系统中典型社会行为模式及其性质，建立形式化描述，同时也论述了代数模型中的社会局势和社会动力学。