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A Unified programming Model over Heterogeneous Data Planes 7

A Unified Programming Model over Heterogeneous Data Planes

引用

7th International conference on Computer and Communications, ICCC 2021

作者： Li, Xianhai Shi, Zhou Pan, Jiangyu Tian, Ye School of Computer Science and Technology University of Science and Technology of China Hefei China

ISBN: (纸本)9781665409506

Software Defined networking (SDN) separates the data plane and the control plane in the traditional network, and the data plane communicates with the control plane through standard protocols. With the development of SDN, there are many southbound communication protocols in academia, such as openFlow, Protocol Oblivious Forwarding (POF), programming protocol-independent packet processors (P4). The design ideas and implementation of these protocols are very different. Therefore, many controllers provide some high-level Application programming Interfaces (API) supporting different protocols to shield the complexity of the protocol and facilitate the writing of network strategies, but none of them can support different southbound protocols at the runtime. That is, the controller can't support a variety of different protocols while the data plane has kinds of switches. For example, open network Operating System (ONOS) supports P4 and openFlow, but it can only support a specific data plane at the runtime, so it cannot combine the strengths and advantages of different types of programmable switches. This paper proposes a unified programming model that can support both the P4 and POF protocols at the runtime so that network users can combine the high performance of the P4 and the flexibility of the POF. We also provide kinds of API to facilitate the writing of network strategies. In certain application scenarios, the losing of data packets caused by updating the data plane pipeline can be effectively eliminated with the programming model. © 2021 ieee.

关键词： Controllers

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Addressing the ieee AV Test Challenge with SCENIC and VERIFAI 3

Addressing the IEEE AV Test Challenge with SCENIC and VERIFA...

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3rd ieee International conference on Artificial Intelligence Testing (AITest)

作者： Viswanadha, Kesav Indaheng, Francis Wong, Justin Kim, Edward Kalvan, Ellen Pant, Yash Fremont, Daniel J. Seshia, Sanjit A. Univ Calif Berkeley Berkeley CA 94720 USA Univ Calif Santa Cruz Santa Cruz CA 95064 USA

ISBN: (纸本)9781665434812

This paper summarizes our formal approach to testing autonomous vehicles (AVs) in simulation for the ieee AV Test Challenge. We demonstrate a systematic testing framework leveraging our previous work on formally-driven simulation for intelligent cyber-physical systems. First, to model and generate interactive scenarios involving multiple agents, we used SCENIC, a probabilistic programming language for specifying scenarios. A SCENIC program defines an abstract scenario as a distribution over configurations of physical objects and their behaviors over time. Sampling from an abstract scenario yields many different concrete scenarios which can be run as test cases for the AV. Starting from a SCENIC program encoding an abstract driving scenario, we can use the VERIFAI toolkit to search within the scenario for failure cases with respect to multiple AV evaluation metrics. We demonstrate the effectiveness of our testing framework by identifying concrete failure scenarios for an open-source autopilot, Apollo, starting from a variety of realistic traffic scenarios.

关键词： Measurement Computer languages Systematics conferences Tools Cyber-physical systems Probabilistic logic

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OrchestRAN: network Automation through Orchestrated Intelligence in the open RAN

OrchestRAN: Network Automation through Orchestrated Intellig...

引用

ieee Annual Joint conference: INFOCOM, ieee Computer and Communications Societies

作者： Salvatore D’ Oro Leonardo Bonati Michele Polese Tommaso Melodia Institute for the Wireless Internet of Things Northeastern University Boston MA U.S.A.

The next generation of cellular networks will be characterized by softwarized, open, and disaggregated architectures exposing analytics and control knobs to enable network intelligence via innovative data-driven algorithms. How to practically realize this vision, however, is largely an open problem. For a given network optimization/automation objective, it is currently unknown how to select which data-driven models should be deployed and where, which parameters to control, and how to feed them appropriate inputs. In this paper, we take a decisive step forward by presenting and prototyping OrchestRAN, a novel orchestration framework for next generation systems that embraces and builds upon the open Radio Access network (RAN) paradigm to provide a practical solution to these challenges. OrchestRAN has been designed to execute in the non-Real-time (RT) RAN Intelligent Controller (RIC) and allows network Operators (NOs) to specify high-level control/inference objectives (i.e., adapt scheduling, and forecast capacity in near-RT, e.g., for a set of base stations in Downtown New York). OrchestRAN automatically computes the optimal set of data-driven algorithms and their execution location (e.g., in the cloud, or at the edge) to achieve intents specified by the NOs while meeting the desired timing requirements and avoiding conflicts between different data-driven algorithms controlling the same parameters set. We show that the intelligence orchestration problem in open RAN is NP-hard, and design low-complexity solutions to support real-world applications. We prototype OrchestRAN and test it at scale on Colosseum, the world’s largest wireless network emulator with hardware in the loop. Our experimental results on a network with 7 base stations and 42 users demonstrate that OrchestRAN is able to instantiate data-driven services on demand with minimal control overhead and latency.

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Trace Visualization within the Software City Metaphor: A Controlled Experiment on Program Comprehension

Trace Visualization within the Software City Metaphor: A Con...

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Working conference on Software Visualization (VISSOFT)

作者： Dashuber, Veronika Philippsen, Michael QAware GmbH Munich Germany Friedrich Alexander Univ Erlangen Nurnberg FAU Programming Syst Grp Erlangen Germany

ISBN: (纸本)9781665431446

Especially with the rise of microservice architectures, software is hard to understand when just the static dependencies are known. The reason is that the actual call paths and the dynamic behavior of the application is hidden behind network communication. To comprehend what is going on in the software the vast amount of runtime data (traces) needs to be reduced and visualized. DYNACITY uses the city metaphor for visualization. Its novel trace visualization displays dynamic dependencies as arcs atop the city. To reduce the number of traces, DYNACITY aggregates all requests between the same two components into one arc whose brightness reflects both the number and the total duration of the requests. DYNACITY also encodes dynamic trace data in a heatmap that it uses to light up the building: the brighter a building is, the more active it is, i.e., the more and the longer the requests are that it receives and/or spawns. In a controlled experiment, we compare our approach with a traditional trace visualization built into the same Software City but showing all dependencies (without aggregation) as individual arcs and also disabling the heatmap. The study shows that professional software developers can solve typical software comprehension tasks faster (5.84%) and more correctly (11.7%) with the help of DYNACITY and that they prefer our approach over the more traditional dynamic trace visualization.

关键词： trace visualization software city program comprehension aggregation heatmap

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Boosting Adversarial Training via Fisher-Rao Norm-Based Regularization

Boosting Adversarial Training via Fisher-Rao Norm-Based Regu...

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conference on Computer Vision and Pattern Recognition (CVPR)

作者： Xiangyu Yin Wenjie Ruan University of Liverpool UK

ISBN: (数字)9798350353006

ISBN: (纸本)9798350353013

Adversarial training is extensively utilized to improve the adversarial robustness of deep neural networks. Yet, miti-gating the degradation of standard generalization performance in adversarial-trained models remains an open prob-lem. This paper attempts to resolve this issue through the lens of model complexity. First, We leverage the Fisher-Rao norm, a geometrically invariant metric for model complexity, to establish the non-trivial bounds of the Cross-Entropy Loss-based Rademacher complexity for a ReLU-activated Multi-Layer Perceptron. Then we generalize a complexity-related variable, which is sensitive to the changes in model width and the trade-off factors in adversarial training. Moreover, intensive empirical evidence validates that this variable highly correlates with the generalization gap of Cross-Entropy loss between adversarial-trained and standard-trained models, especially during the initial and final phases of the training process. Building upon this observation, we propose a novel regularization framework, called Logit-Oriented Adversarial Training (LOAT), which can mitigate the trade-off between robustness and accuracy while imposing only a negligible increase in computational overhead. Our extensive experiments demonstrate that the proposed regularization strategy can boost the performance of the prevalent adversarial training algorithms, including PGD-AT, TRADES, TRADES (LSE), MART, and DM-AT, across various network architectures. Our code will be available at https://***/TrustAI/LOAT.

关键词： Training Accuracy Sensitivity Computational modeling Artificial neural networks network architecture Robustness

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MISO: A CRDT-based Middleware for Stateful Objects in the Serverless Edge-Cloud Continuum

MISO: A CRDT-based Middleware for Stateful Objects in the Se...

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ieee International conference on Cloud Engineering (IC2E)

作者： Valentin Goronjic Stefan Nastic Distributed Systems Group TU Wien Austria

ISBN: (数字)9798331528690

ISBN: (纸本)9798331528706

Serverless functions typically depend on external services to manage the application state, which can be difficult at the Edge due to high latency and network costs. Current solutions for stateful serverless functions at the Edge either have limited support for data locality or require mutual consensus for write operations which is hard to achieve at the Edge. This paper introduces MISO, a novel middleware for serverless computing that enables stateful serverless functions across the Edge-Cloud continuum. The middleware provides MISO Objects offering data locality. It is interoperable with existing serverless platforms and allows concurrent state modifications in a decentralized manner. The main contributions of our work include: i) A novel conceptual model to maintain application state in serverless functions called MISO Objects, ii) MISO middleware and an SDK for serverless functions, and iii) The asynchronous state replication mechanism of MISO Objects using an overlay network to optimize data transfer and resource consumption. Our evaluation demonstrated that MISO outperforms the state-of-theart by up to $243 \%$ in terms of total execution time for AllReducetype operations. Furthermore, the state replication exhibits $O(n)$ scalability regarding time, throughput, memory usage, and data volume. We further demonstrate that our work can seamlessly be integrated into an open-source serverless platform and that our SDK requires up to $150 \%$ fewer lines of code and exhibits up to $75 \%$ less cognitive complexity than the state-of-the-art.

关键词： Codes Overlay networks Scalability Serverless computing Transforms MISO communication programming Throughput Complexity theory Middleware

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An improved network design of open loop reverse supply chain

An improved network design of open loop reverse supply chain

引用

2021 International conference on Automation, Control and Mechatronics for Industry 4.0, ACMI 2021

作者： Kabir, Md. Rashedul Kamal, Md. Shahriar Islam, Md. Zahidul Rajshahi University of Engineering Technology Department of Industrial and Production Engineering Rajshahi Bangladesh

ISBN: (纸本)9781665438438

In recent years, industries have been moving with tremendous speed towards "green thinking"as never before. Proceeding into a more circular economy will offer benefits such as reducing environmental burdens, enhancing the protection of raw material supply, increasing competition, promoting productivity, boosting sustainable economic growth and creating employment. Remanufacturing leads to circularity, while reverse supply chains pose difficulties. Closed loop supply chains are prioritized for reverse supply chain networks. However, alternative supply chains and different market actors make remanufacturing possible through open loops. In this study, a new integrated mathematical approach is proposed to address designing a multi-stage, multi-product and multi-period open loop reverse supply chain network which maximizes the profit and utilizes reverse logistics to benefit the environment in the most efficient way. The proposed approach presents a mixed integer linear programming model (MILP) that uses water treatment facility along with the common components of open loop reverse supply chain (OLSC). The objective determines the facility location and material flows between stages in each period. Using a realistic network instance, computational results are used to verify the feasibility of the study. © 2021 ieee.

关键词： Supply chain management

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Development of Intelligent Ground Control Station and Autopilot architectures for UAVs and UGVs

Development of Intelligent Ground Control Station and Autopi...

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ieee Signal Processing and Communications Applications (SIU)

作者： Emre Çintaş Barış Özyer Bilgisayar Mühendisliği Bölümü Atatürk Üniversitesi Erzurum Türkiye Bilgisayar Mühendisliği Bölümü Erzurum Teknik Üniversitesi Erzurum Türkiye

ISBN: (数字)9798350388961

ISBN: (纸本)9798350388978

Multi-rotor Unmanned Aerial and Ground Vehicles (UAV/UGV) are utilized for various military and civilian purposes such as detection, mapping, surveillance, target destruction, observation, and logistical applications due to their high agility, mechanical simplicity, ease of control, and autonomous capabilities. With advancing technology, UAVs and UGVs can be remotely controlled autonomously by onboard computers or by a pilot at a ground control station (GCS). Integrating these onboard computers into UAVs/UGVs enables information flow between the different modules they possess and the GCS. However, due to the traditional processing of this information flow in GCS software studies in the literature, there is a need for different and intelligent GCS software and autopilot design approaches. In this study, an intelligent new GCS capable of remotely commanding and controlling UAVs/UGVs has been designed, equipped with artificial intelligence features, capable of real-time recognition, positioning of more than seventy objects, and communication with UAVs/UGVs. The open-source Java programming language was used for coding operations, and the MAVLink (Micro Air Vehicle Link) protocol was utilized for communication between UAVs/UGVs and the GCS. For real-time object detection and localization, one of the fast and highly accurate algorithms in the literature, SSD MobileNet v2, was used and integrated with the GCS via Flask API. The obtained results demonstrated the consistency between the initial motivation and the software outputs, leading to the development of an open-source intelligent ground control station software and autopilot.

关键词： Computers Protocols Surveillance Software algorithms Signal processing algorithms Object detection Signal processing

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GOX: Towards a Scalable Graph Database-Driven SDN Controller

GOX: Towards a Scalable Graph Database-Driven SDN Controller

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ieee conference on network Softwarization (NetSoft)

作者： Fetia Bannour Stefania Dumbrava Alex Danduran--Lembezat ENSIIE &#x0026 SAMOVAR Evry France ENSIIE Evry France

ISBN: (数字)9781665406949

ISBN: (纸本)9781665406956

The Software-Defined networking (SDN) paradigm relies on decoupling the control and data planes, and logically centralizing SDN control to enable direct network programming via open interfaces. New abstractions are thus needed in a bid to rethink the traditional networking approach and create new opportunities for management and automation. We demonstrate the GOX controller, proposing a novel graph abstraction of the network topology in real time using the scalable Neo4j graph database. Our proof-of-concept was evaluated for a forwarding application designed for GOX. Compared to POX’s model, GOX shows better performance and scalability on synthetic topologies and real-world topologies from the Internet Topology Zoo.

关键词： Automation network topology Databases Scalability conferences programming Real-time systems

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Privacy Preserving Framework for Big Data Management in Smart Buildings

Privacy Preserving Framework for Big Data Management in Smar...

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19th ieee International conference on Pervasive Computing and Communications (ieee PerCom)

作者： Inibhunu, Catherine McGregor, Carolyn Ontario Tech Univ Oshawa ON Canada Univ Technol Sydney Ultimo NSW Australia

ISBN: (纸本)9781665404242

There are many possibilities for smart buildings that have well provisioned and managed internet of things (IoT) frameworks where seamless data acquisition from sensors, processing to analytics can bring benefits to vast domains. Specifically, in building management, data captured from sensors, actuators and multiple devices within a building can be analyzed and utilized for resource planning as well as informed services provision while maintaining the security and privacy of IoT data sources and context. To facilitate such a process, a robust framework for acquisition, processing and analysis of data from vast IoT systems is necessary. This is an extremely complex procedure that requires augmentation of multiple computation layers for management of IoT data coupled with privacy preservation capabilities. In this paper, an overview of IoT and the data process flow from acquisition, collection, processing, integration and the technological enablers is presented. In particular this work examines methods proposed in the literature for management of IoT data from acquisition to analytical applications, highlights challenges and opportunities that are still open for research and proposes a privacy preserving computation framework that can be explored for robust processing of IoT data in a smart building ecosystem leading to effective provision of services while maintaining privacy of IoT data sources and context.

关键词： IoT frameworks smart buildings privacy preserving IoT edge computing big data architectures intelligent buildings privacy preserving computing

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