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Exploring the Efficiency of Data-Oblivious Programs

Exploring the Efficiency of Data-Oblivious Programs

引用

IEEE international symposium on Performance Analysis of systems and Software (ISPASS)

作者： Biernacki, Lauren Tiruye, Biniyam Mengist Demissie, Meron Zerihun Andargie, Fitsum Assamnew Reagen, Brandon Austin, Todd Univ Michigan Ann Arbor MI 48109 USA Addis Ababa Univ Addis Ababa Ethiopia NYU New York NY 10003 USA

ISBN: (纸本)9798350397390

Data-oblivious programs have gained popularity due to their application in security, but are often dismissed because of anticipated performance loss. In order to better understand these performance concerns, this paper details the first performance characterization of data-oblivious programs. We study mechanical data-oblivious transformations applied to twenty workloads from the VIP-Bench benchmark suite and find that, overall, performance overheads vary widely, with a geomean slowdown of 7.4x. This variance can be attributed to whether or not the data-oblivious transformations affect the workload's asymptotic complexity. Performance overheads are much lower for the fourteen workloads whose complexity is unaffected, at 1.9x geomean. Further, by reducing control hazards, we find that data-oblivious transformations often result in improved per-instruction performance (e.g., better branch and memory performance) and increase the number of instructions the processor can execute in parallel (e.g., IPC). Leveraging lessons from analyzing these overheads, we study four notably slow data-oblivious workloads and show how algorithmic changes can significantly improve performance-achieving an average 86.4x speedup over the mechanically produced baseline programs. While data-oblivious program execution often incurs overheads, the contributions of this paper show that these overheads can be overcome by compiler and algorithmic optimizations, bringing us closer to achieving efficient and widely-used data-oblivious programs.

关键词： Benchmark testing Data oblivious programming If conversion

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Production Control of a Make-to-Stock System with Non-identical Parallel Production Lines and Lost Sales

Production Control of a Make-to-Stock System with Non-identi...

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international symposium for Production Research, ISPR 2023

作者： Özkan, Sinem Deliktaş, Kerem Can Bulut, Önder Industrial Engineering Department Izmir Democracy University Izmir Turkey Industrial Engineering Department Yaşar University Izmir Turkey

ISBN: (纸本)9783031539909

A production-inventory control problem of a single-item make-to-stock system with non-identical production lines is studied. The item is demanded by customers arriving according to the Poisson process. Unmet demands of incoming customers are lost and lost sales cost occurs. The mentioned production system has multiple and parallel production lines, but these lines are not the same. Hence, some production lines run faster while others run slower. Moreover, each production line is capable to produce the item, and item processing times have an Exponential distribution with different rates. To ease modelling, it is assumed that there are two different production line groups processing the item at different rates. The decision to be taken into account in the management of such a system is the production control decision. It determines when to start production in which production line group. This study contributes to the technical literature on controlling make-to-stock systems by addressing non-identical production lines. A formulation based on dynamic programming is presented and the model is solved with the value iteration algorithm. An extensive numerical study is presented to understand the nature of the production policy. It is shown that the optimal policy is state-dependent according to the numerical results. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

关键词： Dynamic programming

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Anti-Attack Control of Positive Cyber-Physical systems Using Linear programming

Anti-Attack Control of Positive Cyber-Physical Systems Using...

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international symposium on Computer Science and Intelligent Controls (ISCSIC)

作者： Pengcheng Zhu Siyu Zhong Wei Xing Junfeng Zhang School of Information and Communication Engineering Hainan University Haikou China

ISBN: (数字)9798350380286

ISBN: (纸本)9798350380293

This paper investigates the state-feedback and observer-based feedback control for positive cyber-physical systems. A novel positive anti-attack controller is first proposed for the systems by introducing a switched control strategy. By developing observer technique for cyber-physical systems, a positive controller equipped with dynamic output-feedback approach is refined to estimate unavailable output. Under the designed controllers, the positive and stable with $L_{1}$-gain performance are reached. Then, a matrix decomposition method is employed to design observer and controller gains. All presented conditions are described via linear programming. Finally, an illustrative example is given to verify the effectiveness of the proposed design.

关键词： Switches Cyber-physical systems Observers Control systems Linear programming Stability analysis Feedback control Matrix decomposition Thermal stability Intelligent control

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Towards Easy Robot System Integration: Challenges and Future Directions

Towards Easy Robot System Integration: Challenges and Future...

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IEEE/SICE international symposium on System Integration (SII)

作者： Tola, Daniella Madsen, Emil Gomes, Claudio Esterle, Lukas Schlette, Christian Hansen, Casper Larsen, Peter Gorm Aarhus Univ Dept Elect & Comp Engn Aarhus Denmark Univ Southern Denmark Odense Denmark Technicon ApS Hobro Denmark

ISBN: (纸本)9781665445405

The amount of robots in industry is increasing, pushing the need for easier configuration and integration of robots. The cost of robot integration is often larger than the cost of the robots themselves. With the increasing complexity of robotic systems and the tasks they perform, the future of reducing the expenses of robot system integration is significant. In this position paper, we report on some of the main challenges in robot system configuration, and give an overview of the current state-of-the-art of robot system configuration. We briefly look into the configuration of personal computers (PCs) and study how the robot system configuration can be improved inspired by the standards used in the PC area. We conclude with concrete proposals as to what can be done in the future, to make the process of robot system configuration and integration easier and cheaper.

关键词： Industries Costs Service robots System integration programming Microcomputers Proposals

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Fast LiDAR Informed Visual Search in Unseen Indoor Environments

Fast LiDAR Informed Visual Search in Unseen Indoor Environme...

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2025 IEEE/SICE international symposium on System Integration, SII 2025

作者： Gupta, Ryan Morgenstein, Kyle Ortega, Steven Sentis, Luis University of Texas at Austin Department of Aerospace Engineering and Engineering Mechanics AustinTX78712 United States University of Texas at Austin Department of Mechanical Engineering AustinTX78712 United States

ISBN: (纸本)9798331531614

This paper details a system for fast visual exploration and search without prior map information. We leverage frontier based planning with both LiDAR and visual sensing and augment it with a perception module that contextually labels points in the surroundings from wide Field of View 2D LiDAR scans. The goal of the perception module is to recognize surrounding points more likely to be the search target in order to provide an informed prior on which to plan next best viewpoints. The robust map-free scan classifier used to label pixels in the robot's surroundings is trained from expert data collected using a simple cart platform equipped with a map-based classifier. We propose a novel utility function that accounts for the contextual data found from the classifier. The resulting viewpoints encourage the robot to explore points unlikely to be permanent in the environment, leading the robot to locate objects of interest faster than several existing baseline algorithms. Our proposed system is further validated in real-world search experiments for single and multiple search objects with a Spot robot in two unseen environments. Videos of experiments, implementation details and open source code can be found at https://***/view/lives-2024/home. © 2025 IEEE.

关键词： Robot programming

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Static Analysis of Current Limiting Techniques for Accurate Memristor programming

Static Analysis of Current Limiting Techniques for Accurate ...

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IEEE international symposium on Circuits and systems (ISCAS)

作者： Tommaso Addabbo Riccardo Moretti Department of Information Engineering and Mathematics University of Siena Siena Italy

We discuss a novel investigation approach to study current limiting techniques for accurate memristor programming. In detail, referring to the case of the Stanford memristor model, we propose to analyze its programming dynamics adopting a nonlinear static analysis point of view and considering, for the sake of simplicity, the special case of a linear resistive current limiter.

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Learning Self-adaptations for IoT Networks: A Genetic programming Approach 17

Learning Self-adaptations for IoT Networks: A Genetic Progra...

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17th international symposium on Software Engineering for Adaptive and Self-Managing systems (SEAMS)

作者： Li, Jia Nejati, Shiva Sabetzadeh, Mehrdad Univ Ottawa Ottawa ON Canada

ISBN: (纸本)9781450393058

Internet of Things (IoT) is a pivotal technology in application domains that require connectivity and interoperability between large numbers of devices. IoT systems predominantly use a software-defined network (SDN) architecture as their core communication backbone. This architecture offers several advantages, including the flexibility to make IoT networks self-adaptive through software programmability. In general, self-adaptation solutions need to periodically monitor, reason about, and adapt a running system. The adaptation step involves generating an adaptation strategy and applying it to the running system whenever an anomaly arises. In this paper, we argue that, rather than generating individual adaptation strategies, the goal should be to adapt the logic / code of the running system in such a way that the system itself would learn how to steer clear of future anomalies, without triggering self-adaptation too frequently. We instantiate and empirically assess this idea in the context of IoT networks. Specifically, using genetic programming (GP), we propose a self-adaptation solution that continuously learns and updates the control constructs in the data-forwarding logic of SDN-based IoT networks. Our evaluation, performed using open-source synthetic and industrial data, indicates that, compared to a baseline adaptation technique that attempts to generate individual adaptations, our GP-based approach is more effective in resolving network congestion, and further, reduces the frequency of adaptation interventions over time. In addition, we compare our approach against a standard data-forwarding algorithm from the network literature, demonstrating that our approach significantly reduces packet loss.

关键词： Internet of things

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Adaptive Dynamic programming-based Approximate Optimal Control for Collaborative Robot via Quintic Polynomial Planning

Adaptive Dynamic Programming-based Approximate Optimal Contr...

引用

international symposium on Autonomous systems (ISAS)

作者： Bo Dong Jinlong Pan Tianjiao An Chong Wang Bing Ma Department of Control Science and Engineering Changchun University of Technology Changchun China

ISBN: (数字)9798350363173

ISBN: (纸本)9798350363180

In this paper, we investigate adaptive dynamic programming-based quintic polynomial trajectory planning and optimal tracking control for collaborative robotic systems. According to polynomial interpolation, a quintuple polynomial trajectory planning method is proposed, which solves the problems of non-smooth angular velocity changes and jumps in acceleration with cubic polynomial interpolation. In addition, the optimal control strategy is solved by adaptive dynamic programming. Lyapunov functions are introduced to prove the stability of the control system. At last, the simulation results verify the truth of the above theory.

关键词： Interpolation Trajectory planning Robot kinematics Neural networks Optimal control Collaboration Collaborative robots

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ST4MP: A Blueprint of Multiparty Session Typing for Multilingual programming 11th

ST4MP: A Blueprint of Multiparty Session Typing for Multilin...

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11th international symposium on Leveraging Applications of Formal Methods, Verification and Validation

作者： Jongmans, Sung-Shik Proenca, Jose Open Univ Netherlands Heerlen Netherlands NWO I Ctr Wiskunde & Informat CWI Amsterdam Netherlands Polytech Inst Porto ISEP CISTER Porto Portugal

ISBN: (纸本)9783031198489;9783031198496

Multiparty session types (MPST) constitute a method to simplify construction and analysis of distributed systems. The idea is that well-typedness of processes at compile-time (statically) entails deadlock freedom and protocol compliance of their sessions of communications at execution-time (dynamically). In practice, the premier approach to apply the MPST method in combination with mainstream programming languages has been based on API generation. However, existing MPST tools support only unilingual programming (homogeneity), while many real-world distributed systems are engineered using multilingual programming (heterogeneity). In this paper, we present a blueprint of ST4MP: a tool to apply the MPST method in multilingual programming, based on API generation.

关键词： Blueprints

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ML-DSP: Machine Learning-Assisted Dynamic Spectrum Partitioning in Elastic Optical Networks 17

ML-DSP: Machine Learning-Assisted Dynamic Spectrum Partition...

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17th IEEE international Conference on Advanced Networks and Telecommunications systems, ANTS 2023

作者： Barbhuiya, Dilwar Hussain Deka, Sanjib K. Chatterjee, Bijoy Chand Sarma, Nityananda Tezpur University Department of Cse Assam India South Asian University New Delhi India

ISBN: (纸本)9798350307672

The efficiency of elastic optical networks (EONs) can be improved if services are provisioned based on traffic patterns and dynamic reconfiguration of network resources, reducing network expenses by cutting down on wasteful over-provisioning of network resources. Recently, there have been advancements in using machine learning (ML) in EONs to enable automated operations. This paper proposes an ML-assisted dynamic spectrum partitioning-based allocation scheme, named ML-DSP, for EONs to suppress blocking performance. The ML model predicts the request pattern of each source-destination pair in the network for each time interval. An integer linear programming (ILP) is formulated to optimally partition the spectrum into different partitions for each demand type using the ML prediction to enhance the resource utilization. When ILP is not tractable due to scalability, we introduce a heuristic for partitioning the spectrum. The first-last fit (FLF) spectrum allocation policy is used to allocate the connection requests. The simulation results indicate that ML-DSP outperforms the conventional static partitioning-based scheme that uses the first fit allocation policy in terms of blocking ratio, fairness, and spectrum time utilization ratio. © 2023 IEEE.

关键词： Integer programming

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