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SNIP: Southbound Message Delivery with In-network Pruning in Clouds 28

SNIP: Southbound Message Delivery with In-network Pruning in...

引用

IEEE 28th International conference on parallel and distributed Systems (IEEE ICPADS)

作者： Yu, Yan Zhao, Gongming Xu, Hongli Tu, Huaqing Luo, Luyao Xie, Liguang Univ Sci & Technol China Sch Data Sci Hefei Peoples R China Univ Sci & Technol China Sch Comp Sci & Technol Hefei Peoples R China Futurewei Technol Santa Clara CA USA

ISBN: (纸本)9781665473156

In a hyper-scale cloud data center, a large number of control messages are distributed to hundreds of thousands of compute nodes from a logically centralized control plane. The delivery of these control messages, a.k.a. southbound messages, is critical to cloud infrastructure management, as it greatly affects customer experience. Existing works mainly deal with southbound message delivery by two methods: point-to-point transmission and Message Queue (MQ)-based solutions. With the point-to-point transmission method, each message is sent from the control plane to compute nodes directly, which may cause high control complexity and overhead in hyper-scale clouds. The MQ-based method can address the challenge of high complexity through message aggregation and subscribe/publish model. However, it usually brings in redundant messages, and further causes extra load on compute nodes. To solve the problem above, we design SNIP, which exploits the ability of programmable switches to perform in-network message pruning and to reduce message redundancy. Specifically, forwarding and processing information computed by the control plane is attached to the package header of every control message. Redundant messages can be identified and processed by programmable switches. In addition, we propose a rounding-based algorithm to prune messages with minimal redundancy. The simulation results show that SNIP can reduce the control overhead by 80%-85% and the total traffic of redundant messages by 35% compared with existing solutions.

关键词： Southbound Message Delivery Message Queue Programmable Switch In-network Pruning

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A Ray-based Asynchronous distributed parallel K-SVD Method 12

A Ray-based Asynchronous Distributed Parallel K-SVD Method

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12th International conference on Advanced Cloud and Big Data, CBD 2024

作者： Li, Yongkang Chen, Xiaodong Wan, Xiaohui Sun, Jin Zheng, Peng Wang, Yunchang Wu, Zebin School of Computer Science and Engineering Nanjing University of Science and Technology Nanjing China Quzhou Transportation Bureau Department of Industry Development Quzhou China Chang shan Inspection and Testing institute Department of Quality Control and Testing Quzhou China

ISBN: (纸本)9798331511074

K-SVD (K-Singular Value Decomposition)is a com-monly used dictionary learning method that progressively opti-mizes dictionaries to better represent data by iterating sparse coding and dictionary update steps. However, with the increasing data size, the traditional K -SVD method faces significant challenges in terms of computational efficiency. Therefore, this paper proposes an asynchronous distributed parallel K-SVD method based on Ray framework to cope with the computational efficiency problem in large-scale data processing. This method achieves efficient parallel computation by decomposing the sparse coding and dictionary updating steps of the K-SVD method into multiple independent tasks and utilizing the distributed scheduling capability of the Ray framework. Since the zero elements of the coefficient matrix are unevenly distributed, we introduce a stride partitioning approach when performing the decomposition. In addition, in order to avoid the method falling into local optima and failing to find global optima due to parallelism, this paper synchronizes with the global at the same time as the atomic update of the dictionary. Meanwhile, for the purpose of avoiding the overhead caused by data synchronization, a parameter server is introduced to realize asynchronous updating of dictionary and coefficient matrix to reduce the overhead caused by communication. The experimental results show that, compared with the traditional K-SVD method, the method proposed in this paper has a significant advantage in computational efficiency and is able to efficiently process hyperspectral image datasets under the premise of guaranteeing the sparse representation accuracy. Compared with the synchronous parallel K-SVD method, the proposed method has faster error convergence and does not fall into local optima. © 2024 IEEE.

关键词： network security

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Prefetching-based Adaptive Video Streaming Strategy on Edge Computing 29

Prefetching-based Adaptive Video Streaming Strategy on Edge ...

引用

29th IEEE International conference on parallel and distributed Systems, ICPADS 2023

作者： Yi, Xuanyu Zhou, Jipeng Jinan University Department of Computer Science Guangzhou China Jinan University School of Data Science of Guangzhou Huashang College Department of Computer Science Guangzhou China

ISBN: (纸本)9798350330717

Dynamic Adaptive Streaming over HTTP (DASH) is a widely adopted video streaming protocol. Adaptive Bitrate Streaming (ABR) algorithm is utilized to dynamically switch between different bitrates. However, traditional ABR algorithms have gradually failed to meet users' demands for high-quality video transmission, especially in complex network environments. Thus, the current research focus has shifted towards enhancing the accuracy of algorithm. The advent of edge computing has brought new possibilities for DASH transmission. Edge computing-based algorithms can make decisions from a more macroscopic perspective, which can enhance algorithm efficiency. In this paper, we propose an edge computing-based strategy that enables the edge server to obtain the actual file size of the next segment at every bitrate. As a result, edge servers can obtain more informations. We further propose an edge-based system model that assists the ABR algorithm in achieving better operational efficiency. With additional information, the algorithm located at the edge node possesses the capability to make more precise decisions, which is advantageous for enhancing the quality of experience (QoE) for users. Our experiments demonstrate that the proposed strategy can significantly enhance QoE and network resource utilization. © 2023 IEEE.

关键词： DASH Edge Computing Video Streaming

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GANDPS: Ensuring Both Detection Precision and Stability in GAN-based Anomaly Detection for network Traffic 21

GANDPS: Ensuring Both Detection Precision and Stability in G...

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21st IEEE International Symposium on parallel and distributed processing with Applications, 13th IEEE International conference on Big Data and Cloud Computing, 16th IEEE International conference on Social Computing and networking and 13th International conference on Sustainable Computing and Communications, ISPA/BDCloud/SocialCom/SustainCom 2023

作者： Li, Liuhuan Yang, Ximin Zhang, Xiao Yang, Yumeng Chen, Xuefeng Tang, Wan South-Central Minzu University School of Computer Science Wuhan China Key Laboratory of Cyber-Physical Fusion Intelligent Computing State Ethnic Affairs Commission China China Telecom Group GuiZhou Co. Ltd. Guiyang China

ISBN: (纸本)9798350329223

With the ever-growing network traffic and the vast amount of abnormal traffic being created, anomaly detection methods have attracted close attention in the cybersecurity domain. Generative adversarial networks (GANs) have been applied to network traffic anomaly detection, but obtaining high-precision and consistently stable detection results is still challenging for current methods. In the paper, we propose an improved GAN-based anomaly detection method called GANDPS for network traffic. The improved GAN introduces an encoder based on the original GAN, and a specialized layer is integrated into the encoder to process abnormal data. This improvement enables the encoder to effectively capture the features of normal data while distinguishing the features of abnormal data. In addition, an analogous reconstruction training strategy is employed between the generator and the encoder to balance the adversarial training between the generator and the discriminator, thereby improving the detection precision and stability of the GAN-based model. This comprehensive enhancement not only effectively elevates the detection performance of our method, but also ensures stable detection results. Experimental results on public datasets demonstrate that the proposed GANDPS outperforms multiple GAN-based methods in terms of detection precision, recall, and F1-score, and the detection results are stabilized within acceptable ranges. © 2023 IEEE.

关键词： Anomaly detection

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An Online Detection System for LDoS attack based on XGBoost 21

An Online Detection System for LDoS attack Based on XGBoost

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作者： Deng, Jialun Cheng, Li Yuan, HaiWen Zheng, Kuanlei Li, Xuan Li, Quli Wuhan Institute of Technology College of Electrical Information Wuhan China

ISBN: (纸本)9798350329223

Low-rate-Denial-of-Service (LDoS) attack poses a significant threat to network service quality and even has the potential to cause network paralysis. Therefore, it is urgent to conduct research on LDoS. However, the deployment of extension modules for online attack detection in traditional networks is a formidable undertaking due to the limited flexibility and scalability inherent in conventional network equipment. Software-Defined networking (SDN) offers a viable solution to this challenge. SDN represents an innovative network architecture that delivers both flexibility and programmability by segregating the network Control Plane from the Data forwarding Plane, thereby enabling real-time detection of LDoS attack. In this paper, we implemented a real-time LDoS attack detection system on SDN, with Extreme Gradient Boosting (XGBoost) serving as the primary method for identifying LDoS attack. Furthermore, we employed RYU as the SDN controller, utilized the Mininet simulation software to create network topologies, and employed attack code to simulate a real LDoS attack environment. The XGBoost classifier is applied to detect LDoS attack in the real-time network traffic collected by the OpenFlow protocol, and its performance is compared with that of several other classifiers. Experimental results conclusively demonstrated that XGBoost exhibited the most optimal detection performance, achieving accuracy and F1 scores of 97.43% and 98.37%,respectively. © 2023 IEEE.

关键词： network architecture

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FlowValve: Packet Scheduling Offloaded on NP-based SmartNICs 42

FlowValve: Packet Scheduling Offloaded on NP-based SmartNICs

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42nd IEEE International conference on distributed Computing Systems (ICDCS)

作者： Xi, Shaoke Li, Fuliang Wang, Xingwei Northeastern Univ Shenyang Peoples R China Zhejiang Univ Hangzhou Peoples R China

ISBN: (数字)9781665471770

ISBN: (纸本)9781665471770

Enforcing scheduling policies at end-hosts with software schedulers suffers from high CPU consumption, low throughput, and inaccuracy. Offloading scheduling functions to the network interface card (NIC) provides a promising direction to address these problems. However, existing efforts in scheduling offloading suffer from inflexible on-NIC packet schedulers, which cannot execute complex hierarchies of network policies. In this paper, we present FlowValve, the first parallel packet scheduler for network Processor (NP)-based SmartNlCs that offloads critical functions of Linux traffic control, including packet classifying and scheduling. The key insight behind FlowValve is to abstract inherent queues attached to the NIC interface (wire side) as a single FIFO queue and perform specialized tail drop to mix the FIFO queue with expected flow proportions. FlowValve takes advantage of on-chip multi-core parallelism and hardware accelerations to produce high throughput. Meanwhile, it substantially reduces CPU and memory burdens on endhosts. We prototype FlowValve on a Netronome Agilio SmartNIC and demonstrate its effectiveness against non-offloaded kernel schedulers and DPDK QoS Scheduler. We find that FlowValve outperforms both in accurately enforcing network policies while driving line rate performance (i.e., 40Gbps), which contributes to saving at least two CPU cores.

关键词： Scheduling algorithms Multicore processing Linux Wires Tail Traffic control parallel processing

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Transitioning to Smart Sustainable Cities based on Cutting-Edge Technological Improvements

Transitioning to Smart Sustainable Cities Based on Cutting-E...

引用

29th International conference on parallel and distributed Computing (Euro-Par)

作者： Andreou, Andreas Mavromoustakis, Constandinos X. Univ Nicosia Dept Comp Sci Nicosia Cyprus Univ Nicosia Res Fdn Nicosia Cyprus

ISBN: (纸本)9783031488023;9783031488030

A smart city is a concept that has been gaining momentum in recent years as cities worldwide seek to improve their efficiency, sustainability, and quality of life for their residents. Smart cities are constructed atop smart data. Therefore, this research work focuses on the optimization of data acquisition, data sharing and data analysis. Aiming towards this evolution, the research elaborates on the advancement of smart healthcare, a novel approach for energy consumption, preparedness for a potential pandemic, innovative data encryption techniques, and vehicle-to-everything (V2X) connectivity to enable smart mobility. However, developing an intelligent ecosystem is paramount to providing citywide, reliable, high multi-Gbps peak data speeds with ultra-lowlatency. Hence, we finally focused our research on Unmanned Aerial Vehicles (UAV) assisted network optimization.

关键词： Smart Cities UAV Healthcare Consumption V2X

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Reliability Dynamic Perception-based Power Line Communication Hierarchical networking Method 4

Reliability Dynamic Perception-based Power Line Communicatio...

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4th International conference on Information Science, parallel and distributed Systems, ISPDS 2023

作者： Shi, Zhan Li, Bo Wu, Zhentian Wang, Xiuzhu Guangdong Power Grid Co. Ltd. Power Dispatching Control Center Communication Management Department Guangdong China Guangdong Electric Power Communication Technology Co. Ltd. Science Innovation Department Guangdong China

ISBN: (纸本)9798350337181

With the large-scale access of distributed photovoltaic, controllable load, and energy storage devices to the low-voltage distribution network, the requirements for the transmission quality and processing efficiency of power line communication data are rapidly increasing. However, large access of high proportion power electronic components will introduce color noise, which will have a great impact on the channel environment of power line communication. This paper first constructs a multi-layer hierarchical power line communication networking architecture. Then, a reliability dynamic perception-based optimal subcarrier selection method is proposed to meet the high-speed transmission requirements of renewable power system services. The simulation results show that the algorithm has excellent performance in probability of selecting the optimal subcarrier versus iteration and data transmission efficiency. © 2023 IEEE.

关键词： Memory architecture

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Multimodal Rumor Detection with Causal Graph Attention network 29

Multimodal Rumor Detection with Causal Graph Attention Netwo...

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29th IEEE International conference on parallel and distributed Systems, ICPADS 2023

作者： Huang, Jiawen Cao, Donglin Lin, Dazhen Xiamen University School of Informatics Xiamen China

ISBN: (纸本)9798350330717

In the era of big data, the automatic detection and governance of rumors are of great significance in protecting the privacy and security of users. Many previous works have achieved good results in rumor detection through multimodal feature fusion, background knowledge expansion, etc. Causality in rumors is a potential textual feature representing rumors' linguistic logic and causality semantics. The rumors' causality often appears inconsistent with the truth, based on which we can improve the rumor detection model. However, previous work has neglected the use of the feature of causality between entities in rumor texts. To address these challenges, we propose a Causal Graph Attention network (CGANet) for multimodal rumor detection, which constructs a causal graph for the rumor dataset to achieve better detection performance. CGANet extracts the node and causal relationship features of causal graphs through graph learning and enhances the causal semantics of multimodal features, thereby improving the detection ability of the model on false causal semantic content. Finally, we use a self-attention classification network to obtain the rumor detection results. We conducted experiments on two public benchmark datasets, Pheme and Weibo, and achieved an accuracy of 92.81% and 91.32%, respectively, better performance than the state-of-the-art methods. It proves the advantage of causal graphs in rumor detection tasks. © 2023 IEEE.

关键词： Causal Graph Data analytics Machine Learning Neural network Rumor Detection

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3D Single Target Tracking Algorithm based on Dynamic Search Center 29

3D Single Target Tracking Algorithm Based on Dynamic Search ...

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29th IEEE International conference on parallel and distributed Systems, ICPADS 2023

作者： Zhu, Yanping Chen, Qi Jiang, Aimin Zhu, Chenyang Liu, Chang Chen, Wenlong Changzhou University College of Microelectronics and Control Eng. Changzhou China Changzhou University College of Computer Sci. and Ai Changzhou China Hohai University College of Information Sci. and Eng. Changzhou China

ISBN: (纸本)9798350330717

In the realm of 3D single object tracking (SOT), Siamese network-based algorithms have shown remarkable performance. However, they can lose track of targets in complex environments. To enhance tracking accuracy and continuity, in this paper we introduce a new re-detection mechanism with a dynamic anchor relocation strategy. This mechanism includes: (i) dynamic anchor generation: When tracking fails, dynamic anchors are generated and adjusted until the target is re-detected. The most confident anchor prediction becomes the tracking result;(ii) model aggregation: A re-detected module is integrated into the PTT-Net framework, significantly improving tracking accuracy compared to other algorithms;(iii) reliability assessment: An assessment criterion for tracking reliability in PTT-Net is established to balance accuracy and speed. © 2023 IEEE.

关键词： dynamic anchor object tracking re-detection mechanism Siamese network tracking reliability

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