Home / Journals / CSSE / Vol.33, No.4, 2018
  • Open Access

    ARTICLE

    Preface of Special Issue: Future Internet

    Xiulong Liu1, Mianxiong Dong2, Xiaobo Zhou3
    Computer Systems Science and Engineering, Vol.33, No.4, pp. 233-234, 2018, DOI:10.32604/csse.2018.33.233
    Abstract This article has no abstract. More >

  • Open Access

    ARTICLE

    Reliable Differentiated Services Optimization for Network Coding Cooperative Communication System

    Anfeng Liu1, Jie Min1, Kaoru Ota2, Ming Zhao3
    Computer Systems Science and Engineering, Vol.33, No.4, pp. 235-250, 2018, DOI:10.32604/csse.2018.33.235
    Abstract Software-Defined Networking (SDN) is a new network architecture with flexibility and scalability, researchers introduced the core idea of SDN into wireless network, and a cooperative communication system based on network coding is proposed. In this paper, we carry on an investigation in differentiated service strategy of network coding cooperative communication system. The meaning of differentiated services is for the different applications take different power for data transmission and the transmission power is associated with their reliability needs. In other words, transmission power control is performed in the presence of known reliability, we named the scheme Reliability-Bounded Transmission Power Control (RTPC)… More >

  • Open Access

    ARTICLE

    Openflow Based Dynamic Flow Scheduling with Multipath for Data Center Networks

    Haisheng Yu1, Heng Qi1, Keqiu Li1, Jianhui Zhang1,Peng Xiao2, Xun Wang1
    Computer Systems Science and Engineering, Vol.33, No.4, pp. 251-258, 2018, DOI:10.32604/csse.2018.33.251
    Abstract The routing mechanism in Data Center networks can affect network performance and latency significantly. Hash-based method, such as ECMP (Equal-Cost Multi-Path), has been widely used in Data Center networks to fulfill the requirement of load balance. However, ECMP statically maps one flow to a path by a hash method, which results in some paths overloaded while others remain underutilized. Some dynamic flow scheduling schemes choose the most underutilized link as the next hop to better utilize the network bandwidth, while these schemes lacks of utilizing the global state of the network. To achieve high bandwidth utilization and low latency, we… More >

  • Open Access

    ARTICLE

    PPP: Prefix-Based Popularity Prediction for Efficient Content Caching in Contentcentric Networks

    Jianji Ren1, Shan Zhao1, Junding Sun1, Ding Li2, Song Wang3, Zongpu Jia1
    Computer Systems Science and Engineering, Vol.33, No.4, pp. 259-265, 2018, DOI:10.32604/csse.2018.33.259
    Abstract In the Content-Centric Networking (CCN) architecture, popular content can be cached in some intermediate network devices while being delivered, and the following requests for the cached content can be efficiently handled by the caches. Thus, how to design in-network caching is important for reducing both the traffic load and the delivery delay. In this paper, we propose a caching framework of Prefix-based Popularity Prediction (PPP) for efficient caching in CCN. PPP assigns a lifetime (in a cache) to the prefix of a name (of each cached object) based on its access history (or popularity), which is represented as a Prefix-Tree… More >

  • Open Access

    ARTICLE

    Analysis and Application of the Spatio-Temporal Feature in Wind Power Prediction

    Ruiguo Yu1,2, Zhiqiang Liu1,2, Jianrong Wang1,3, Mankun Zhao1,2, Jie Gao1,3, Mei Yu1,3,*
    Computer Systems Science and Engineering, Vol.33, No.4, pp. 267-274, 2018, DOI:10.32604/csse.2018.33.267
    Abstract The spatio-temporal feature with historical wind power information and spatial information can effectively improve the accuracy of wind power prediction, but the role of the spatio-temporal feature has not yet been fully discovered. This paper investigates the variance of the spatio-temporal feature. Based on this, a hybrid machine learning method for wind power prediction is designed. First, the training set is divided into several groups according to the variance of the input pattern, and then each group is used to train one or more predictors respectively. Multiple machine learning methods, such as the support vector machine regression and the decision… More >

  • Open Access

    ARTICLE

    Spectrum Allocation for Cognitive Radio Networks Using the Fireworks Algorithm

    Zhou Feng, Xue Weilian*
    Computer Systems Science and Engineering, Vol.33, No.4, pp. 275-286, 2018, DOI:10.32604/csse.2018.33.275
    Abstract The fireworks algorithm features a small number of parameters, remarkable optimization ability, and resistance to a local optimum. Based on the graph coloring model, the fireworks algorithm is introduced for the first time to solve the spectrum allocation problem for cognitive radio networks, thus maximizing utility and fairness of spectrum allocation. Two-layer binary coding is adopted for individual fireworks. The first layer refers to the coding of cognitive users used to determine channels that can be connected with the user. The second layer refers to the auxiliary coding of channels responsible for addressing mutual interference among multiple cognitive users when… More >

  • Open Access

    ARTICLE

    Topic Evolution Analysis in Social Networking Services: Taking Sina Weibo as an Example

    Yuhui Wang
    Computer Systems Science and Engineering, Vol.33, No.4, pp. 287-291, 2018, DOI:10.32604/csse.2018.33.287
    Abstract Event-related topics in social networking services are always the epitome of heated society issues, therefore determining the significance of analyzing its evolution patterns. In this paper, we present a comprehensive survey on the tweets about "ransomware" in Sina Weibo, a famous social networking service similar to twitter in China. The keyword corresponds to a global ransomware attack in May 2017, on which our example event-related topics are based. We collect text data from sina Weibo and vectorize each tweets, before using a dynamic topic model to discover the event-related topics. The results of the topic model are explainable enough and… More >

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