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Cloud Service Composition Using Genetic Algorithm and Particle Swarm Optimization

Cloud Service Composition Using Genetic Algorithm and Partic...

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international econference on Computer and Knowledge Engineering (ICCKE)

作者： Javad Dogani Farshad Khunjush Shiraz University Shiraz Iran

ISBN: (纸本)9781665402095

Cloud computing indicates the on-demand accessibility of computer system resources, especially data storage and computing capabilities that users manage without direct intervention. One of the benefits of using cloud computing services is that companies can use the computing resources they need. Cloud service composition with service quality awareness is a crucial requirement in service-oriented computing, as it enables users to perform complex operations while meeting service quality constraints. Since there are multiple services in the distributed cloud space, the problem space is enormous and choosing the optimal composition is often very complex, which is considered NP-hard. In this paper, a new method using a combination of genetic algorithm and particle swarm optimization algorithm is presented for cloud services composition, which uses exploration and exploitation of these algorithms simultaneously. Our proposed method aims to establish a proper balance between different performance goals to composition these services. We evaluated our approach on the QWS real dataset and compared the results with multiple baseline methods. Based on the number of different generations and services, the proposed method outperforms the basic algorithms and two previous studies and delivers 5% to 15% improvement compared to baseline methods in terms of different criteria.

关键词： Q-factor Cloud computing Web services NP-hard problem Memory Particle swarm optimization Standards

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Detection and Mitigation of DDoS Attacks Using Conditional Entropy in Software-defined networking 11

Detection and Mitigation of DDoS Attacks Using Conditional E...

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11th international conference on Advanced computing (ICoAC)

作者： Xuanyuan, Ming Ramsurrun, Visham Seeam, Amar Middlesex Univ Sch Sci & Technol Flic En Flac Mauritius

ISBN: (数字)9781728152868

ISBN: (纸本)9781728152868

Software-defined networking (SDN) is a relatively new technology that promotes network revolution. the most distinct characteristic of SDN is the transformation of control logic from the basic packet forwarding equipment to a centralized management unit called controller. However, the centralized control of the network resources is like a double-edged sword, for it not only brings beneficial features but also introduces single point of failure if the controller is under distributed denial of service (DDoS) attacks. In this paper, we introduce a light-weight approach based on conditional entropy to improve the SDN security with an aim of defending DDoS at the early stage. the experimental results show that the proposed method has a high average detection rate of 99.372%.

关键词： DDoS DDoS detection Mitigation SDN Entropy

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Service Function Chaining and Traffic Steering in SDN using Graph Neural Network 11

Service Function Chaining and Traffic Steering in SDN using ...

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11th international conference on Information and Communication Technology Convergence (ICTC) - Data, Network, and AI in the age of Untact (ICTC)

作者： Rafiq, Adeel Khan, Talha Ahmed Afaq, Muhammad Song, Wang-Cheol Jeju Natl Univ Comp Engn Jeju South Korea

ISBN: (纸本)9781728167589

In the network softwarization, Network Function Virtualisation (NFV) has shifted the standard of network services deployment and management for telecommunication. However, the allocation of physical resources to the Virtualised Network Functions (VNFs) dynamically, efficiently, and autonomously is one of the key tasks to achieve this objective. Network designing is a serious factor for the deployment of VNFs to create a Service Function Chaining (SFC) with efficient resource utilization and optimal path in the edge computing environment. the development of a self-driven Software-Defined Network (SDN) also requires an intelligent network design, especially to find optimum routing patterns for traffic steering that meet the goals set by administrators. But unfortunately, the current network designing methods do not fulfill the desired requirement for precise estimations of related performance metrics. Recently, the application of Artificial Intelligence (AI) is considered by the research community to operate and control the network. the Graph Neural Network (GNN) is adopted as an AI solution in the field of the network because GNN can understand the complex relationship between network traffic features, routing, and topology to produce an accurate estimation of relevant performance metrics. In this paper, we propose the implementation of the Knowledge-Defined networking (KDN) system based on Graph Neural Network (GNN) to predict the optimal path for SFC deployment and traffic steering. the proposed system is evaluated using the complete virtualized environment which is composed of ONOS, OpenStack, and open-source MANO (OSM).

关键词： software-defined network virtualized network functions knowledge-defined networking graph neural network service function chaining

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11th international conference on Intelligent networking and Collaborative Systems, INCoS 2019

11th International Conference on Intelligent Networking and ...

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11th international conference on Intelligent networking and Collaborative Systems, INCoS 2019

ISBN: (纸本)9783030290344

the proceedings contain 57 papers. the special focus in this conference is on Intelligent networking and Collaborative Systems. the topics include: A novel bounded-error piecewise linear approximation algorithm for streaming sensor data in edge computing;A message relaying method with a dynamic timer considering non-signal duration from neighboring nodes for vehicular DTN;a 2-dimensional technology and real-world interaction view approach;event management service system;method for extracting positions of players from video of lacrosse game;digital university admission application system with study documents using smart contracts on blockchain;algorithm using deep learning for recognition of japanese historical characters in photo image of historical book;proposing a blockchain-based open data platform and its decentralized oracle;performance analysis of wmns by wmn-psohc-dga simulation system considering linearly decreasing inertia weight and linearly decreasing vmax replacement methods;visualization of users raking in online dating service;performance evaluation of V2V and V2R communication based on 2-wavelength cognitive wireless network on road state information gis platform;a machine learning approach to fake news detection using knowledge verification and natural language processing;short-term solar power forecasting using svr on hybrid pv power plant in indonesia;optical axis estimation method using binocular free space optics;enhancing security of cellular IoT with identity federation;reversible data hiding algorithm in homomorphic encrypted domain based on ec-eg;impact of automation to event management efficiency;a new fair electronic contract signing protocol;captcha recognition based on kohonen maps;development and evaluation of iot/m2m application using real object oriented model;movies recommendation system.

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Evaluation of Data and Subprocess Transmission Strategies in the Tree-Based Fog computing Model 22nd

Evaluation of Data and Subprocess Transmission Strategies in...

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11th international conference on Intelligent networking and Collaborative Systems (INCoS) / 22nd international conference on Network-Based Information Systems (NBiS)

作者： Oma, Ryuji Nakamura, Shigenari Duolikun, Dilawaer Enokido, Tomoya Takizawa, Makoto Hosei Univ Tokyo Japan Rissho Univ Tokyo Japan

ISBN: (纸本)9783030290290;9783030290283

In order to increase the performance of the IoT (Internet of things), the fog computing model is proposed. Here, subprocesses of an application process to handle sensor data are performed on fog nodes in addition to servers. In the TBFC (Tree-Based Fog computing) model proposed in our previous studies, an application process to handle sensor data is assumed to be a sequence of subprocesses, i.e. linear model. At each level of a TBFC tree, a same subprocess is performed on every node. In this paper, we consider a more general model, GTBFC (General TBFC) model of the IoT where subprocesses of an application process are structured in a tree. Each subprocess in the process tree is performed on fog nodes which are at a same level in the GTBFC tree. Each leaf subprocess is performed on edge nodes which communicate with sensor and actuator devices. We also proposed MEG (Minimum Energy in the GTBFC tree) and SMPRG (Selecting Multiple Parents for Recovery in the GTBFC tree) algorithms to select a new parent node for a child node of a faulty node in the GTBFC tree. In the evaluation, we show the energy consumption of nodes in the SMPRG algorithm as 21% and 31% smaller than the MEG and RD (Random) algorithms.

关键词： General TBFC (GTBFC) model Process tree Equivalent nodes Faults of fog nodes MEG algorithm SMPRG algorithm

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TNRAS: Tor Nodes Reliability Analysis Scheme 2021

TNRAS: Tor Nodes Reliability Analysis Scheme

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2021 the 11th international conference on Communication and Network Security

作者： Wenzhen Zhang Tianbo Lu Zeyu Du School of Computer Science (National Pilot Software Engineering School) Beijing University of Posts and Telecommunications China and Key Laboratory of Trustworthy Distributed Computing and Service (BUPT) Beijing University of Posts and Telecommunications China School of Computer Science (National Pilot Software Engineering School) School of Cyberspace Security Beijing University of Posts and Telecommunications China and Key Laboratory of Trustworthy Distributed Computing and Service (BUPT) Beijing University of Posts and Telecommunications China

ISBN: (纸本)9781450386425

With the rapid Internet development, the security attacks become more and more noteworthy that people have paid more concentration on personal privacy. the Onion Router (Tor), a distributed anonymous communication network, has gradually come into our field of vision for secure communicating on the Internet. However, there are still several security issues like the Sybil attack in Tor, which pose a non-negligible threat to both the network and its users. this paper proposes an ideal method Tor nodes reliability analysis scheme (TNRAS), Tor nodes reliability analysis scheme, against the Sybil attack. We explore an effective mean to reveal the Sybil or unreliable nodes in Tor. through analyzing the general characteristics of nodes from six aspects, we can predict the unreliable nodes. We filter them and assess the remaining high reliable nodes for practical application afterwards. After that, the Tor reliable nodes analysis scheme application is implemented and analyzed. Moreover, this paper points out the definition of the Sybil nodes, high reliable nodes, and the reliability, then further assessing the nodes’ reliability. the research reveals the Sybil nodes characteristics through our six aspects detection method, and the predict model achieves to 0.928 training correlation and 0.715 validation correlation both with more than 0.8 ROC, which is of great significance for Tor with its increasing number of users and the worsening network context.

关键词： reliable nodes anonymous communication the Sybil attack Tor reliability

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Duet Benchmarking: Improving Measurement Accuracy in the Cloud 20

Duet Benchmarking: Improving Measurement Accuracy in the Clo...

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11th ACM/SPEC international conference on Performance Engineering (ICPE)

作者： Bulej, Lubomir Horky, Vojtech Tuma, Petr Farquet, Francois Prokopec, Aleksandar Charles Univ Prague Dept Distributed & Dependable Syst Prague Czech Republic Oracle Labs Zurich Switzerland

ISBN: (纸本)9781450369916

We investigate the duet measurement procedure, which helps improve the accuracy of performance comparison experiments conducted on shared machines by executing the measured artifacts in parallel and evaluating their relative performance together, rather than individually. Specifically, we analyze the behavior of the procedure in multiple cloud environments and use experimental evidence to answer multiple research questions concerning the assumption underlying the procedure. We demonstrate improvements in accuracy ranging from 2.3x to 12.5x (5.03x on average) for the tested ScalaBench (and DaCapo) workloads, and from 23.8x to 82.4x (37.4x on average) for the SPEC CPU 2017 workloads.

关键词： cloud computing software performance performance measurement performance testing

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Predicting the Mental State of the Social Network Users based on the Latent Dirichlet Allocation and fastText

Predicting the Mental State of the Social Network Users base...

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IEEE international Workshop on Intelligent Data Acquisition and Advanced computing Systems: Technology and Applications

作者： Igor Kotenko Yash Sharma Alexander Branitskiy St. Petersburg Federal Research Center of the Russian Academy of Sciences (SPC RAS) Saint-Petersburg Russia St. Petersburg Electrotechnical University (ETU LETI) Saint-Petersburg Russia

ISBN: (纸本)9781665426060

In modern society, social networks are popular Internet resources in which users create communities of common interests and exchange text and multimedia messages with each other. the content of these messages can be considered as a data source for predicting the sender's mental state. Such a task is important since the excessively frequent presence of depressive emotions in a person's behavior negatively affects his (her) psychological and physical state, and the timely detection and prevention of such manifestations helps to preserve his/her health. To solve this problem, this paper proposes an approach that calculates the emotion lexicon and classifies posts using the fastText classifier. We used the Latent Dirichlet Allocation (LDA) model to extract topics from the posts. the open dataset Pushshift Reddit Dataset was used to conduct experiments, as a result of which the high efficiency of the developed approach was shown. In particular, for the class none, the F1-score reached 96%.

关键词： Social networking (online) Soft sensors conferences Data acquisition Psychology Machine learning Depression

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Impact of Data Center Cooling Technology to Effectiveness of Turbo-Mode 11

Impact of Data Center Cooling Technology to Effectiveness of...

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11th international conference on Information and Communication Technology Convergence (ICTC) - Data, Network, and AI in the age of Untact (ICTC)

作者： Shin, Jaehyong Seo, Euiseong Sungkyunkwan Univ Dept Semicond & Display Engn Data Ctr Grp DIT CtrSamsung Elect Co Ltd Suwon South Korea Sungkyunkwan Univ Dept Comp Sci & Engn Suwon South Korea

ISBN: (纸本)9781728167589

the importance of cooling and energy efficiency is getting more and more important in data centers. the liquid cooling technology for CPUs is well known for its energy efficiency. In addition, it provides performance improvement by enriching the opportunity for turbo mode, which temporarily boost the clock frequency when the temperature and power consumption conditions stay below predefined thresholds. However, not all CPUs show improved performance when liquid cooling is applied. In this paper, we experimentally reveal that liquid cooling has different effects on performance improvement depending on the design of the cooling device and the thermal and power consumption characteristics of the processor. through a series of experiments, we reveal that, in this paper, the higher the TDP, the greater the performance improvement obtainable through liquid cooling. We also identify that distributed temperature sensing (DTS) margin is the main cause of performance improvement of turbo mode. Intel's 200Watt CPU, in particular, has improved performance by 4.7% due to liquid cooling.

关键词： Liquid cooling High performance computing Data Center Server Turbo mode

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Accelerating Message Propagation in Blockchain Networks 11

Accelerating Message Propagation in Blockchain Networks

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11th international conference on Information and Communication Technology Convergence (ICTC) - Data, Network, and AI in the age of Untact (ICTC)

作者： Santiago, Carlos Lee, Choonhwa Hanyang Univ Dept Comp Sci Seoul South Korea

ISBN: (纸本)9781728167589

Improving performance of blockchain systems is one of the principal research interests in the field. While many efforts are being made to produce faster and more efficient consensus protocols, they are all constrained by a common factor: the time it takes for a block to propagate through the network. Most blockchain networks use different variations of gossip-like communication protocols to be able to send large messages whilst minimizing latency and bandwidth use. Unfortunately, it still supposes a major bottleneck for state-of-the-art high-performance blockchain systems. In this paper we analyze the most relevant work being done to improve message propagation in blockchain networks. More specifically, we introduce the problem of neighbour selection for gossip protocols, and we propose an alternative method to pick neighbours based on weights derived from self-collected metrics. Our technical performance study shows that the proposed method can suppose an improvement of up to 5 seconds. Additionally, in combination with the use of erasure coding techniques, we are capable of achieving a 75% reduction of the overall block propagation time.

关键词： blockchain gossip distributed computing peer-to-peer

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