In recent years, with the rapid development of the electric vehicle industry, the optimal scheduling problem for electric vehicles for corporate attendance has become a research focus. This paper establishes a multi-o...
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Serverless computing enables a new way of building and scaling cloud applications by allowing developers to write fine-grained functions. The execution duration of a cloud function is typically short, usually ranging ...
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A cascaded network represents a classic scaling-out model in traditional electrical switching networks. Recent proposals have integrated optical circuit switching at specific tiers of these networks to reduce power co...
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A cascaded network represents a classic scaling-out model in traditional electrical switching networks. Recent proposals have integrated optical circuit switching at specific tiers of these networks to reduce power consumption and enhance topological flexibility. Utilizing a multi-tiered cascaded optical circuit switching network is expected to extend the advantages of optical circuit switching further. The main challenges fall into two categories. First, an architecture with sufficient connectivity is required to support varying workloads. Second, the network reconfiguration is more complex and necessitates a low-complexity scheduling algorithm. In this work, we propose COCSN, a multi-tiered cascaded optical circuit switching network architecture for data center. COCSN employs wavelength-selective switches that integrate multiple wavelengths to enhance network connectivity. We formulate a mathematical model covering lightpath establishment, network reconfiguration, and reconfiguration goals, and propose theorems to optimize the model. Based on the theorems, we introduce an over-subscription-supported wavelength-by-wavelength scheduling algorithm, facilitating agile establishment of lightpaths in COCSN tailored to communication demand. This algorithm effectively addresses scheduling complexities and mitigates the issue of lengthy WSS configuration times. Simulation studies investigate the impact of flow length, WSS reconfiguration time, and communication domain on COCSN, verifying its significantly lower complexity and superior performance over classical cascaded networks.
Suspension-based locks are widely used in real-time systems to coordinate simultaneous accesses to exclusive shared resources. Although suspension-based locks have been well studied for sequential real-time tasks, lit...
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Suspension-based locks are widely used in real-time systems to coordinate simultaneous accesses to exclusive shared resources. Although suspension-based locks have been well studied for sequential real-time tasks, little work has been done on this topic for parallel real-time tasks. This article for the first time studies the problem of how to extend existing sequential-task locking protocols and their analysis techniques to the parallel task model. More specifically, we extend two locking protocols OMLP and OMIP, which were designed for clustered scheduling of sequential real-time tasks, to federated scheduling of parallel real-time tasks. We present corresponding blocking analysis techniques, and develop path-oriented techniques to analyze and count blocking time. Schedulability tests with different efficiency and accuracy are further developed. Experiments are conducted to evaluate the performance of our proposed approaches against the state-of-the-art.
Compared to industrial wired networks, 5G can improve device mobility and reduce the cost of networking. However, the real-time performance and reliability of 5G new radio (NR) still need to be improved to satisfy ind...
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Compared to industrial wired networks, 5G can improve device mobility and reduce the cost of networking. However, the real-time performance and reliability of 5G new radio (NR) still need to be improved to satisfy industrial applications' requirements. In factories, the main factor that affects the performance of 5G NR is the unstable signal quality caused by high temperatures and metal. Although assigning dedicated resources to all transmissions and retransmissions is an effective method to improve the performance of 5G NR, the unstable signal quality causes the resources required for retransmissions to be uncertain. To address the problem, we introduce the mixed-criticality task model to 5G NR. When high-criticality packets cannot be transmitted, they are allowed to preempt the resources shared with low-criticality packets. The mixed-criticality scheduling problem of 5G NR is NP-hard. We formulate it as an optimization modulo theories (OMT) specification and propose a scheduling algorithm based on bin packing methods to make 5G NR satisfy industrial applications' requirements. Finally, we conduct extensive evaluations based on an industrial 5G testbed and random test cases. The evaluation results indicate that our algorithm makes communication reliability greater than 99.9% on unlicensed spectrum, and for most test cases, our algorithm is close to optimal solutions.
The rapid development and deployment of the Cellular V2X (C-V2X) require a highly reliable support system for many vehicular key applications. However, the current standard sensing-based semi-persistent scheduling (SB...
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The rapid development and deployment of the Cellular V2X (C-V2X) require a highly reliable support system for many vehicular key applications. However, the current standard sensing-based semi-persistent scheduling (SB-SPS) protocol yields poor performance in terms of reliability, due to the hidden terminal problem and the half-duplex issue. In this paper, we propose a reliable self-adaptive MAC protocol for C-V2X Mode 4 (autonomous sidelink). It utilizes frame information and RSSI to exclusively scheduling resource blocks in two-hop neighbors, and dynamically adjusts scheduling and frame length according to changes of the network environment. Simulation results show that the proposed protocol achieves significantly higher PDR and lower number of the packet collisions than SB-SPS and IEEE 802.11p.
Aiming at the dynamic flexible scheduling problem in the integrated installation of large-scale laser devices, a deep learning rule acquisition method based on artificial neural network is proposed. Firstly, the typic...
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Aiming at flexible job shop scheduling, a multi-objective optimization model was established to minimize the maximum completion time, total machine load and total carbon emission. In the traditional Jaya algorithm, th...
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In the scenarios of social governance, it often requires real-time handling of various unexpected events, which usually involves collaboration among multiple entities. The keys to this task are real-time action and th...
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The performance of multi-core transactional systems is a well-studied area, with the ultimate goal of optimizing the balance between high concurrency and the appearance of serial execution. In recent years, partitioni...
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