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International Workshop on Intelligent Systems and Applications

作者： Liu, Tao Li, Minghui Key Laboratory of Data Engineering and Knowledge Engineering MOE Beijing 100872 China School of Information Renmin University of China Beijing 100872 China School of Computer Science and Technology Harbin Institute of Technology Harbin 150001 China

ISBN: (纸本)9781424498574

Discovering the relationship between protein sequence pattern and protein secondary structure is important for accurately predicting secondary structure of protein sequence. A protein secondary structure pattern dictionary is constructed using protein sequence pattern and its corresponding secondary structure in this paper. Based on the constructed dictionary, we propose four effect factors on secondary structure of protein sequence pattern, including 1) the core pattern itself;2) patterns or amino acid residues that neighbor with the core pattern;3) patterns or amino acid residues that are far away from the core pattern;and 4) amino acid sequence segment that match the core pattern. Statistical measures are adopted to analyze these factors. The experimental result shows the reliability of these factors. The recognition of these effect factors presents new directions to predict protein secondary structure based on protein pattern dictionary. © 2011 IEEE.

关键词： Amino acids

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TinyQP: A query processing system in wireless sensor networks

TinyQP: A query processing system in wireless sensor network...

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14th International Conference on Web-Age Information Management, WAIM 2013

作者： Mo, Shangfeng Chen, Hong Zhang, Xiaoying Li, Cuiping Key Laboratory of Data Engineering and Knowledge Engineering of MOE Renmin University of China Beijing 100872 China School of Information Renmin University of China Beijing 100872 China Hunan University of Science and Technology Xiangtan 411201 China

ISBN: (纸本)9783642385612

Wireless Sensor Networks (WSNs) can be viewed as a new type of distributed databases. data management technology is one of the core technologies of WSNs. In this demo we show a Query Processing system based on TinyOS in WSNs, which is called TinyQP. TinyQP provides the in-network processing of several complex queries including real time query, historical query, event detection, aggregate query, top-k query, etc. TinyQP displays the network topology in a graphical way. TinyQP allows the user to remotely execute query commands and browse query result. © 2013 Springer-Verlag Berlin Heidelberg.

关键词： Query processing

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Energy-efficient approximate skyline computation in sensor networks

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Journal of Computational Information Systems 2007年第5期3卷 1821-1826页

作者： Xie, Tingting Lai, Yongxuan Chen, Hong School of Information Renmin University of China Beijing 100872 China Key Laboratory of Data Engineering and Knowledge Engineering China

The skyline query is frequently used to find a set of dominating data points (called skyline points) in a multidimensional dataset It is one of the most important query methods for database, datastream, P2P networks. However, it has not been implemented in sensor networks due to limited energy of the sensor nodes. This paper presents an energy-efficient approximate skyline query scheme for sensor networks. According to the experiments, this scheme can greatly improve the lifetime of sensor networks compared to the naive skyline query.

关键词： Wireless sensor networks

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A Multiple-Blockchains based Service Monitoring Framework in Edge-Cloud Computing 23

A Multiple-Blockchains based Service Monitoring Framework in...

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23rd IEEE International Conference on High Performance Computing and Communications, 7th IEEE International Conference on data Science and Systems, 19th IEEE International Conference on Smart City and 7th IEEE International Conference on Dependability in Sensor, Cloud and Big data Systems and Applications, HPCC-DSS-SmartCity-DependSys 2021

作者： Fu, Hang Wang, Puwei Li, Haoran Zhan, Ying Chen, Jinchuan Du, Xiaoyong Guizhou University of Finance and Economics Guiyang City550025 China School of Information Renmin University of China China Renmin University of China Key Laboratory of Data Engineering and Knowledge Engineering of Ministry of Education Beijing100872 China

ISBN: (纸本)9781665494571

In the edge-cloud computing, the applications usually are delivered as services, each of which runs independently and can cooperate to construct the complicated applications. However, it is difficult to monitor the services in the decentralized edge-cloud environment since there usually does not exist the central authorization to guarantee trustiness of the service quality data collected. To address the trust issue, the blockchain techniques have been introduced to the service monitoring. Considering the services usually are distributed on the edge nodes, if we deploy only a blockchain on the edge nodes near to the services, it may have to support both the service registration and monitoring because of the loose-coupling principle. That would influence the performance, even would crash the edge nodes. In this paper, we propose a multiple-blockchains based framework, including a registration blockchain that focuses on the service registration and discovery, and a set of monitoring blockchains that focus on the service invocation and monitoring. The registration blockchain is deployed on the cloud nodes, and the monitoring blockchains are deployed on the edge nodes near to the services for collecting efficiently and precisely the service quality data. Based on the cross-chain technology, we design a cross-chain service discovery between the monitoring blockchain and the registration blockchain for finding the services the requesters need. Finally, we implement the registration and monitoring blockchains based on the blockchain platform Cosmos and conduct a set of experiments to show the effectiveness of the proposed framework. © 2021 IEEE.

关键词： Authorization Cloud computing Smart cities Computer crashes Blockchains Monitoring

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Towards comprehensive integration management of business continuity, records and knowledge

Towards comprehensive integration management of business con...

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作者： An, Xiaomi Wang, Wang Key Laboratory of Data Engineering and Knowledge Engineering Ministry of Education Renmin University of China Beijing 100872 China School of Information Resource Management Renmin University of China Beijing 100872 China

ISBN: (纸本)9788988678251

Many of management systems for business continuity, records and knowledge (BRK) are standalone. Connections and networks of business continuity management systems (BCMS), records management systems (RMS) and knowledge management systems (KMS) are expected to study for facing challenges from evidence-based collaborations in a networked working environment, in terms of control of documented information for business efficiency;guarantee of evidentiality and quality of documented information for organizational effectiveness;and sharing, protecting and increasing values of records as business and knowledge assets for knowledge economy. Based on review of ideas of integration management thinking, best practice frameworks of business continuity management, records management and knowledge management, management models of BCMS, RMS and KMS, an architecture framework towards comprehensive integration management of BRK is proposed by vertical integration design and crosswise integration operations. Case studies demonstrate that such architecture framework has implications to enhance controls of efficiency, effectiveness, and economy of organizational resources and assets adaptable to complex global competition;to improve quality assurance of documented information for supporting evidence-based governance adaptable to dynamic changing of information and communication technologies;to consistent accumulation, sharing and exchanging evidence, memory and knowledge along e-business processes to promote collaboration, optimization and innovation of BCMS, RMS and KMS.

关键词： knowledge management

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Social Group Query Based on Multi-Fuzzy-Constrained Strong Simulation

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ACM Transactions on knowledge Discovery from data 2021年第3期16卷 1–27页

作者： Guliu Liu Lei Li Guanfeng Liu Xindong Wu Key Laboratory of Knowledge Engineering with Big Data (Hefei University of Technology) Ministry of Education and Hefei University of Technology Key Laboratory of Knowledge Engineering with Big Data (Hefei University of Technology) Ministry of Education Intelligent Interconnected Systems Laboratory of Anhui Province (Hefei University of Technology) and Hefei University of Technology Macquarie University NSW Australia Key Laboratory of Knowledge Engineering with Big Data (Hefei University of Technology) Ministry of Education and Mininglamp Academy of Sciences Mininglamp Technology

Traditional social group analysis mostly uses interaction models, event models, or other social network analysis methods to identify and distinguish groups. This type of method can divide social participants into different groups based on their geographic location, social relationships, and/or related events. However, in some applications, it is necessary to make more specific restrictions on the members and the interactions between members of the group. Generally, Graph Pattern Matching (GPM) technique is used to solve this problem. However, the existing GPM methods rarely consider the rich contextual information of nodes and edges to measure the credibility between members. In this article, first, a social group query problem that needs to consider the trust between members of the group is proposed. Then, to solve this problem, a multi-fuzzy-constrained strong simulation matching model is proposed based on multi-constrained simulation, and a Strong Simulation GPM algorithm (NTSS) based on the exploration of pattern Node Topological ordered sequence is proposed. Aiming at the inefficiency of the NTSS algorithm when pattern graph with multiple nodes with zero in-degree and the problem of repeated calculation of matching edges shared by multiple matching subgraphs, two optimization strategies are proposed. Finally, we conduct verification experiments on the effectiveness and efficiency of the NTSS algorithm and the algorithms with the optimization strategies on four social network datasets in real applications. Experimental results show that the NTSS algorithm is significantly better than the existing multi-constrained GPM algorithm, and the NTSS_Inv_EdgC algorithm, which combines two optimization strategies, greatly improves the efficiency of the NTSS algorithm.

关键词： Graph pattern matching contextual social network multi-fuzzy-constrained strong simulation social group query

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Marginal Value-Based Edge Resource Pricing and Allocation for Deadline-Sensitive Tasks 42

Marginal Value-Based Edge Resource Pricing and Allocation fo...

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42nd IEEE International Conference on Computer Communications, INFOCOM 2023

作者： Wang, Puwei Sun, Zhouxing Zhan, Ying Li, Haoran Du, Xiaoyong Renmin University of China School of Information China Renmin University of China Key Laboratory of Data Engineering and Knowledge Engineering of Ministry of Education Beijing100872 China Guizhou University of Finance and Economics Guiyang City550025 China

ISBN: (纸本)9798350334142

In edge computing (EC), resource allocation is to allocate computing, storage and networking resources on the edge nodes (ENs) efficiently and reasonably to tasks generated by users. Due to the resource-limitation of ENs, the tasks often need to compete for the resources. Pricing mechanisms are widely used to deal with the resource allocation problem, and the valuations of tasks play a critical role in the price mechanisms. However, users naturally are not willing to expose the valuations of their tasks due to conflicts of interests. Current research works usually adopt truthful auctions to motivate the users to report honestly the valuations of their tasks. In this paper, we introduce the marginal value to estimate the valuations of tasks, and propose a marginal value-based pricing mechanism using the incentive theory, which motivates the tasks with higher marginal values to actively request more resources. The EC platform sets the resource prices using the price mechanism, and then the users determine their resource requests relying on the resource prices and the valuations of their tasks. After receiving the deadline-sensitive tasks from the users, the resource allocation can be modeled as a knapsack problem with the deadline constraints. Extensive experimental results demonstrate that our approach is computationally efficient and is promising in enhancing the utility of the EC platform and the tasks. © 2023 IEEE.

关键词： Resource allocation

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Topology-based data compression in wireless sensor networks

Topology-based data compression in wireless sensor networks

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13th International Conference on Web-Age Information Management, WAIM 2012

作者： Mo, Shangfeng Chen, Hong Li, Yinglong Key Laboratory of Data Engineering and Knowledge Engineering of MOE Renmin University of China Beijing 100872 China School of Information Renmin University of China Beijing 100872 China Hunan University of Science and Technology Xiangtan 411201 China

ISBN: (纸本)9783642322808

In this paper, we address the problem of data Compression which is critical in wireless sensor networks. We proposed a novel Topology-based data Compression (TDC) algorithm for wireless sensor networks. We utilize the topological structure of routing tree to reduce the transmission of message packets. We analyzed the differences and relations between our algorithm and other compression algorithms. Extensive experiments are conducted to evaluate the performance of the proposed TDC approach by using two kinds of data sets: real data set and synthetic data set. The results show that the TDC algorithm substantially outperforms Non-compression algorithm in terms of packets transmitted. © 2012 Springer-Verlag.

关键词： Topology

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P-TECS: An Energy Balance Algorithm for Opportunistic Networks Integrating Multiple Node Attributes 5th

P-TECS: An Energy Balance Algorithm for Opportunistic Netwo...

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5th International Conference on Security and Privacy in New Computing Environments, SPNCE 2022

作者： Xu, Gang Yang, Xiaoying Chen, Jingjian Huang, Baoqi College of Computer Science Inner Mongolia University Hohhot010021 China Inner Mongolia A.R. Key Laboratory of Data Mining and Knowledge Engineering Inner Mongolia University Hohhot010021 China

ISBN: (纸本)9783031306228

This paper proposes an energy balance opportunistic networks routing algorithm P-TECS. The P-TECS solves the problems of energy consumption of key nodes in existing opportunistic routing algorithms. This paper defines the relay degree of communication between nodes, and designs a P-TECS opportunistic routing algorithm integrating dynamic attributes of multiple nodes. Simulation results show that in resource-constrained opportunistic networks, P-TECS significantly improves the message delivery rate and average remaining energy of nodes, and significantly reduces the routing overhead rate. © 2023, ICST Institute for Computer Sciences, Social Informatics and Telecommunications engineering.

关键词： Routing algorithms

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Managing a Large Shared Bank of Unstructured data by Using Free-Table

Managing a Large Shared Bank of Unstructured Data by Using F...

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International Asia-Pacific Web Conference (APWEB)

作者： Xiao Zhang Xiaoyong Du Jinchuan Chen Shan Wang Key Laboratory of Data Engineering and Knowledge Engineering MOE Renmin University of China Beijing China

This paper presents a reference framework, called BUD, to manage a large shared bank of unstructured data. This paper lists several important issues on managing or maintaining the unstructured data in BUD. BUD stores and manages the ever-growing unstructured data by introducing a novel technique called free-table, which is a conceptual view for end-users and a physical entity maintained by transactional storage manager of BUD. Free-table is cell-oriented but not column-oriented as relational table. It can store various types of unstructured data in cell with different versions. Additionally, we study two cases, VMP and PXRDB, to show that our proposal is feasible and tractable.

关键词： data models Conference management knowledge management engineering management data engineering Proposals Maintenance engineering knowledge engineering data mining Relational databases

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