To realize the sharing and reuse of sensor data and improve interoperability, semantic sensor web(SSW)is proposed to add semantics information to existing sensor networksby utilizing domain, spatial and temporal antho...
详细信息
The time-critical online contest environment calls for an elegant and precise management system to start a contest online. The management system should simultaneously follow three rules of security that are confidenti...
详细信息
The time-critical online contest environment calls for an elegant and precise management system to start a contest online. The management system should simultaneously follow three rules of security that are confidentiality, anonymity and fairness. We present in this paper a novel system named Secure Synchronized Reading (SSR) system as well as its corresponding security model according to the three rules. SSR can evoke a synchronized start for all competitors in a contest at the intended time by employing a Randomness-reused Identity-Based Encryption (RIBE) scheme. It can avoid huge differences among delivery delays of heterogeneous competitors and any false start by an adverse competitor. Consequently when an online contest begins, the SSR system performs quasi real-time with ignorable communication delays in the security model. As a complement, the analysis on the provable security of SSR is given finally, as well as a further analysis on the achievement of synchronization.
A Bayesian optimization algorithm (BOA) belongs to estimation of distribution algorithms (EDAs). It is characterized by combining a Bayesian network and evolutionary algorithms to solve nearly decomposable optimizatio...
详细信息
ISBN:
(纸本)9781479938414
A Bayesian optimization algorithm (BOA) belongs to estimation of distribution algorithms (EDAs). It is characterized by combining a Bayesian network and evolutionary algorithms to solve nearly decomposable optimization problems. BOA is less popularly applied to solve high dimensionality complex optimization problems. A key reason is that the cost of training all dimensions by BOA becomes expensive with the increase of problem dimensionality. Since data are relatively sparse in a high dimensional space, even though BOA can train all dimensions simultaneously, the interdependent relations between different dimensions are difficult to learn. Its search ability is thus significantly reduced. In this paper, we propose a team of Bayesian optimization algorithms (TBOA) to search and learn dimensionality. TBOA consists of multiple BOAs, in which each BOA corresponds to a dimension of the solution domain and it is responsible for the search of this dimension's value region. The proposed TBOA is used to solve the real problem of task assignment in heterogeneous computingsystems. Extensive experiments demonstrate that the computational cost of the overall training in TBOA is decreased very significantly while keeping high solution accuracy.
The creation of value-added services by automatic composition of existing ones is gaining a significant momentum as the potential silver bullet in service-oriented architecture. However, service composition faces two ...
详细信息
The creation of value-added services by automatic composition of existing ones is gaining a significant momentum as the potential silver bullet in service-oriented architecture. However, service composition faces two aspects of difficulties. First, users' needs present such characteristics as diversity, uncertainty and personalisation; second, the existing services run in a real-world environment that is highly complex and dynamically changing. These difficulties may cause the emergence of nondeterministic choices in the process of service composition, which has gone beyond what the existing automated service composition techniques can handle. According to most of the existing methods, the process model of composite service includes sequence constructs only. This article presents a method to introduce conditional branch structures into the process model of composite service when needed, in order to satisfy users' diverse and personalised needs and adapt to the dynamic changes of real-world environment. UML activity diagrams are used to represent dependencies in composite service. Two types of user preferences are considered in this article, which have been ignored by the previous work and a simple programming language style expression is adopted to describe them. Two different algorithms are presented to deal with different situations. A real-life case is provided to illustrate the proposed concepts and methods. [ABSTRACT FROM AUTHOR]
A multi-cluster tool is composed of a number of single-cluster tools linked by buffering modules. The capacity of a buffering module can be one or two. Aiming at finding an optimal one-wafer cyclic schedule, this work...
详细信息
Petri net is an important tool to model and analyze concurrent systems, but Petri net models are frequently large and complex, and difficult to understand and modify. Slicing is a technique to remove unnecessary parts...
详细信息
Interacting with a random environment, Learning Automata (LAs) are automata that, generally, have the task of learning the optimal action based on responses from the environment. Distinct from the traditional goal of ...
详细信息
ISBN:
(纸本)9781479938414
Interacting with a random environment, Learning Automata (LAs) are automata that, generally, have the task of learning the optimal action based on responses from the environment. Distinct from the traditional goal of Learning Automata to select only the optimal action out of a set of actions, this paper considers a multiple-action selection problem and proposes a novel class of Learning Automata for selecting an optimal subset of actions. Their objective is to identify the optimal subset: the top k out of r actions. Based on conventional continuous pursuit and discretized pursuit learning schemes, this paper introduces four pursuit learning schemes for selecting the optimal subset, called continuous equal pursuit, discretized equal pursuit, continuous unequal pursuit and discretized unequal pursuit learning schemes, respectively. In conjunction with a reward-inaction learning paradigm, the above four schemes lead to four versions of pursuit Learning Automata for selecting the optimal subset. The simulation results present a quantitative comparison between them.
Online shopping integrating third-party payment platforms (TPPs) has rapidly developed recently. The integration leads to new security problems derived from complex interactions among Application Programming Interface...
详细信息
In this paper, we investigate the synchronization problem for nonlinearly coupled networks under periodically intermittent pinning control, where the coupling matrix denoting network topology is assumed to be symmetri...
详细信息
ISBN:
(纸本)9781467355339
In this paper, we investigate the synchronization problem for nonlinearly coupled networks under periodically intermittent pinning control, where the coupling matrix denoting network topology is assumed to be symmetric. A sufficient condition to guarantee global synchronization is presented. Moreover, a centralized adaptive intermittent control is designed and its validity is rigorously proved. Finally, some numerical examples are presented to demonstrate the correctness of obtained theoretical results.
In this paper,the cluster synchronization problem for nonlinearly coupled networks under periodically intermittent pinning control is *** first,a sufficient condition to guarantee cluster synchronization is ***,an ada...
详细信息
ISBN:
(纸本)9781479900305
In this paper,the cluster synchronization problem for nonlinearly coupled networks under periodically intermittent pinning control is *** first,a sufficient condition to guarantee cluster synchronization is ***,an adaptive intermittent control algorithm is designed to the control strength and its validity is rigorously ***,some numerical examples are presented to demonstrate the correctness of obtained theoretical results.
暂无评论