Given the inherent reliance of distributedsystems on concurrent programming, coupled with increased hardware concurrency and diversity, ensuring their reliability, safety, and security without compromising performanc...
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ISBN:
(纸本)9783031753794;9783031753800
Given the inherent reliance of distributedsystems on concurrent programming, coupled with increased hardware concurrency and diversity, ensuring their reliability, safety, and security without compromising performance has become exceedingly challenging. This necessitates scalable verification methods that can accurately capture the behavior of concurrent and distributedsystems while providing robust guarantees of compliance with specific requirements. The Scalable Verification and Validation of Concurrent and distributedsystems (ScaVeri) track is dedicated to presenting and discussing advancements in formal methods tailored to these systems. Emphasizing scalable techniques and models that have been validated through real-world case studies, the track covers subtopics such as generating correct parallel code, compositional verification with assume-guarantee contracts, enhanced analysis for large-scale systems, and combinations of various analysis techniques, collectively aiming to improve the assurance of diverse and complex distributed computing environments.
The proceedings contain 3 papers. The topics discussed include: ECO-LLM: LLM-based edge cloud optimization;toward using representation learning for cloud resource usage forecasting;and MPIrigen: MPI code generation th...
ISBN:
(纸本)9798400706523
The proceedings contain 3 papers. The topics discussed include: ECO-LLM: LLM-based edge cloud optimization;toward using representation learning for cloud resource usage forecasting;and MPIrigen: MPI code generation through domain-specific language models.
Network interfaces play a central role in multicore architectures that use a network-on-chip for communication. Network interface designs have not received much attention in the research community despite this central...
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ISBN:
(纸本)9798350371291;9798350371284
Network interfaces play a central role in multicore architectures that use a network-on-chip for communication. Network interface designs have not received much attention in the research community despite this central role. This paper explores different network interface configurations for a real-time network-on-chip architecture. We evaluate the effects of different FIFO queue organizations on the bandwidth and maximum latency of messages in a time-division multiplexing network-on-chip.
The interaction between deep brain stimulation (DBS) systems and magnetic resonance imaging (MRI) can induce tissue heating in patients. While electromagnetic (EM) simulations can be used to estimate the specific abso...
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ISBN:
(纸本)9798350384734;9798350384727
The interaction between deep brain stimulation (DBS) systems and magnetic resonance imaging (MRI) can induce tissue heating in patients. While electromagnetic (EM) simulations can be used to estimate the specific absorption rate (SAR) values in the presence of an implanted DBS system, they are computationally expensive. To address Ibis drawback, we predict local SAR values in the tips of DBS leads with machine learning based efficient algorithms, specifically XgBoost and deep learning. We significantly outperformed the previous state of the art, and adapted new machine learning models based on Residual networks family as well as XgBoost models. We observed that already extracted limited features are better suited for ensemble learning via XgBoost than deep networks due the small-data regime. Although we conclude that boosting gradient algorithm is more suitable for this non-linear regression problem due to stnictured nature of the data and small data regime, we found that width plays a more critical role than depth in network design and it has a strong potential for future research. Our experimental results, using a dataset of 260 instances that are patient -derived and artificial, reached an outstanding RMSE of 17.8 VV/kg with XgBoost, 78 NV/kg with deep networks, given that the previous study on this problem reached a state-of-the-art root mean square error value (RMSE) of 168 %V/kg.
Incremental graphs that change over time capture the changing relationships of different entities. Given that many real-world networks are extremely large, it is often necessary to partition the network over many dist...
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ISBN:
(纸本)9798350305487
Incremental graphs that change over time capture the changing relationships of different entities. Given that many real-world networks are extremely large, it is often necessary to partition the network over many distributedsystems and solve a complex graph problem over the partitioned network. This paper presents a distributed algorithm for identifying strongly connected components (SCC) on incremental graphs. We propose a two-phase asynchronous algorithm that involves storing the intermediate results between each iteration of dynamic updates in a novel meta-graph storage format for efficient recomputation of the SCC for successive iterations. To the best of our knowledge, this is the first attempt at identifying SCC for incremental graphs across distributed compute nodes. Our experimental analysis on real and synthesized graphs shows up to 2.8x performance improvement over the state-of-the-art by reducing the overall memory utilized and improving the communication bandwidth.
The idea and implementation of a testbed are essen-tial steps in assessing and improving the functionality of wireless systems in real-time scenarios. In this research, we proposed a testbed for establishing a secure ...
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Deciding on appropriate mechanical ventilator management strategies significantly impacts the health outcomes for patients with respiratory diseases. Acute Respiratory Distress Syndrome (ARDS) is one such disease that...
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ISBN:
(纸本)9798350384734;9798350384727
Deciding on appropriate mechanical ventilator management strategies significantly impacts the health outcomes for patients with respiratory diseases. Acute Respiratory Distress Syndrome (ARDS) is one such disease that requires careful ventilator operation to be effectively treated. In this work, we frame the management of ventilators for patients with ARDS as a sequential decision making problem using the Markov decision process framework. We implement and compare controllers based on clinical guidelines contained in the ARDSnet protocol, optimal control theory, and learned latent dynamics represented as neural networks. The Pulse Physiology Engine's respiratory dynamics simulator is used to establish a repeatable benchmark, gather simulated data, and quantitatively compare these controllers. We score performance in terms of measured improvement in established ARDS health markers (pertaining to improved respiratory rate, oxygenation, and vital signs). Our results demonstrate that techniques leveraging neural networks and optimal control can automatically discover effective ventilation management strategies without access to explicit ventilator management procedures or guidelines (such as those defined in the ARDSnet protocol).
Local failover mechanisms are used to achieve fast recovery from link failures in communication networks. These mechanisms are typically implemented using static routing tables at the nodes of a network, only relying ...
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ISBN:
(纸本)9783031744976;9783031744983
Local failover mechanisms are used to achieve fast recovery from link failures in communication networks. These mechanisms are typically implemented using static routing tables at the nodes of a network, only relying on failures of outgoing links, as well as the label of the source and target node of a packet (called s - t-routing). Static failover s- t-routing on undirected graphs has been shown to be able to tolerate at most 2 failures, denoted 2-resilient, with 3-resiliency being impossible without additional rewritable bits in the packet header. In this work, we investigate local failover routing on directed graphs with n nodes and show lower and upper bounds on the number of bits required. Even 1-resilience cannot be achieved on all topologies without additional bits and we prove that 1-resilience can be obtained with inverted right perpendicularlog(n)inverted left perpendicular bits. For k > 1 failures, we show that at least inverted right perpendicularlog(k + 1)inverted left perpendicular bits are necessary, but that k(inverted right perpendicularlog(vertical bar E vertical bar)inverted left perpendicular) bits are sufficient to obtain k-resiliency.
Although LoRa (Long Range) wireless communication technology is most commonly used in the form of LoRaWAN, a single-hop Low Power Wide Area Network (LPWAN) protocol, recent advancements have seen the emergence of mult...
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ISBN:
(纸本)9798331531317;9798331531300
Although LoRa (Long Range) wireless communication technology is most commonly used in the form of LoRaWAN, a single-hop Low Power Wide Area Network (LPWAN) protocol, recent advancements have seen the emergence of multi-hop and mesh LoRa networks. Among these, research on linear LoRa mesh networks for subterranean environments, where traditional LoRaWAN networks face challenges due to limited telecommunication infrastructure, insufficient range, and environmental constraints, is notable. In a linear LoRa mesh network, LoRa repeaters are arranged in a line to provide extended coverage in lengthy environments such as underground mines, pipelines, and tunnels. In this paper, we present a comprehensive analysis of the scalability of these networks, based on a series of simulation experiments conducted using LoRaMeshSim, the first-ever LoRa mesh network simulator, developed by us. We propose optimal selections for LoRa configurations and network properties, including the optimal repeater density, the optimal waiting period in our presented repeater algorithm featuring carrier sensing, and a strategic method of utilizing two frequency channels to enhance network performance. Employing our proposed optimizations, we demonstrate how linear LoRa mesh networks can effectively scale up to support numerous repeaters, end devices, and high-traffic loads.
This paper studies the shuffling phase in a distributed computing model with rate-limited links between nodes. Each node is connected to all other nodes via a noiseless broadcast link with a finite capacity. For this ...
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ISBN:
(纸本)9798350382853;9798350382846
This paper studies the shuffling phase in a distributed computing model with rate-limited links between nodes. Each node is connected to all other nodes via a noiseless broadcast link with a finite capacity. For this network, the shuffling phase is described as a distributed index-coding problem to extend an outer bound for the latter to the distributed computing problem. An inner bound on the capacity region is also established by using the distributed composite-coding scheme introduced for the distributed index-coding problem. We consider some special cases of the distributed computing problem through two examples for which we prove that the inner and outer bounds agree, thereby establishing the capacity regions. We, then, generalize the special cases to any number of nodes and computation loads under certain constraints.
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