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Cache replication for information-centric networks through programmable networks 通过可编程网络实现信息中心网络的缓存复制
Pub Date : 2019-08-09 DOI: 10.1504/IJGUC.2019.10023106
E. B. Nascimento, E. Moreno, D. D. J. D. Macedo
Software-Defined Networking (SDN) is a new approach that decouples control from the data transfer function and can be directly programmable by the programming language. At the same time, Information-Centric Networks (ICNs) influence the search for information through network caching and multipart communication. Moreover, these projects are developed to solve traffic problems and have content transfer through a scalable network structure with simple management. The SDN covers ICNs, besides decoupling the control to allow flexibility of network settings to reduce overhead of segments. Based on this information, an architecture was designed to provide reliable content that can be replicated in the network. The ICN architecture proposed stores information through a logical volume to the next access, enabling connection with remote controllers for reliable storage in cloud environments. The cache efficiency achieved almost 50% reduction of time response, in addition, there was improvement around 10% when the number of parallel requests was increased.
软件定义网络(SDN)是一种将控制与数据传输函数解耦的新方法,可以通过编程语言直接对其进行编程。同时,信息中心网络(ICNs)通过网络缓存和多部分通信影响着信息的搜索。此外,这些项目的开发是为了解决流量问题,并通过可扩展的网络结构进行内容传输,管理简单。SDN涵盖ICNs,除了解耦控制以允许网络设置的灵活性以减少段开销之外。基于这些信息,设计了一个体系结构来提供可在网络中复制的可靠内容。提出的ICN架构通过逻辑卷将信息存储到下一个访问,实现与远程控制器的连接,从而在云环境中实现可靠的存储。缓存效率几乎减少了50%的时间响应,此外,当并行请求的数量增加时,有大约10%的改进。
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引用次数: 1
Towards autonomous creation of service chains on cloud markets 在云市场上自主创建服务链
Pub Date : 2019-08-09 DOI: 10.1504/IJGUC.2019.10023105
Benedikt Pittl, I. Haq, W. Mach, E. Schikuta
Today, cloud services, such as virtual machines, are traded directly at fixed prices between consumers and providers on platforms, e.g. Amazon EC2. The recent development of Amazon's EC2 spot market shows that dynamic cloud markets are gaining popularity. Hence, autonomous multi-round bilateral negotiations, also known as bazaar negotiations, are a promising approach for trading cloud services on future cloud markets. They play a vital role for composing service chains. Based on a formal description we describe such service chains and derive different negotiation types. We implement them in a simulation environment and evaluate our approach by executing different market scenarios. Therefore, we developed three negotiation strategies for cloud resellers. Our simulation results show that cloud resellers as well as their negotiation strategies have a significant impact on the resource allocation of cloud markets. Very high as well as very low mark-ups reduce the profit of a reseller.
今天,云服务,如虚拟机,在平台上的消费者和供应商之间直接以固定价格进行交易,例如亚马逊EC2。最近亚马逊EC2现货市场的发展表明,动态云市场越来越受欢迎。因此,自主多轮双边谈判,也称为集市谈判,是在未来云市场上交易云服务的一种很有前途的方法。它们对于组成服务链起着至关重要的作用。基于形式化描述,我们描述了这些服务链,并派生出不同的协商类型。我们在模拟环境中实现它们,并通过执行不同的市场场景来评估我们的方法。因此,我们为云经销商制定了三种谈判策略。仿真结果表明,云经销商及其谈判策略对云市场的资源配置有显著影响。过高和过低的加价都会减少经销商的利润。
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引用次数: 0
An autonomic mechanism based on ant colony pattern for detecting the source of incidents in complex enterprise systems 基于蚁群模式的复杂企业系统事件源检测自主机制
Pub Date : 2019-07-18 DOI: 10.1504/IJGUC.2019.10022685
Kamaleddin Yaghoobirafi, E. Nazemi
In complex enterprises, various events such as failure of a server, malfunction of an application etc. may happen. In many cases, these events are caused by a change or an incident in a resource which belongs to another layer of information technology architecture. This makes the detection of complex events very difficult. In this paper, a mechanism is proposed based on pheromone deposition pattern for detecting the main source of failures and deficiencies in any position in the information technology architectural layers and recognising appropriate alternative solutions. It is expected that this mechanism facilitates the coordination between the resources which are not digitally represented. For sake of evaluation, two case studies are considered which investigate the inter-layer adaptation scenarios. The results show that the adaptation process can be done in less time and with more scalability with utilisation of the proposed mechanism in comparison with classic approaches.
在复杂的企业中,可能会发生各种事件,如服务器故障、应用程序故障等。在许多情况下,这些事件是由属于另一层信息技术体系结构的资源中的更改或事件引起的。这使得检测复杂事件变得非常困难。本文提出了一种基于信息素沉积模式的机制,用于检测信息技术架构层中任何位置的故障和缺陷的主要来源,并识别适当的替代解决方案。预计这一机制将促进未以数字方式表示的资源之间的协调。为了进行评价,本文考虑了两个研究层间适应情景的案例。结果表明,与传统方法相比,利用该机制可以在更短的时间内完成自适应过程,并具有更大的可扩展性。
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引用次数: 12
Facial expression recognition using geometric features and modified hidden Markov model 基于几何特征和改进隐马尔可夫模型的面部表情识别
Pub Date : 2019-07-18 DOI: 10.1504/IJGUC.2019.10022683
M. Rahul, Narendra Kohli, Rashi Agarwal, Sanju Mishra
This work proposes a geometric feature-based descriptor for efficient Facial Expression Recognition (FER) that can be used for better human-computer interaction. Although lots of research has been focused on descriptor-based FER still different problems have to be solved regarding noise, recognition rate, time and error rates. The Japanese Female Facial Expression (JAFFE) data sets help to make FER more reliable and efficient as pixels are distributed uniformly. The proposed system introduces novel geometric features to extract important features from the images and layered Hidden Markov Model (HMM) as a classifier. The layered HMM is used to recognised seven facial expressions i.e., anger, disgust, fear, joy, sadness, surprise and neutral. The proposed framework is compared with existing systems where the proposed framework proves its superiority with the recognition rate of 84.7% with the others 85%. Our proposed framework is also tested in terms of recognition rates, processing time and error rates and found its best accuracy with the other existing systems.
这项工作提出了一种基于几何特征的描述符,用于有效的面部表情识别(FER),可以用于更好的人机交互。尽管基于描述符的FER已经得到了大量的研究,但在噪声、识别率、时间和错误率等方面还有待解决。日本女性面部表情(JAFFE)数据集有助于使FER更可靠和高效,因为像素分布均匀。该系统引入新颖的几何特征提取图像的重要特征,并采用分层隐马尔可夫模型作为分类器。分层HMM用于识别七种面部表情,即愤怒、厌恶、恐惧、喜悦、悲伤、惊讶和中性。将该框架与现有系统进行了比较,结果表明,该框架的识别率为84.7%,其他系统的识别率为85%。我们提出的框架还在识别率、处理时间和错误率方面进行了测试,并发现它与其他现有系统具有最佳的准确性。
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引用次数: 19
A new bi-matrix game model with fuzzy payoffs in credibility space 可信度空间中具有模糊收益的双矩阵对策模型
Pub Date : 2019-07-18 DOI: 10.1504/ijguc.2019.101997
Cunlin Li, Ming Li
Uncertain theory based on expert's evaluation and non-additive measure is introduced to explore the bi-matrix game with the uncertain payoffs. The uncertainty space based on the axiom of the uncertain measures is presented. Some basic characteristics of uncertain events are described and the expected value of the uncertain variables is given in uncertainty space. A new model of bi-matrix game with uncertain payoffs is established and its equivalent strategy is given. Then, we develop an expected model of uncertain bi-matrix games and define the uncertain equilibrium strategy of uncertain bi-matrix games. By using the expected value of uncertain variable, we transform the model into a linear programming, the expected equilibrium strategy of the uncertain bi-matrix games is identified through solving linear equations.
引入基于专家评价和非加性测度的不确定理论,研究具有不确定收益的双矩阵对策。提出了基于不确定测度公理的不确定空间。描述了不确定事件的一些基本特征,给出了不确定变量在不确定空间中的期望值。建立了一种新的具有不确定收益的双矩阵对策模型,并给出了其等价策略。然后,建立了不确定双矩阵对策的期望模型,定义了不确定双矩阵对策的不确定均衡策略。利用不确定变量的期望值,将该模型转化为线性规划,通过求解线性方程确定不确定双矩阵对策的期望均衡策略。
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引用次数: 0
An enhanced Jaya algorithm for solving nurse scheduling problem 一种改进的Jaya算法求解护士调度问题
Pub Date : 2019-07-18 DOI: 10.1504/IJGUC.2019.10022662
W. H. Elashmawi, A. Ali
Nurse Scheduling Problem (NSP) is one of the main optimisation problems that require an efficient assignment of a number of nurses to a number of shifts in order to cover the hospital's planning horizon demands. NSP is an NP-hard problem which subjects to a set of hard and soft constraints. Such problems can be solved by optimisation algorithms efficiently such as meta-heuristic algorithms. In this paper, we enhanced one of the most recent meta-heuristic algorithms which is called Jaya for solving the NSP. The enhanced algorithm is called EJNSP (Enhanced Jaya for Nurse Scheduling Problem). EJNSP focuses on maximising the nurses' preferences about shift requests and minimising the under- and over-staffing. EJNSP has two main strategies. First, it randomly generates an initial effective scheduling that satisfies a set of constraints. Second, it uses swap operators in order to satisfy the set of soft constraints to achieve an effective scheduling. A set of experiments have been applied to a set of the benchmark dataset with different numbers of nurses and shifts. The experimental results demonstrated that EJNSP algorithm achieved effective results for solving NSP in order to minimise the under- and over-staffing and satisfy the nurses' preferences.
护士调度问题(NSP)是一个主要的优化问题,需要有效地分配一些护士到一些班次,以覆盖医院的规划地平线的需求。NSP是一个NP-hard问题,它受制于一组硬约束和软约束。这些问题可以通过优化算法如元启发式算法有效地解决。在本文中,我们改进了一种最新的元启发式算法,称为Jaya,用于解决NSP问题。该算法被称为EJNSP (enhanced Jaya for nurses Scheduling Problem)。EJNSP侧重于最大限度地提高护士对轮班请求的偏好,并最大限度地减少人员配备不足和过剩。ejjsp有两个主要策略。首先,随机生成满足一组约束条件的初始有效调度。其次,利用交换算子来满足软约束集,实现有效的调度。一组实验应用于一组具有不同数量护士和班次的基准数据集。实验结果表明,EJNSP算法在解决NSP问题上取得了有效的结果,以最大限度地减少人员不足和过剩,满足护士的偏好。
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引用次数: 1
An efficient content sharing scheme using file splitting and differences between versions in hybrid peer-to-peer networks 在混合型点对点网络中,利用文件分割和版本间差异的高效内容共享方案
Pub Date : 2019-07-18 DOI: 10.1504/IJGUC.2019.10022665
Toshinobu Hayashi, S. Sugawara
This paper proposes an efficient content sharing strategy using file splitting and difference between versions in hybrid Peer-to-Peer (P2P) networks. In this strategy, when a user requests a content item, he/she can get it from the network by retrieving the other version of the content item and the difference from the requested version, if the obtaining cost of the requested version is expensive. This way of content sharing can be expected to accomplish effective and flexible operation. Furthermore, efficient utilisation of a peer's storage capacity is achieved by splitting each replica of a content item into several small blocks and storing them separately in the plural peers.
提出了一种基于文件分割和版本差异的混合P2P网络内容共享策略。在这种策略中,当用户请求一个内容项时,如果获得请求版本的成本很高,他/她可以通过检索内容项的另一个版本以及与请求版本的差异从网络中获得该内容项。这种内容共享方式可以实现有效而灵活的操作。此外,通过将内容项的每个副本分成几个小块并将它们单独存储在多个对等节点中,可以有效地利用对等节点的存储容量。
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引用次数: 0
Novel mobile palmprint databases for biometric authentication 用于生物识别认证的新型移动掌纹数据库
Pub Date : 2019-07-18 DOI: 10.1504/IJGUC.2019.10019524
Mahdieh Izadpanahkakhk, S. Razavi, Mehran Taghipour-Gorjikolaie, Seyyed Hamid Zahiri, A. Uncini
Mobile palmprint biometric authentication has attracted a lot of attention as an interesting analytics tool for representing discriminative features. Despite the advances in this technology, there are some challenges including lack of enough data and invariant templates to the rotation, illumination, and translation. In this paper, we provide two mobile palmprint databases and we can address the aforementioned challenges via deep convolutional neural networks. In the best of our knowledge, this paper is the first study in which mobile palmprint images were acquired in some special views and then were evaluated via deep learning training algorithms. To evaluate our mobile palmprint images, some well-known convolutional neural networks are applied for verification task. By using these networks, the best performing results are achieved via GoogLeNet and CNN-F architectures in terms of cost of the training phase and classification accuracy of the test phase obtained in the 1-to-1 matching procedure.
移动掌纹生物识别作为一种表示鉴别特征的有趣分析工具,引起了人们的广泛关注。尽管该技术取得了进步,但仍存在一些挑战,包括缺乏足够的数据和旋转、照明和平移的不变模板。在本文中,我们提供了两个移动掌纹数据库,我们可以通过深度卷积神经网络解决上述挑战。据我们所知,本文是第一个在某些特殊视图下获取移动掌纹图像,然后通过深度学习训练算法进行评估的研究。为了对我们的手机掌纹图像进行评估,应用了一些著名的卷积神经网络进行验证任务。通过使用这些网络,在1对1匹配过程中获得的训练阶段的成本和测试阶段的分类精度方面,通过GoogLeNet和CNN-F架构获得了最佳的性能结果。
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引用次数: 7
An intelligent water drops-based approach for workflow scheduling with balanced resource utilisation in cloud computing 云计算中基于智能水滴的平衡资源利用工作流调度方法
Pub Date : 2019-07-18 DOI: 10.1504/ijguc.2019.101995
Mala Kalra, Sarbjeet Singh
The problem of finding optimal solutions for scheduling scientific workflows in cloud environment has been thoroughly investigated using various nature-inspired algorithms. These solutions minimise the execution time of workflows, however may result in severe load imbalance among Virtual Machines (VMs) in cloud data centres. Cloud vendors desire the proper utilisation of all the VMs in the data centres to have efficient performance of overall system. Thus, load balancing of VMs becomes an important aspect while scheduling tasks in cloud environment. In this paper, we propose an approach based on Intelligent Water Drops (IWD) algorithm to minimise the execution time of workflows while balancing the resource utilisation of VMs in cloud computing environment. The proposed approach is compared with a variety of well-known heuristic and meta-heuristic techniques using three real-time scientific workflows, and experimental results show that the proposed algorithm performs better than these existing techniques in terms of makespan and load balancing.
利用各种受自然启发的算法,对云环境中科学工作流调度的最佳解决方案问题进行了深入研究。这些解决方案最大限度地减少了工作流的执行时间,但可能导致云数据中心中虚拟机(vm)之间的严重负载不平衡。云供应商希望正确利用数据中心中的所有虚拟机,以实现整个系统的高效性能。因此,在云环境中,虚拟机的负载均衡成为任务调度的一个重要方面。在本文中,我们提出了一种基于智能水滴(IWD)算法的方法,以最大限度地减少工作流的执行时间,同时平衡云计算环境中虚拟机的资源利用率。利用三种实时科学工作流,将所提算法与各种知名的启发式和元启发式技术进行了比较,实验结果表明,所提算法在makespan和负载均衡方面优于现有技术。
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引用次数: 8
Fog computing with original data reference function 雾计算具有原始数据参考功能
Pub Date : 2019-07-18 DOI: 10.1504/IJGUC.2019.10022667
Tsukasa Kudo
In recent years, since large amounts of data are being transferred to the cloud server because of the evolution of the Internet of Things (IoT), problems such as the network bandwidth restrictions and sensor feedback control delays have appeared. For these limitations, fog computing, in which the primary processing of sensor data is performed at the fog node, and only the results are transferred to the cloud server, has been proposed. However, in this method, when the original sensor data are necessary for the analysis in the cloud server, the data are missing. For this problem, I propose a data model, in which the original sensor data are stored at the fog node with a distributed database. Furthermore, the performance of this data model is evaluated, showing the original data reference from the cloud server can be executed efficiently, particularly in the case of installing multiple fog nodes.
近年来,由于物联网(IoT)的发展,大量数据被传输到云服务器,出现了网络带宽限制和传感器反馈控制延迟等问题。针对这些限制,提出了雾计算,其中传感器数据的主要处理在雾节点上进行,只有结果才传输到云服务器。然而,在这种方法中,当原始传感器数据需要在云服务器中进行分析时,数据丢失。针对这个问题,我提出了一个数据模型,其中原始传感器数据用分布式数据库存储在雾节点上。此外,对该数据模型的性能进行了评估,表明来自云服务器的原始数据引用可以有效地执行,特别是在安装多个雾节点的情况下。
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引用次数: 0
期刊
Int. J. Grid Util. Comput.
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