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Star based Reachability Analysis of Interval Neural networks 62

Star based Reachability Analysis of Interval Neural Networks

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62nd ieee conference on Decision and Control (CDC)

作者： Bondalakunta, Vishnu Prabhakar, Pavithra Kansas State Univ Dept Comp Sci Manhattan KS 66506 USA Kansas State Univ Dept Comp Sci Comp Sci Manhattan KS 66506 USA

ISBN: (纸本)9798350301243

The paper explores the computation of output reachable sets for Interval Neural networks (INNs) with ReLU activation functions. An INN is a generalization of a Neural network (NN), where the weights and biases are intervals rather than numbers. We propose a novel algorithm for computing precise over-approximations of the output reachable sets for INNs by introducing a novel data structure called interval star set which is a generalized version of the star set. Specifically, when the INN is a traditional NN, our method reduces to the standard star-based verification of NNs. We present experimental results that demonstrate that our method outperforms the existing method based on mixed integer linear programming (MILP) for the problem of INN output reachable set computation.

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Parallel Longest Common SubSequence Analysis In Chapel

Parallel Longest Common SubSequence Analysis In Chapel

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ieee High Performance Extreme Computing Virtual conference (HPEC)

作者： Vahidi, Soroush Schieber, Baruch Du, Zhihui Bader, David A. New Jersey Inst Technol Dept Comp Sci Newark NJ 07102 USA New Jersey Inst Technol Dept Data Sci Newark NJ USA

ISBN: (纸本)9798350308600

One of the most critical problems in the field of string algorithms is the longest common subsequence problem (LCS). The problem is NP-hard for an arbitrary number of strings but can be solved in polynomial time for a fixed number of strings. In this paper, we select a typical parallel LCS algorithm and integrate it into our large-scale string analysis algorithm library to support different types of large string analysis. Specifically, we take advantage of the high-level parallel language, Chapel, to integrate Lu and Liu's parallel LCS algorithm into Arkouda, an open-source framework. Through Arkouda, data scientists can easily handle large string analytics on the back-end high-performance computing resources from the front-end Python interface. The Chapel-enabled parallel LCS algorithm can identify the longest common subsequences of two strings, and experimental results are given to show how the number of parallel resources and the length of input strings can affect the algorithm's performance.

关键词： string algorithms parallel computing Chapel programming language

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Enhancing 5G network Throughput Using Reinforcement Learning

Enhancing 5G Network Throughput Using Reinforcement Learning

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2024 ieee International conference on Communication, Computing and Signal Processing, IICCCS 2024

作者： Adnan, Myasar Mundher Farkhodjonovich, Muydinov Firuzjon Shrivastava, Rohit Bhandari, Anika Aravind, A.R. Sandeep Kumar, S. The Islamic University College Of Technical Engineering Department Of Computers Techniques Engineering Najaf Iraq The Islamic University Of Al Diwaniyah College Of Technical Engineering Department Of Computers Techniques Engineering Al Diwaniyah Iraq Fergana Medical Institute Of Public Health Head Of Educational and Methodological Department Fergana Uzbekistan Ies College of Technology Department of Electronics & Communication Engineering M.P. Bhopal India Chandigarh Group of Colleges Chandigarh Engineering College Department of Computer Application Punjab Mohali India Prince Shri Venkateshwara Padmavathy Engineering College Chennai India Department of Computer and Communication Engineering Karnataka Udupi India

ISBN: (纸本)9798350390759

In this research, RL is proposed as a solution towards achieving the dynamic optimization of 5G network throughput hindered by the complexity of Intersystems environments. To this extent, the optimization problem is formulated and modeled within the framework of Markov Decision Process and the study resorts to techniques from Deep Reinforcement Learning leading to the design of adaptive algorithms that optimise various network parameters in real-time. It uses simulated raw 5G network data and other data open for public usage for training it and the application itself is coded in Python programming language with TensorFlow for implementing different algorithms. As for the performance, it could be seen that the RL-optimized approach is superior to traditional methods and leads to better system performance in terms of throughput, latency, energy efficiency and user satisfaction in a number of scenarios. The study identifies the possibility to apply RL to enable the learning capability of 5G networks in supporting new services and optimizing the network performance. This research finding can be beneficial for the advancement of 5G wireless communication technology by demonstrating the versatility and advantages of utilizing RL in the network. © 2024 ieee.

关键词： Deep reinforcement learning

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Service and network function placement in the edge-cloud continuum

Service and network function placement in the edge-cloud con...

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ieee conference on Standards for Communications and networking (ieee CSCN)

作者： Tsolkas, Dimitris Charsmiadis, Anastastios-Stavros Xenakis, Dionysis Merakos, Lazaros NKUA Dept Informat & Telecommun Athens Greece FOGUS Innovat Serv PC Kaisariani Greece

ISBN: (纸本)9781665476218

The virtualization and containerization technologies have paved the way towards a flexible and fully programmable service provisioning chain over mobile telecommunication infrastructures. On top of those technologies the network slicing concept has emerged;a concept that enables the installation and migration of service and network functions on a compute fabric that spans from the central cloud to distributed far-edge hosts. In this context, the efficient placement of service and network functions in the hosts of the continuum is an open and challenging problem. We formulate this problem as a scheduling process and we analyze its optimal performance through the integer linear programming toolkit. The study revealed interesting insights regarding the impact of sequence constraints (i.e., some functions should be allocated according to a specific order) and host-continuity constraints (i.e., some functions should be allocated in the same cloud host with others) to the overall efficiency of the scheduling.

关键词： network function placement network slicing edge-cloud continuum Integer linear programming

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Adaptive Optimal Control of Nonlinear Systems with Multiple Time-scale Eligibility Traces 62

Adaptive Optimal Control of Nonlinear Systems with Multiple ...

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62nd ieee conference on Decision and Control (CDC)

作者： Rao, Jun Wang, Jingcheng Xu, Jiahui Wu, Shunyu Shanghai Jiao Tong Univ Dept Automat Key Lab Syst Control & Informat Proc Shanghai 200240 Peoples R China

ISBN: (纸本)9798350301243

Adaptive dynamic programming (ADP) is one of the main methods to solve the optimal control problem of nonlinear systems. Eligibility traces are utilized in recent years to reduce the computing burden of the value function, but the existing fixed eligibility trace is difficult to ensure stable convergence especially when facing environmental changes and complex neural network structures. To solve the above issues, a novel off-policy algorithm, T-HDP(lambda) with Multiple Timescale Eligibility Traces (MET), is proposed. By utilizing MET, the new algorithm can adaptively accumulate gradients and include more gradient information, which guides the control faster in the optimal direction. T-step Truncated lambda-returns are utilized to solve the infinite-horizon optimal control problems, and a new importance sampling ratio is designed to correct the value function. Furthermore, the convergence and boundedness of the algorithm are proved. Based on the actor-critic network architecture, the optimal value function and policy are well approximated. Finally, compared with the original algorithm by a simulation example, the proposed algorithm has a faster convergence speed and lower variance.

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Study and Analysis of Wired and Wireless network-on-Chip Using Noxim

Study and Analysis of Wired and Wireless Network-on-Chip Usi...

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2023 ieee International conference on network, Multimedia and Information Technology, NMITCON 2023

作者： Shruthi, R. Shashidhara, H.R. Bhargavi, R. Dharanendra, H.N. Divyashree, N. Rahul Raaj, E. The National Institute of Engineering Department of Ece Mysuru India

ISBN: (纸本)9798350300826

One of the most recent technologies for VLSI design study is network-on-Chip (NoC), an intriguing concept. network metrics rather than the system's physical specifications determine the efficiency of a network-on-chip-based system. One of the primary methods for examining novel ideas in the network-on-Chip space is simulation. The open-source Noxim simulator stands out among the simulators for analyzing and testing novel concepts in NoC architectures and is popular among researchers because it supports wireless technology (Wireless network-on-Chip). Noxim offers straightforward support for input traces, but it is quite constrained in terms of how the system will generally behave by taking different performance parameters over time. The performance of NoC varies along with the change in packet injection rate (PIR) for different routing algorithms and random selection strategy. The study mainly underlines the behavior of XY and DyAD routing algorithms for different traffic patterns for 6x6 mesh topology for wired and wireless interconnects. © 2023 ieee.

关键词： network-on-chip

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Analysis of Vulnerabilities in Satellite Software Bus network Architecture

Analysis of Vulnerabilities in Satellite Software Bus Networ...

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ieee Military Communications conference (MILCOM)

作者： Schalk, Adrian Brodnik, Luke Brown, Dane US Naval Acad Cyber Sci Dept Annapolis MD 21402 USA

ISBN: (纸本)9781665485340

With the rapid expansion of the space industry, there has been a strong push to develop simple, reusable, and easy to deploy satellite system architecture solutions. The space industry may have assumed that the complexity of their systems of systems would make the vulnerability discovery process too difficult for attackers. However, focused research into the design of modern Software-Bus (SB) dependent satellite systems has the ability to reveal numerous vulnerabilities in deployed space system architectures. In particular, our in-depth analysis of NASA's open source core Flight System (cFS) resulted not only in the discovery of various novel vulnerabilities, but also the implementation of several straight-forward, practical exploits. Due to the lack of authentication required to execute commands via the SB as well as the inability to recover from an attack in a robust manner, cFS is vulnerable to a number of attacks through the SB entry point. This paper presents four exploit demonstrations on the unsecured cFS bus architecture, and then provides recommendations on how to secure against these attacks and make a modern satellite system architecture more robust.

关键词： Space network Architecture Software Bus System Architecture network Architecture Cyber System Design Satellite Cyber Security core Flight System Space Data Link Security open Source Architecture

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GOX: Towards a Scalable Graph Database-Driven SDN Controller 8

GOX: Towards a Scalable Graph Database-Driven SDN Controller

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8th ieee International conference on network Softwarization (NetSoft) - network Softwarization Coming of Age - New Challenges and Opportunities

作者： Bannour, Fetia Dumbrava, Stefania Danduran--Lembezat, Alex ENSIIE Evry France SAMOVAR Evry France

ISBN: (纸本)9781665406949

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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Traffic Injection Regulation Protocol Based on Free Time-Slots Requests 29

Traffic Injection Regulation Protocol Based on Free Time-Slo...

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29th ieee International conference on Embedded and Real-Time Computing Systems and Applications, RTCSA 2023

作者： González, Yilian Ribot Nelissen, Geoffrey Tovar, Eduardo CISTER Research Centre ISEP IPP Porto Portugal Eindhoven University of Technology Eindhoven Netherlands

ISBN: (纸本)9798350337860

network-on-Chips (NoCs) have demonstrated be a favorable alternative to conventional bus-based communication architectures for interconnecting programming elements (PEs). However, NoCs consist of numerous shared resources such as routers and links leading to traffic contention and hence packet transmission delays. Existing works rely on various mechanisms, e.g., leaky buckets, to regulate the network bandwidth distribution and reduce contention. However, such bandwidth regulation mechanisms rarely use runtime information to decide which PEs can inject packets in the network. In this paper, we propose a traffic injection regulation protocol where PEs can dynamically request other PEs to relinquish some network bandwidth. The proposed solution prevents starvation and excessive communication delays due to PEs being unable to inject their flits on the network. Moreover, since the proposed solution uses runtime information, it does not waste communication bandwidth. Experimental results show that our solution leads to a more equitable distribution of network bandwidth among PEs compared to leaky bucket-based mechanisms. © 2023 ieee.

关键词： network-on-chip

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Policy-Gradient-Based Reinforcement Learning for Computing Resources Allocation in O-RAN 11

Policy-Gradient-Based Reinforcement Learning for Computing R...

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11th ieee International conference on Cloud networking (CloudNet)

作者： Sharara, Mahdi Pamuklu, Turgay Hoteit, Sahar Veque, Veronique Erol-Kantarci, Melike Univ Paris Saclay Lab Signaux & Syst CNRS Cent Supelec Gif Sur Yvette France Univ Ottawa Sch Elect Engn & Comp Sci Ottawa ON Canada

ISBN: (数字)9781665486279

ISBN: (纸本)9781665486279

open Radio Access network (O-RAN) is a novel architecture aiming to disaggregate the network components to reduce capital and operational costs and open the interfaces to ensure interoperability. In this work, we consider the problem of allocating computing resources to process the data of enhanced Mobile BroadBand (eMBB) users and Ultra-Reliable Low-Latency (URLLC) Users. Supposing the processing of users' frames from different base stations is done in a shared O-Cloud, we model the computing resources allocation problem as an Integer Linear programming (ILP) problem that aims at fairly allocating computing resources to eMBB and URLLC users and optimizing the QoS of URLLC users without neglecting eMBB users. Due to the high complexity of solving an ILP problem, we model the problem using Reinforcement Learning (RL). Our results demonstrate the ability of our RL-based solution to perform close to the ILP solver while having much lower computational complexity. For a different number of open Radio Units (O-RUs), the objective value of the RL agent does not deviate from the ILP objective by more than 6%.

关键词： O-RAN Integer Linear programming Reinforcement Learning Computing Resources Allocation

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