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International Conference on parallel and distributed Systems (ICPADS)

作者： Wei Liu Yang-Bin Tang Huai-Min Wang School of Computer National University of Defense Technology Changsha Hunan China National Laboratory for Parallel and Distributed Processing Changsha Hunan China Institute of Science National University of Defense Technology Changsha Hunan China

Reputation systems provide a promising way to build trust relationships between users in distributed cooperation systems, such as file sharing, streaming, distributed computing and social network, through which a user can distinguish good services or users from malicious ones and cooperate with them. However, most reputation models mainly focus on evaluating the qualities of different services in one dimension, but care less about the preferences of different users. This paper proposes a personalized reputation model which provides each user a personalized trust view on others according to his preference. In our approach, we aggregate the users' preferences with collaborative filtering method and qualify it with user similarity which is integrated into the computing of reputation values. The experimental results suggest that our model can resist possible kinds of malicious behaviors efficiently.

关键词： Computational modeling Measurement Indexes Aggregates Resists Peer to peer computing Electronic mail

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F3A: Fairness-Aware AI-Workloads Allocation Considering Multidimensional User Demands in JointCloud

F3A: Fairness-Aware AI-Workloads Allocation Considering Mult...

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IEEE International Conference on Joint Cloud Computing (JCC)

作者： Jiacheng Yang Guodong Yi Fei Gao Peichang Shi Huaimin Wang National Key Laboratory of Parallel and Distributed Processing College of Computer Science National University of Defense Technology Changsha China Xiangjiang Lab Changsha China School of Advanced Interdisciplinary Studies Hunan University Of Technology and Business Changsha China

ISBN: (数字)9798350387339

ISBN: (纸本)9798350387346

With the rapid growth of large language models, cloud computing has become an indispensable component of the AI industry. Cloud service providers(CSPs) are establishing AI data centers to service AI workloads. In the face of this surging need for AI computing power, building a connected computing environment across various clouds and forming a JointCloud presents an attractive solution. However, scheduling AI tasks across multiple AI data centers within a JointCloud environment presents a significant challenge: how to balance users’ demands while ensuring CSPs’ fairness in scheduling. Existing research primarily focuses on optimizing scheduling quality with limited consideration for fairness. Therefore, this paper proposes a Fairness-Aware AI-Workloads Allocation method (F3A), a fair cross-cloud allocation technique for AI tasks. F3A utilizes Point and Token to reflect both the resource status and historical task allocations of AI data centers, enabling the consideration of users’ multidimensional demands and facilitating fair task allocation across multiple centers. In order to better assess the fairness of scheduling, we also devised a fairness indicator(FI), based on the Gini coefficient to measure the fairness of task allocation. The experimental results demonstrate that F3A consistently maintains FI within 0.1 across various cluster sizes and different task quantities, representing an improvement of 76.45% compared to classical fair scheduling algorithms round-robin. F3A exhibits commendable performance in ensuring fairness in task allocation while also demonstrating effectiveness in cost reduction and enhancing user satisfaction.

关键词： Industries Data centers Cloud computing Job shop scheduling Costs Scheduling algorithms Large language models

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DCSA: The Deployment Mechanism of Chained Serverless Applications in JointCloud Environment

DCSA: The Deployment Mechanism of Chained Serverless Applica...

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IEEE International Conference on Joint Cloud Computing (JCC)

作者： Yaojie Li Peichang Shi Jianfei Liu Rui Li Fei Gao Penghui Ma Dong Xie Guodong Yi National Key Laboratory of Parallel and Distributed Processing College of Computer Science National University of Defense Technology Changsha China Xiangjiang Lab Changsha China School of Advanced Interdisciplinary Studies Hunan University Of Technology and Business Changsha China

ISBN: (数字)9798350387339

ISBN: (纸本)9798350387346

Serverless computing, comprised of Function as a Service (FaaS) and Backend as a Service (BaaS), has garnered widespread attention owning to its features such as maintenance-free operations, pay-per-use pricing, and automatic scalability. However, practical usage encounters several challenges: 1) The diversity of user applications makes comprehensive performance evaluation difficult, as benchmark and application tests only reflect performance under specific conditions and cannot fully capture users’ actual experiences across different serverless platforms. 2) Disparities in performance and costs across different serverless platforms make it challenging to achieve optimal performance and cost efficiency through single-cloud deployment, thereby underutilizing the advantages of each platform. 3) Vendor lock-in issues restrict the migration of user applications and exacerbate dependence on a single cloud *** address these challenges, this paper proposes a collaborative mechanism, referred to as DCSA, which integrates FaaS and storage services to achieve automatic cross-cloud deployment of user applications while considering both performance and cost comprehensively. Firstly, we adapt the interfaces of different serverless platforms, effectively reducing the complexity of cross-cloud deployment. Secondly, we develop cost and latency models for the cross-cloud deployment of chained serverless applications and propose a deployment scheduling algorithm that simultaneously considers both latency and cost. Finally, we conduct experiments to evaluate the performance of the proposed algorithm. Results demonstrate that our method can effectively reduce latency (up to 2.3%) and lower costs (up to 9.9%).

关键词： Performance evaluation Adaptation models Costs Scheduling algorithms Scalability Serverless computing Collaboration

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DMSA: Decentralized and Multi-keyword Selective Data Sharing and Acquisition

DMSA: Decentralized and Multi-keyword Selective Data Sharing...

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International Symposium on parallel and distributed processing with Applications, ISPA

作者： Moheng Lin Peichang Shi Xiang Fu Feng Jiang Guodong Yi National Key Laboratory of Parallel and Distributed Computing College of Computer Science National University of Defense Technology Changsha China Xiangjiang Lab Changsha China

ISBN: (数字)9798331509712

ISBN: (纸本)9798331509729

Blockchain technology has been extensively uti-lized in decentralized data-sharing applications, with the immutability of blockchain providing a witness for the circulation of data. However, current blockchain data-sharing solutions still fail to address the simultaneous screening needs of both the sender and receiver with multi-keywords. Without the capability to support bilateral simultaneous filtering, the disclosure of reasons for matching failures could inadvertently expose sensitive user data. Therefore, the challenge lies in enabling ciphertexts with multiple keywords and receivers with multiple interests to achieve mutual and simultaneous matching. Based on the technical foundations of SE (Searchable Encryption), MABE (Multi-Attribute Based Encryption), and polynomial fitting, this paper proposes a scheme called DMSA (Decentralized and Multi-keyword selective Sharing and selective Acquisition). This scheme can satisfy soundness, enabling ciphertexts carrying multiple keywords and receivers representing multiple interests to match each other simultaneously. We conducted a security analysis that confirms the security of DMSA against chosen-plaintext attacks. Our experimental results demonstrate a significant efficiency improvement, with a 67% increase over single-keyword data-sharing schemes and a 16% enhancement compared to the existing multi-keyword data-sharing solution.

关键词： distributed processing Filtering Data security keyword search Fitting Receivers Polynomials Data models Blockchains Encryption

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Accelerating FDTD simulation of microwave pulse coupling into narrow slots on the Intel MIC architecture

Accelerating FDTD simulation of microwave pulse coupling int...

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IEEE Pacific Rim Conference on Communications, computers and Signal processing

作者： Qinglin Wang Jie Liu Xiantao Cui Guitao Fu Chunye Gong Zuocheng Xing School of Computer Science National University of Defense Technology Changsha China Science and Technology on Parallel and Distributed Processing Laboratory National University of Defense Technology Changsha China Beijing Satellite Navigation Center Beijing China

ISBN: (纸本)9781467377898

The coupling of microwaves into apertures plays an important part in many electromagnetic physics and engineering fields. When the width of apertures is very small, Finite Difference Time Domain (FDTD) simulation of the coupling is very time-consuming. As a many-core architecture, the Intel's Many Integrated Core (MIC) architecture owns 512-bit vector units and more than 200 threads. In this paper, we parallelize FDTD simulation of microwave pulse coupling into narrow slots on the Intel MIC architecture. In the implementation, the parallel programming model OpenMP is used to exploit thread parallelism while loop unrolling and SIMD intrinsic functions are utilized to accomplish vectorization. Compared with the serial version on Intel Xeon E5-2670 CPU, the implementation on the MIC coprocessor including 57 cores obtains a speedup of 11.57 times. The experiment results also demonstrate that the parallelization has good scalability in performance. Additionally, how binding relationship between OpenMP threads and hardware threads in MIC influences performance is also reported.

关键词： Microwave integrated circuits Finite difference methods Time-domain analysis Chlorine Hardware

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Vision-Language Navigation: A Survey and Taxonomy

arXiv

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arXiv 2021年

作者： Wu, Wansen Chang, Tao Li, Xinmeng Yin, Quanjun Zhu, Jiancheng The College of Systems Engineering National University of Defense Technology Hunan Changsha410073 China National Key Laboratory of Parallel and Distributed Processing College of Computer Science and Technology National University of Defence Technology Changsha410073 China

Vision-Language Navigation (VLN) tasks require an agent to follow human language instructions to navigate in previously unseen environments. This challenging field involving problems in natural language processing, computer vision, robotics, etc., has spawn many excellent works focusing on various VLN tasks. This paper provides a comprehensive survey and an insightful taxonomy of these tasks based on the different characteristics of language instructions in these tasks. Depending on whether the navigation instructions are given for once or multiple times, this paper divides the tasks into two categories, i.e., single-turn and multi-turn tasks. For single-turn tasks, we further subdivide them into goal-oriented and route-oriented based on whether the instructions designate a single goal location or specify a sequence of multiple locations. For multi-turn tasks, we subdivide them into passive and interactive tasks based on whether the agent is allowed to question the instruction or not. These tasks require different capabilities of the agent and entail various model designs. We identify progress made on the tasks and look into the limitations of existing VLN models and task settings. Finally, we discuss several open issues of VLN and point out some opportunities in the future, i.e., incorporating knowledge with VLN models and implementing them in the real physical world. © 2021, CC BY.

关键词： Taxonomies

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A novel anycast-based integrated routing protocol for wireless sensor networks: Design and implementation

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Journal of Computational Information Systems 2013年第21期9卷 8611-8618页

作者： Yan, Guofeng Peng, Yuxing Chen, Shuhong School of Computer and Communication Hunan Institute of Engineering China Science and Technology on Parallel and Distributed Processing Laboratory National University of Defense Technology Changsha 410073 China School of Computer National University of Defense Technology Changsha 410073 China School of Information Science and Engineering Central South University Changsha 410083 China

In this paper, we consider novel anycast-based integrated routing protocol (AIRP) to reduce the cost in delay performance of communications in multihop WSNs. Without tight time synchronization or known geographic information, AIRP provides low-delay cost route. We implement a low-overhead AIRP module in TinyOS kernel by modifying BLIP protocol stack, i. e., the Berkeley Low-power IP stack;as demonstrated, this implementation can be incorporated into existing routing protocols with the least effort. We describe the format of AIRP message, the dynamic updating process of MAP table information, and anycast data flow in detail under TinyOS. And then, we present the anycast group management system. Finally, we show the performance of AIRP where AIRP communication is used to distribute load among a set of servers through a study case. © 2013 Binary Information Press.

关键词： Wireless sensor networks

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Orthogonal Nonnegative Locally Linear Embedding

Orthogonal Nonnegative Locally Linear Embedding

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IEEE International Conference on Systems, Man, and Cybernetics

作者： Lei Wei Naiyang Guan Xiang Zhang Zhigang Luo Dacheng Tao National Laboratory for Parallel and Distributed Processing School of Computer Science National University of Defense Technology Changsha 410073 P.R. China These authors contributed equally to this paper National Laboratory for Parallel and Distributed Processing School of Computer Science National University of Defense Technology Changsha 410073 P.R. China Centre for Quantum Computation and Intelligence Systems and Faculty of Engineering and Information Technology University of Technology Sydney Sydney NSW 2007 Australia

ISBN: (纸本)9781479906505

Nonnegative matrix factorization (NMF) decomposes a nonnegative dataset X into two low-rank nonnegative factor matrices, i.e., W and H, by minimizing either Kullback-Leibler (KL) divergence or Euclidean distance between X and WH. NMF has been widely used in pattern recognition, data mining and computer vision because the non-negativity constraints on both W and H usually yield intuitive parts-based representation. However, NMF suffers from two problems: 1) it ignores geometric structure of dataset, and 2) it does not explicitly guarantee partsbased representation on any datasets. In this paper, we propose an orthogonal nonnegative locally linear embedding (ONLLE) method to overcome aforementioned problems. ONLLE assumes that each example embeds in its nearest neighbors and keeps such relationship in the learned subspace to preserve geometric structure of a dataset. For the purpose of learning parts-based representation, ONLLE explicitly incorporates an orthogonality constraint on the learned basis to keep its spatial locality. To optimize ONLLE, we applied an efficient fast gradient descent (FGD) method on Stiefel manifold which accelerates the popular multiplicative update rule (MUR). The experimental results on real-world datasets show that FGD converges much faster than MUR. To evaluate the effectiveness of ONLLE, we conduct both face recognition and image clustering on real-world datasets by comparing with the representative NMF methods.

关键词： Nonnegative matrix factorization Locally linear embedding Fast gradient descent Stiefel manifold Dataset Nonnegative matrix decomposition geometrical construction NMF protocol images embedding Flue gas desulfurization Nearest neighbor Orthogonal

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Security Issues and Solutions in Cloud Computing

Security Issues and Solutions in Cloud Computing

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International Conference on distributed Computing Systems Workshop

作者： Pengfei You Yuxing Peng Weidong Liu Shoufu Xue National Key Laboratory for Parallel and Distributed Processing School of Computer Science National University of Defense Technology Changsha China Jiangsu Automation Research Institute Jiangsu China CPLA Air Defence Forces Command Academy Zhengzhou Henan China

Recently, Cloud computing, as one of the hottest words in IT world, has drawn great attention. Many IT companies such as IBM, Google, Amazon, Microsoft, Yahoo and others vigorously develop cloud computing systems and related products to customers. However, there are still some difficulties for customers to adopt cloud computing, in which many security issues exist, because data for a customer is stored and processed in cloud, not in a local machine. This paper briefly introduces cloud computing and its key concepts. In particularly, we intend to discuss security requirements and security issues involving data, application and virtualization in cloud computing, as well as current solutions to these issues.

关键词： Cloud computing Computational modeling Virtual machine monitors Operating systems Cryptography

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Hierarchical routing algorithm for ad hoc networks using mobile VMN

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International Journal of Autonomous and Adaptive Communications Systems 2016年第1-2期9卷 40-56页

作者： Yan, Guofeng Peng, Yuxing Liu, Junyi Chen, Shuhong School of Computer and Communication Hunan Institute of Engineering Xiangtan411101 China Science and Technology on Parallel and Distributed Processing Laboratory National University of Defense Technology Changsha410073 China School of Computer National University of Defense Technology Changsha410073 China School of Information Science and Engineering Central South University Changsha410083 China

One of the most significant challenges introduced by routing protocol in mobile networks is coping with the unpredictable motion and the unreliable behaviour of mobile nodes. In this paper, we present a hierarchical routing algorithm based on virtual mobile node (VMN). A routing path can be found rapidly by exchanging path information between VMNs without accurate topology information. We discuss the routing process and the implementing details of the proposed routing algorithm. Finally, we evaluate the performance of our hierarchical routing algorithm through simulations, and the results show that the number of mobile WAVE generated by routing algorithm is well satisfied with the quality of service (QoS) requirements of all source and destination nodes. Furthermore, we compare the performance on VMN failure and message delivery ratio using hierarchical and non-hierarchical routing approaches, the results show that we can obtain magnitude better performance by HRA-VMN than hierarchical state routing (HSR) and non-hierarchical routing approach. Copyright © 2016 Inderscience Enterprises Ltd.

关键词： Routing algorithms

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