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Resource investment for DDoS attack resistant SDN: a practical assessment

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Science China(Information Sciences) 2023年第7期66卷 112-129页

作者： Bin YUAN Fan ZHANG Jun WAN Huan ZHAO Shui YU Deqing ZOU Qiangsheng HUA Hai JIN School of Cyber Science and Engineering Huazhong University of Science and Technology National Engineering Research Center for Big Data technology and system services computing technology and system lab Hubei Engineering Research Center on Big Data Security Shenzhen Huazhong University of Science and technology Research Institute School of Computer Science and technology Huazhong University of Science and Technology cluster and grid computing lab School of Computer Science University of Technology Sydney

Software-defined networks(SDNs) present a novel network architecture that is widely used in various datacenters. However, SDNs also suffer from many types of security threats, among which a distributed denial of service(DDoS) attack, which aims to drain the resources of SDN switches and controllers,is one of the most common. Once the switch or controller is damaged, the network services can be *** defense schemes against DDoS attacks have been proposed from the perspective of attack detection;however, such defense schemes are known to suffer from a time consuming and unpromising accuracy, which could result in an unavailable network service before specific countermeasures are taken. To address this issue through a systematic investigation, we propose an elaborate resource-management mechanism against DDoS attacks in an SDN. Specifically, by considering the SDN topology, we leverage the M/M/c queuing model to measure the resistance of an SDN to DDoS attacks. Network administrators can therefore invest a reasonable number of resources into SDN switches and SDN controllers to defend against DDoS attacks while guaranteeing the quality of service(QoS). Comprehensive analyses and empirical data-based experiments demonstrate the effectiveness of the proposed approach.

关键词： SDN security DDoS attacks resource management queueing theory QoS

An Optimistic Checkpoint Mechanism Based on Job Characteristics and Resource Availability for Dynamic grids

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Wuhan University Journal of Natural Sciences 2011年第3期16卷 213-222页

作者： TAO Yongcai JIN Hai WU Song School of Information Engineering Zhengzhou University Zhengzhou 450000 Henan China services computing technology and system lab Cluster and Grid Computing Lab Huazhong University of Science and Technology Wuhan 430074 Hubei China

In the paper, based on the job characteristics and resources availability, an optimistic checkpoint mechanism for dynamic grids（OCM4G） is proposed. It can determine whether to checkpoint a given job running on a given resource node and establish optimal aperiodic checkpoint intervals by applying the knowledge of job characteristics and resource availability. We evaluate OCM4G over a real grid environment （Chitlagrid） and the results show that OCM4G achieves better performance than the periodic checkpoint and the analytical method of calculating aperiodic checkpoint intervals.

关键词： grid computing fault tolerance checkpoint Markov

Improving Entity Linking in Chinese Domain by Sense Embedding Based on Graph clustering

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Journal of Computer Science & technology 2023年第1期38卷 196-210页

作者：张照博钟芷漫袁平鹏金海 National Engineering Research Center for Big Data technology and system Huazhong University of Science and Technology Wuhan 430074China service computing technology and system laboratory Huazhong University of Science and Technology Wuhan 430074China cluster and grid computing laboratory Huazhong University of Science and TechnologyWuhan 430074China School of Computer Science and technology Huazhong University of Science and TechnologyWuhan 430074China

Entity linking refers to linking a string in a text to corresponding entities in a knowledge base through candidate entity generation and candidate entity *** is of great significance to some NLP(natural language processing)tasks,such as question *** English entity linking,Chinese entity linking requires more consideration due to the lack of spacing and capitalization in text sequences and the ambiguity of characters and words,which is more evident in certain *** Chinese domains,such as industry,the generated candidate entities are usually composed of long strings and are heavily *** addition,the meanings of the words that make up industrial entities are sometimes *** semantic space is a subspace of the general word embedding space,and thus each entity word needs to get its exact ***,we propose two schemes to achieve better Chinese entity ***,we implement an ngram based candidate entity generation method to increase the recall rate and reduce the nesting ***,we enhance the corresponding candidate entity ranking mechanism by introducing sense *** the contradiction between the ambiguity of word vectors and the single sense of the industrial domain,we design a sense embedding model based on graph clustering,which adopts an unsupervised approach for word sense induction and learns sense representation in conjunction with *** test the embedding quality of our approach on classical datasets and demonstrate its disambiguation ability in general *** confirm that our method can better learn candidate entities’fundamental laws in the industrial domain and achieve better performance on entity linking through experiments.

关键词： natural language processing(NLP) domain entity linking computational linguistics word sense disambiguation knowledge graph

Toward High-Performance Delta-Based Iterative Processing with a Group-Based Approach

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Journal of Computer Science & technology 2022年第4期37卷 797-813页

作者： Hui Yu Xin-Yu Jiang Jin Zhao Hao Qi Yu Zhang Xiao-Fei Liao Hai-Kun Liu Fu-Bing Mao Hai Jin National Engineering Research Center for Big Data technology and system Huazhong University of Science and TechnologyWuhan 430074China service computing technology and system laboratory Huazhong University of Science and TechnologyWuhan 430074China cluster and grid computing laboratory Huazhong University of Science and TechnologyWuhan 430074China School of Computer Science and technology Huazhong University of Science and TechnologyWuhan 430074China

Many systems have been built to employ the delta-based iterative execution model to support iterative algorithms on distributed platforms by exploiting the sparse computational dependencies between data items of these iterative algorithms in a synchronous or asynchronous approach. However, for large-scale iterative algorithms, existing synchronous solutions suffer from slow convergence speed and load imbalance, because of the strict barrier between iterations;while existing asynchronous approaches induce excessive redundant communication and computation cost as a result of being barrier-free. In view of the performance trade-off between these two approaches, this paper designs an efficient execution manager, called Aiter-R, which can be integrated into existing delta-based iterative processing systems to efficiently support the execution of delta-based iterative algorithms, by using our proposed group-based iterative execution approach. It can efficiently and correctly explore the middle ground of the two extremes. A heuristic scheduling algorithm is further proposed to allow an iterative algorithm to adaptively choose its trade-off point so as to achieve the maximum efficiency. Experimental results show that Aiter-R strikes a good balance between the synchronous and asynchronous policies and outperforms state-of-the-art solutions. It reduces the execution time by up to 54.1% and 84.6% in comparison with existing asynchronous and the synchronous models, respectively.

关键词： iterative algorithm delta-based execution model efficiency

Discovering Cohesive Temporal Subgraphs with Temporal Density Aware Exploration

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Journal of Computer Science & technology 2022年第5期37卷 1068-1085页

作者： Chun-Xue Zhu Long-Long Lin Ping-Peng Yuan Hai Jin National Engineering Research Center for Big Data technology and system Huazhong University of Science and TechnologyWuhan 430074China service computing technology and system laboratory Huazhong University of Science and TechnologyWuhan 430074China cluster and grid computing laboratory Huazhong University of Science and TechnologyWuhan 430074China School of Computer Science and technology Huazhong University of Science and TechnologyWuhan 430074China

Real-world networks,such as social networks,cryptocurrency networks,and e-commerce networks,always have occurrence time of interactions between *** networks are typically modeled as temporal *** cohesive subgraphs from temporal graphs is practical and essential in numerous data mining applications,since mining cohesive subgraphs gets insights into the time-varying nature of temporal ***,existing studies on mining cohesive subgraphs,such as Densest-Exact and k-truss,are mainly tailored for static graphs(whose edges have no temporal information).Therefore,those cohesive subgraph models cannot indicate both the temporal and the structural characteristics of *** this end,we explore the model of cohesive temporal subgraphs by incorporating both the evolving and the structural characteristics of temporal ***,the volume of time intervals in a temporal network is *** a result,the time complexity of mining temporal cohesive subgraphs is *** efficiently address the problem,we first mine the temporal density distribution of temporal *** by the distribution,we can safely prune many unqualified time intervals with the linear time ***,the remaining time intervals where cohesive temporal subgraphs fall in are examined using the greedy *** results of the experiments on nine real-world temporal graphs indicate that our model outperforms state-of-the-art solutions in efficiency and ***,our model only takes less than two minutes on a million-vertex DBLP and has the highest overall average ranking in EDB and TC metrics.

关键词： temporal network temporal feature distribution cohesive subgraph convex property

China in the eyes of news media:a case study under COVID-19 epidemic

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Frontiers of Information technology & Electronic Engineering 2021年第11期22卷 1443-1457页

作者： Hong HUANG Zhexue CHEN Xuanhua SHI Chenxu WANG Zepeng HE Hai JIN Mingxin ZHANG Zongya LI National Engineering Research Center for Big Data technology and system Huazhong University of Science and TechnologyWuhan430074China services computing technology and system lab Huazhong University of Science and TechnologyWuhan430074China cluster and grid computing lab Huazhong University of Science and TechnologyWuhan430074China School of Computer Science and technology Huazhong University of Science and TechnologyWuhan430074China School of Journalism and Information Communication Huazhong University of Science and TechnologyWuhan430074China

As one of the early COVID-19 epidemic outbreak areas,China attracted the global news media’s attention at the beginning of *** the epidemic period,Chinese people united and actively fought against the ***,in the eyes of the international public,the situation reported about China is not *** better understand how the international public portrays China,especially during the epidemic,we present a case study with big data *** aim to answer three questions:(1)What has the international media focused on during the COVID-19 epidemic period?(2)What is the media’s tone when they report China?(3)What is the media’s attitude when talking about China?In detail,we crawled more than 280000 pieces of news from 57 mainstream media agencies in 22 countries and made some interesting *** example,international media paid more attention to Chinese livelihood during the COVID-19 epidemic *** March and April,“progress of Chinese vaccines,”“specific drugs and treatments,”and“virus outbreak in U.S.”became the media’s most common *** terms of news attitude,Cuba,Malaysia,and Venezuela had a positive attitude toward China,while France,Canada,and the United Kingdom had a negative *** study can help understand China’s image in the eyes of the international media and provide a sound basis for image analysis.

关键词： Country image COVID-19 epidemic Topic mining Entity Tone of news Emotion

On the Security of Smart Home systems:A Survey

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Journal of Computer Science & technology 2023年第2期38卷 228-247页

作者：袁斌万俊吴宇晗邹德清金海 School of Cyber Science and Engineering Huazhong University of Science and TechnologyWuhan 430074China Hubei Key laboratory of Distributed system Security Huazhong University of Science and Technology Wuhan 430074China Hubei Engineering Research Center on Big Data Security Huazhong University of Science and Technology Wuhan 430074China National Engineering Research Center for Big Data technology and system Huazhong University of Science and TechnologyWuhan 430074China services computing technology and system lab Huazhong University of Science and TechnologyWuhan 430074China Shenzhen Huazhong University of Science and technology Research Institute Shenzhen 518057China School of Computer Science and technology Huazhong University of Science and TechnologyWuhan 430074China cluster and grid computing lab Huazhong University of Science and TechnologyWuhan 430074China

Among the plethora of IoT(Internet of Things)applications,the smart home is one of the ***,the rapid development of the smart home has also made smart home systems a target for ***,researchers have made many efforts to investigate and enhance the security of smart home *** a more secure smart home ecosystem,we present a detailed literature review on the security of smart home ***,we categorize smart home systems’security issues into the platform,device,and communication *** exploring the research and specific issues in each of these security areas,we summarize the root causes of the security flaws in today's smart home systems,which include the heterogeneity of internal components of the systems,vendors'customization,the lack of clear responsibility boundaries and the absence of standard security ***,to better understand the security of smart home systems and potentially provide better protection for smart home systems,we propose research directions,including automated vulnerability mining,vigorous security checking,and data-driven security analysis.

关键词： IoT(Internet of Things) smart home IoT security smart home security

Resources Allocation in Virtualized systems Based on Try-before-buy Approach

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Resources Allocation in Virtualized Systems Based on Try-bef...

Coach-assistedmulti-agent reinforcement learning framework for unexpected crashed agents

2011 2ND International Conference on Innovative computing and Communication and 2011 Asia-Pacific Conference on Information technology and Ocean Engineering(CICC-ITOE 2011)

作者： Ritai Yu Congfeng Jiang Xianghua Xu Hui Cheng Jian Wan grid and service computing technology lab Hangzhou Dianzi University

In virtualization environments, resources are shared across multiple virtual machines（VMs）, which results in contentions and even conflicting under heavily loaded or consolidated situations. In order to accommodate as many as service instances while still delivering performance guarantees, resource allocation should be optimized in a just adequate manner such that less resources will be utilized for a specific performance requirement. To achieve this goal, in this paper we propose a try-before-buy approach for allocating contending resources. This approach firstly does a try of minor resource allocation to find the performance feedback and search for the optimal amount of resource that should be allocated to the target virtual machine. This approach does not require a highly accurate performance model in a virtualized system where workloads usually change frequently with time in some intervals. Experiments on a Xen based virtualized environment are conducted and evaluated for its effectiveness. The results show that the proposed approach utilizes less CPU and memory resources to achieve the same performance goals compared to default Xen configuration with over-provisioning..

关键词： virtualization provisioning resource allocation performance feedback

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Frontiers of Information technology & Electronic Engineering 2022年第7期23卷 1032-1042页

作者： Jian ZHAO Youpeng ZHAO Weixun WANG Mingyu YANG Xunhan HU Wengang ZHOU Jianye HAO Houqiang LI School of Information Science and technology University of Science and Technology of ChinaHefei 230026China College of Intelligence and computing Tianjin UniversityTianjin 300072China

Multi-agent reinforcement learning is difficult to apply in practice,partially because of the gap between simulated and real-world *** reason for the gap is that simulated systems always assume that agents can work normally all the time,while in practice,one or more agents may unexpectedly“crash”during the coordination process due to inevitable hardware or software *** crashes destroy the cooperation among agents and lead to performance *** this work,we present a formal conceptualization of a cooperative multi-agent reinforcement learning system with unexpected *** enhance the robustness of the system to crashes,we propose a coach-assisted multi-agent reinforcement learning framework that introduces a virtual coach agent to adjust the crash rate during *** have designed three coaching strategies(fixed crash rate,curriculum learning,and adaptive crash rate)and a re-sampling strategy for our coach *** our knowledge,this work is the first to study unexpected crashes in a multi-agent *** experiments on grid-world and StarCraft II micromanagement tasks demonstrate the efficacy of the adaptive strategy compared with the fixed crash rate strategy and curriculum learning *** ablation study further illustrates the effectiveness of our re-sampling strategy.

关键词： Multi-agent system Reinforcement learning Unexpected crashed agents