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11th International Conference on Intelligent Control and Information Processing, ICICIP 2021

作者： Zhu, Xinhui Zhang, Li Shi, Yang Wang, Jing Li, Jian Xinyang Normal University School of Computer and Information Technology Xinyang464000 China Henan Key Lab. of Analysis and Application of Education Big Data Xinyang Normal University Xinyang464000 China Yangzhou University School of Information Engineering Yangzhou225127 China

ISBN: (纸本)9781665425155

Robot manipulator control is a complicated multi-tasking problem in reality. It includes not only basic tracking task, but also additional tasks, such as conquering joint angle limits, posture control. However, most existing works only consider the goal of tracking and formulate it as single-layered time-variant problems, which leads to impracticality. In this work, robot manipulator control problem is formulated as four-layered time-variant equations including linear, nonlinear equalities and inequalities. Each layer formulates one subtask: The first layer of nonlinear equality describes basic tracking task based on forward kinematics;The second layer and third layer are inequalities, which describe joint angle upper and lower limits;The last layer is a linear equality with respect to joint angle velocity, which could be designed by user to describe other task, such as posture control. To solve this complicated four-layered time-variant problem, it is converted as single-layered equation based on the zeroing neural dynamics method. Then, continuous-time solution is proposed. Furthermore, discrete-time algorithm is proposed based on a third-order time-discretization formula and continuous-time solution. Numerical experiments illustrate the effectiveness and superiority compared to existing work. © 2021 IEEE.

关键词： Industrial robots

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Unavailable time aware scheduling of hybrid task on heterogeneous distributed system

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IAENG International Journal of Applied Mathematics 2020年第1期50卷 133-146页

作者： Xuan, Hejun Wei, Shiwei Zhao, Xuelin Zhou, Yang Ma, Xingpo Liu, Daohua Li, Yanling School of Computer and Information Technology Xinyang Normal University Henan Xinyang China School of Computer and Technology Guilin University of Aerospace Technology Guilin541000 China Henan Key Lab. of Analysis and Application of Education Big Data Xinyang Normal University Henan Xinyang464000 China

The resource allocation for tasks in heterogeneous distributed system is a well known NP-hard problem. For the sake of making the makespan is minimized, it is hard to distribute the tasks to proper processors. The problem is even more complex and challenging when the processors have unavailable time and the tasks type are various. This paper investigates a resource allocation problem for hybrid tasks comprising both divisible and bag-of-tasks(BoT) in heterogeneous distributed system when the processors has unavailable time. First, the mathematical model, which minimizes the makespan of the hybrid tasks when the processors have unavailable time, is established. Second, we propose a scheduling algorithm referred to as bag-of-tasks allocate-pull and divisible task allocation (BoTAPDTA) algorithm for handling hybrid tasks on heterogeneous distributed systems. In addition, to solving the optimization model efficiently, a generic algorithm(GA) is proposed. For the sake of reducing the search space and solving the optimization model effectively, a two step scheduling algorithm(TSGA), which first allocate bag-of-tasks(BoT) using generic algorithm and then assign divisible task to processors like BoTAPDTA, is designed. Finally, numerical simulation experiments are conducted, and experimental results indicate the effectiveness of the proposed model and algorithm. © 2020.

关键词： Scheduling algorithms

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VNF Service Chain Deployment Algorithm in 5G Communication based on Reinforcement Learning

IAENG International Journal of Computer Science

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IAENG International Journal of Computer Science 2021年第1期48卷 1页

作者： Xuan, Hejun Zhao, Xuelin Fan, Jianwei Xue, Yahui Zhu, Fangfang Li, Yanling School of Computer Science and Technology Xinyang Normal University Xinyang464000 China Henan Key Lab. of Analysis and Application of Education Big Data Xinyang Normal University XinyangHenan464000 China

With the rapidly deployment of 5G communication, network functional virtualization has became one of key technology. However, how to achieve virtual network function service chaining (VNF-SC) adaptively and cost-effectively in an inter datacenter elastic optical network (interDC-EON) has become an interesting and challenging problem. In addition, network function virtualization has became one of the key technology for 5G Commons. In this paper, we propose a resource scheduling framework based on artificial intelligence. In addition, an effective VNF-SC deployment algorithm based on deep reinforcement learning (RL) is designed. In this algorithm, VNF-SC deployed scheme is obtained by using deep Q-learning according to the state of the network and thereward of the action. To verify the efficient of the proposed algorithm, a large number of experiments have been conducted. Experimental results demonstrate that the RL achieves better performance than several benchmarks, in terms of balancing the tradeoff among the overall resource utilization, the vNF-SC request blocking probability. © 2021, IAENG International Journal of Computer Science. All Rights Reserved.

关键词： Reinforcement learning

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IARA: An Orchestrating Improved Artificial Raindrop Algorithm for VNFs Deployment in Network Function Virtualization

IAENG International Journal of Computer Science

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IAENG International Journal of Computer Science 2020年第4期47卷 1-9页

作者： Xuan, Hejun Zhao, Xuelin Liu, Zhenghui Li, Yanling school of Computer and Information Technology Xinyang Normal University XinyangHenan464000 China Henan Key Lab. of Analysis and Application of Education Big Data Xinyang Normal University XinyangHenan464000 China

Network Function Virtualization (NFV) can provide the resource according to the request and can improve the flexibility of the network. It has become the key technology of 5G communication. Resource scheduling for virtual network function service chain (VNF-SC) is the key issue of the NFV. In this paper, the problem of routing and VNFs deployment for VNF service chain (VNF-SC) in inter-data center elastic optical networks (inter-DC EONs) is investigated. We investigate the inter-DC EONs that each data center only can provide some specific VNFs, and the system resources of all the data centers are limited. In addition, part of requiblack VNFs in each VNF-SC is dependent, i.e., the relative order of requiblack VNFs is fixed. To solve the challenging problem, we first establish a mix-integer programming model. Then, to make the population distributed on the search domain uniformly, uniform design method was developed. In addition, an improved artificial raindrop algorithm (IARA) for the established model, which inspired by particle swarm optimization and differential evolution, is proposed to solve the maximum model efficiently. Finally, to demonstrate high performance of the designed algorithm, a series of experiments are conducted in several different experimental scenes. Experimental results indicate that the proposed algorithm can obtain the better results than compared algorithm. © 2020. All Rights Reserved.

关键词： Network function virtualization

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tp-MA: Orchestrating Three Populations Memetic Algorithm for VNF Deployment in 5G Network

IAENG International Journal of Computer Science

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IAENG International Journal of Computer Science 2020年第4期47卷 1-10页

作者： Xuan, Hejun Wei, Shiwei Zhao, Xuelin Xue, Yahui Qiao, Lanlan Li, Yanling school of Computer and Information Technology Xinyang Normal University XinyangHenan464000 China School of Computer and Technology Guilin University of Aerospace Technology Guilin541000 China Henan Key Lab. of Analysis and Application of Education Big Data Xinyang Normal University XinyangHenan464000 China

Virtual network function (VNF) is the key issue and can provide various network services and is widely deployed in 5G communication. Routing and VNF deployment for the VNF service chain (VNF-SC) is a very important and well-known NP-hard problem. For this problem, if determining the number and locations of data centers is additionally considered, it will be more complexity. In this paper, we investigate a network planning problem by determining all these factors, i.e, by determining not only the optimal routing and the optimal VNF deployment for VNF-SCs, but also the optimal number and locations of data centers. To achieve this purpose, a three objectives optimization model, which minimizes capital expenditure, the maximum index of used frequency slots and the number of deployed VNFs on all data centers, is estimated. To solve this model efficiency, we integrate three objectives into one objective by using a weighted sum strategy. Then, a high-performance memetic algorithm with three populations (tp-MA), which includes well-designed crossover, mutation, and local search operators, is proposed. To demonstrate reasonable of the model and high performance of the designed algorithm, a series of experiments are conducted in several different experimental scenes. Experimental results indicate that the effectiveness of the proposed model and the efficiency of the proposed algorithm. © 2020. All Rights Reserved.

关键词： 5G mobile communication systems

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OBSCURE: Information-theoretic oblivious and verifiable aggregation queries 45th

OBSCURE: Information-theoretic oblivious and verifiable aggr...

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45th International Conference on Very Large data Bases, VLDB 2019

作者： Gupta, Peeyush Li, Yin Mehrotra, Sharad Panwar, Nisha Sharma, Shantanu Almanee, Sumaya University of California Irvine United States Xinyang Normal University and Henan Key Lab of Analysis and Application of Educating Big Data China

Despite extensive research on cryptography, secure and efficient query processing over outsourced data remains an open challenge. We develop communication-efficient and information-theoretically secure algorithms for privacy-preserving aggregation queries using multi-party computation (MPC). Specifically, query processing techniques over secret-shared data outsourced by single or multiple database owners are developed. These algorithms allow a user to execute queries on the secret-shared database and also prevent the network and the (adversarial) clouds to learn the user's queries, results, or the database. We further develop (non-mandatory) privacypreserving result verification algorithms that detect malicious behaviors, and experimentally validate the efficiency of our approach over large datasets, the size of which prior approaches to secretsharing or MPC systems have not scaled to. © 2018, VLDB Endowment.

关键词： Query processing

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