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Reliable web services selection based on finite state machine model

Information Technology Journal 2011年第9期10卷 1662-1672页

作者： Shen, Hongjie Ding, Zhijun Chen, Hongzhong Key Laboratory of Embedded System and Service Computing Tongji University Ministry of Education Shanghai 200092 China

Dynamically selecting suitable Web services (WSs) is crucial to users in Web services Composition (WSC). Generally, most works regard a Web service (WS) as the basic unit and compose the composite WS (CWS) end to end. However, a WS may comprise multiple operations that are invoked in sequence and the selection of WSs according to the model still is a NP problem. In this study, the WSs consist of some operations and then WSs selection problem is formalized as a Finite State Machine (FSM) process. This study proposed an algorithm to create the WSC Tree (WSCT), in which each path from root to leaf node is a feasible WSC execution path. Then, a heuristic algorithm is proposed to realize the selection of WSs based on the WSCT. The advantage of heuristic algorithm is that it can address the selection problem without traversing the whole WSCT but it still spends much time in the construction of the WSCT. So, in order to further decrease the time of selection, a backtracking algorithm is presented to select a feasible execution path without generating WSCT. At last, experiments show that heuristic algorithm is more effective than exhaustive method and the backtracking algorithm spend the less time than heuristic algorithm, the reliability of WSC execution path selected by backtracking algorithm can satisfy the requirement of users. So, this study proposed an algorithm to select a feasible WSC execution path within a reasonable time. © 2011 Asian Network for Scientific Information.

关键词： Web services

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Using estimation of distribution algorithm to coordinate decentralized learning automata for meta-task scheduling

Using estimation of distribution algorithm to coordinate dec...

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Congress on Evolutionary Computation

作者： Jie Li Junqi Zhang Key Laboratory of Embedded System and Service Computing Ministry of Education Tongji University Shanghai China Key Laboratory of Embedded System and Service Computing Ministry of Education Tongji University Shanghai Shanghai CN

Learning automaton (LA) is a reinforcement learning model that aims to determine the optimal action out of a set of actions. It is characterized by updating a selection probability vector through a sequence of repetitive feedback cycles interacting with an environment. Decentralized learning automata (DLAs) consists of many learning automata (LAs) that learn at the same time. Each LA independently selects an action based on its own selection probability vector. In order to provide an appropriate central coordination mechanism in DLAs, this paper proposes a novel decentralized coordination learning automaton (DCLA) using a new selection probability vector which is combined with the probability vectors derived from both LA and estimation of distribution algorithm (EDA). LA contributes to the own learning experience of each LA while EDA estimates the distribution of the whole swarm's promising individuals. Thus, decentralized LAs can be coordinated by EDA using the swarm's comprehensive knowledge. The proposed automaton is applied to solve the real problem of meta-task scheduling in heterogeneous computing system. Extensive experiments demonstrate a superiority of DCLA over other counterpart algorithms. The results show that the proposed DCLA provides an effective and efficient way to coordinate LAs for solving complicated problems.

关键词： Vectors Learning automata Sociology Statistics Processor scheduling Scheduling Estimation

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The behavioral sign of account theft: Realizing online payment fraud alert 29

The behavioral sign of account theft: Realizing online payme...

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29th International Joint Conference on Artificial Intelligence, IJCAI 2020

作者： Wang, Cheng Department of Computer Science Tongji University Shanghai China Key Laboratory of Embedded System and Service Computing Ministry of Education Shanghai China Shanghai Institute of Intelligent Science and Technology Tongji University China

ISBN: (纸本)9780999241165

As a matter of fact, it is usually taken for granted that the occurrence of unauthorized behaviors is necessary for the fraud detection in online payment services. However, we seek to break this stereotype in this work. We strive to design an ex-ante anti-fraud method that can work before unauthorized behaviors occur. The feasibility of our solution is supported by the cooperation of a characteristic and a finding in online payment fraud scenarios: The well-recognized characteristic is that online payment frauds are mostly caused by account compromise. Our finding is that account theft is indeed predictable based on users' high-risk behaviors, without relying on the behaviors of thieves. Accordingly, we propose an account risk prediction scheme to realize the ex-ante fraud detection. It takes in an account's historical transaction sequence, and outputs its risk score. The risk score is then used as an early evidence of whether a new transaction is fraudulent or not, before the occurrence of the new transaction. We examine our method on a real-world B2C transaction dataset from a commercial bank. Experimental results show that the ex-ante detection method can prevent more than 80% of the fraudulent transactions before they actually occur. When the proposed method is combined with an interim detection to form a real-time anti-fraud system, it can detect more than 94% of fraudulent transactions while maintaining a very low false alarm rate (less than 0.1%). © 2020 Inst. Sci. inf., Univ. Defence in Belgrade. All rights reserved.

关键词： Crime

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A Better Cardinality Estimator with Fewer Bits, Constant Update Time, and Mergeability 42

A Better Cardinality Estimator with Fewer Bits, Constant Upd...

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42nd IEEE International Conference on Computer Communications, INFOCOM 2023

作者： Du, Yang Huang, He Sun, Yu-E Li, Kejian Zhang, Boyu Gao, Guoju Soochow University School of Computer Science and Technology Suzhou China Soochow University School of Rail Transportation Suzhou China Ministry of Education Key Laboratory of Embedded System and Service Computing Shanghai China

ISBN: (纸本)9798350334142

Cardinality estimation is a fundamental problem with diverse practical applications. HyperLogLog (HLL) has become a standard in practice because it offers good memory efficiency, constant update time, and mergeability. Some recent work achieved better memory efficiency, but typically at the cost of impractical update time or losing mergeability, making them incompatible with applications like network-wide traffic measurement. This work presents SpikeSketch, a better cardinality estimator that reduces memory usage of HLL by 37% without sacrificing other crucial metrics. We adopt a bucket-based data structure to promise constant update time, design a smoothed log4 ranking and a spike coding scheme to compress cardinality observables into buckets, and propose a lightweight mergeable lossy compression to balance memory usage, information loss, and mergeability. Then we derive an unbiased estimator for recovering cardinality from the lossy-compressed sketch. Theoretical and empirical results show that SpikeSketch can work as a drop-in replacement for HLL because it achieves a near-optimal MVP (memory-variance-product) of 4.08 (37% smaller than HLL) with constant update time and mergeability. Its memory efficiency even defeats ACPC and HLLL, the state-of-the-art lossless-compressed sketches using linear-time compression to reduce memory usage. © 2023 IEEE.

关键词： Efficiency

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Meta-Heuristic Based Multipath Joint Routing and Scheduling of Time-Triggered Traffic for Time-Sensitive Networking in IIoT 2

Meta-Heuristic Based Multipath Joint Routing and Scheduling ...

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2nd International Conference on Green Communication, Network, and Internet of Things, CNIoT 2022

作者： Chen, Chen Li, Zhong The College of Information Science and Technology Donghua University Shanghai201620 China The Key Laboratory of the Ministry of Education for Embedded System and Service Computing Department of Computer Science Tongji University Shanghai201804 China

ISBN: (纸本)9781510662940

Time-Sensitive networking (TSN) meets the needs of industrial internet of things (IIoT). It solves the challenges of deterministic transmission and reliable communication of time sensitive data streams. Traffic scheduling is the core mechanism of time-sensitive networks. Many excellent researches have explored and optimized the method of scheduling time-triggered streams in TSN. However, the existing time-triggered streams scheduling in TSN mostly separates routing and scheduling, which limits the scalability of scheduling. Many researches are based on fixed routing to schedule streams. Due to the interaction between scheduling and routing, the quality of fixed route solution is inferior to that of joint routing and scheduling. In this paper, we propose a meta-heuristic based multipath joint routing and scheduling method for time-triggered traffic in TSN, named MMRS. We set path selection as a variable and consider multipath routing for fault tolerance. At the same time, we establish the integer linear programming formulation and use meta-heuristic to obtain high-quality solutions. The evaluations show that compared with other excellent routing and scheduling methods, the runtime of 60 streams of MMRS method is reduced by 65.6%, and the schedulability is improved by 21% on average. The experiments verify that our proposed scheduling method can obtain high-quality solutions in an acceptable solution time. © 2023 SPIE.

关键词： Internet of things

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DSP Assembler Auto-Generation Technique and ToolChain Integration 21

DSP Assembler Auto-Generation Technique and ToolChain Integr...

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21st IEEE International Conference on Communication Technology, ICCT 2021

作者： Wang, Wanli Wu, Jun Ren, Haoqi Zhang, Zhifeng Tongji University Electronics and Information Engineering College Key Laboratory of Embedded System and Service Computing Ministry of Education Shanghai201804 China Fudan University School of Computer Science Shanghai200438 China

ISBN: (纸本)9781665432061

To promote the application of DSP, a fast and accurate toolchain generation method must be realized. Unlike the traditional manual method, in this paper, we propose a toolchain generation algorithm based on the architecture description language, and migrate the toolchain to adapt to the specified processor architecture. The algorithm uses the DSP architecture description as input to generate intermediate expressions, then uses lexical analysis and syntax analysis tools to migrate the assembly toolchain. In addition, an integrated development environment is developed based on Eclipse, which creates a friendly human-computer interface. Experiments show that this toolchain generation algorithm runs fast and accurately, which solves problems of the development and application of the DSP toolchain, and creates favorable conditions for the promotion of DSP. © 2021 IEEE.

关键词： Syntactics

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BMSAD: Behavior Feature and Multi-Scenario -Based Sybil Attack Detection Method in Vehicular Networks 3

BMSAD: Behavior Feature and Multi-Scenario -Based Sybil Atta...

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3rd International Seminar on Artificial Intelligence, Networking, and Information Technology, AINIT 2022

作者： Luo, Jie Li, Zhong College of Information Science and Technology Donghua University Shanghai201620 China Key Laboratory of the Ministry of Education for Embedded System and Service Computing Department of Computer Science Tongji University Shanghai201804 China

ISBN: (数字)9781510662971

ISBN: (纸本)9781510662964

Vehicular networks improve traffic safety and efficiency by wireless communications among vehicles and infrastructures. However, security has always been a challenge to vehicular networks, which may cause severe harm to the intelligent transportation systems. Sybil attack is considered as a serious security threat to vehicular networks since the attacker can disseminate false messages with multiple forged identities. In this paper, we designed a behavior feature and multi-scenario-based Sybil attack detection method, named BMSAD in vehicular networks. In BMSAD, we propose solutions for two scenarios: normal traffic and traffic congestion. A node is allowed to verify the authenticity of another node by estimating their geographic distance based on received signal strength, and compare them to its claimed localizations. Then we design long- and short-term pattern to analyze the similarity of vehicles' behavior features and trajectory for Sybil nodes detection, which act as the second line of defense in normal traffic scenario. At last, the Sybil nodes of the traffic congestion scenario are detected by logical inference based on kinematics theory. And experiment results demonstrate that the proposed scheme achieves high detection rate and low false positive rate. © 2023 SPIE.

关键词： Traffic congestion

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l-SkyDiv query:Effectively improve the usefulness of skylines

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Science China(Information Sciences) 2010年第9期53卷 1785-1799页

作者： HUANG ZhenHua1,2*,XIANG Yang1 & LIN ZiYu3 1Department of Computer Science and Technology,Tongji University,Shanghai 201804,China 2The key laboratory of embedded system and service computing,ministry of education,Tongji University,Shanghai 200092,China 3Department of Computer Science and Technology,Peking University,Beijing 100871,China 1. Department of Computer Science and Technology Tongji University Shanghai 201804 China2. The Key Laboratory of Embedded System and Service Computing Ministry of Education Tongji University Shanghai 200092 China3. Department of Computer Science and Technology Peking University Beijing 100871 China

Skyline query processing has recently received a lot of attention in database *** a set of multi-dimensional objects,the skyline query finds the objects that are not dominated by *** the best of our knowledge,the existing researches mainly focus on how to efficiently return the whole skyline ***,as the cardinality and dimensionality of input dataset increase,the number of skylines grows exponentially,and hence this "huge" skyline set is completely useless to *** by the above fact,in this paper,we present a novel type of l-SkyDiv query,which only returns l skylines having maximum diversity,to improve the usefulness of skyline ***,we prove that the l-SkyDiv query belongs to the NP-Hard problem theoretically,and propose three efficient heuristic algorithms whose time complexities are polynomial to fast implement the proposed ***,we present detailed theoretical analyses and extensive experiments,demonstrating that our algorithms are both efficient and effective.

关键词： skyline query diversity heuristic algorithm query optimization performance evaluation

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Mining World Indicators for Analyzing and Modeling the Development of Countries

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ACM/IMS Transactions on Data Science 2021年第4期2卷 1–27页

作者： Huang, Hong Chi, Mingyuan Song, Yu Jin, Hai The National Engineering Research Center for Big Data Technology and System Key Laboratory of Service Computing Technology and System Ministry of Education School of Computer Science and Technology Huazhong University of Science and Technology Wuhan430074 China

The world indicators released by the World Bank or other organizations usually give the basic public knowledge about the world. However, separate and static index lacks the complex interplay among different indicators and thus cannot help us have an overall understanding of the world. To this end, we study the world indicators from a different angle. Firstly, we discover that there exist correlations between indicators either from a static view or from a dynamic view. Moreover, taking the trade and diplomatic relationships into consideration, we construct a multi-relational network to depict the interactions between different countries, and propose a Multiple Relations to Vector (MR2vec) model to study world indicators from a network perspective. The experimental results show the changes of world indicators are predictable with the proposed model, and our proposed MR2vec has wide adaptability in predicting multi-relation networks. © 2022 Copyright held by the owner/author(s).

关键词： Data mining

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Web service composition techniques in a health care service platform

Web service composition techniques in a health care service ...

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2011 IEEE 9th International Conference on Web services, ICWS 2011

作者： Wang, Pengwei Ding, Zhijun Jiang, Changjun Zhou, Mengchu Key Laboratory of Embedded System and Service Computing Ministry of Education Tongji University Shanghai 200092 China Department of Electrical and Computer Engineering New Jersey Institute of Technology Newark NJ 07102 United States

ISBN: (纸本)9780769544632

The information technology has been recognized as one of the most important means to improve health care and curb its ever-increasing cost. However, existing efforts mainly focus on informatization of hospitals or medical institutions within organizations, and few are directly oriented to individuals. The strong demand for various health services from customers calls for the creation of powerful individual-oriented personalized health care service systems. Web service composition (WSC) and related technologies can greatly help one build such systems. This paper aims to present a newly developed platform called a Public-oriented Health care Information service Platform (PHISP) and several novel WSC techniques that are used to build it. Among them include WSC techniques that can well support branch and parallel structures. © 2011 IEEE.

关键词： Web services

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