Recent GPU architectures make available numbers of parallel processing units that exceed by orders of magnitude the ones offered by CPU architectures. Whereas programs written using dataflow programming languages are ...
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open Radio Access networks (O-RAN) are transforming telecommunications by shifting from centralized to distributed architectures, promoting flexibility, interoperability, and innovation through open interfaces and mul...
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ISBN:
(数字)9798350368369
ISBN:
(纸本)9798350368376
open Radio Access networks (O-RAN) are transforming telecommunications by shifting from centralized to distributed architectures, promoting flexibility, interoperability, and innovation through open interfaces and multi-vendor environments. However, O-RAN's reliance on cloud-based architecture and enhanced observability introduces significant security and resource management challenges. Efficient resource management is crucial for secure and reliable communication in O-RAN, within the resource-constrained environment and heterogeneity of requirements, where multiple User Equipment (UE) and O-RAN Radio Units (O-RUs) coexist. This paper develops a framework to manage these aspects, ensuring each O-RU is associated with UEs based on their communication channel qualities and computational resources, and selecting appropriate encryption algorithms to safeguard data confidentiality, integrity, and authentication. A Multi-objective Optimization Problem (MOP) is formulated to minimize latency and maximize security within resource constraints. Different approaches are proposed to relax the complexity of the problem and achieve near-optimal performance, facilitating tradeoffs between latency, security, and solution complexity. Simulation results demonstrate that the proposed approaches are close enough to the optimal solution, proving that our approach is both effective and efficient.
This paper develops IC&NEV simulation software based on UML object-oriented programming, Builder design pattern, MATLAB, PostgreSQL and SuMO. By using Python program, the road network document data is preprocessed...
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ISBN:
(数字)9798350361643
ISBN:
(纸本)9798350361650
This paper develops IC&NEV simulation software based on UML object-oriented programming, Builder design pattern, MATLAB, PostgreSQL and SuMO. By using Python program, the road network document data is preprocessed and the road network GIS database is established. Builder provides the Director with an abstract interface for building a product that allows the Director to hide the appearance and structure of a particular product. The simulation program developed in this paper can provide help for the research of optimal control of integrated circuits and dynamic systems of new energy vehicles. Using abstract syntactic expression, the information transfer between TCP/IP interfaces is realized. The iec61499 compliant controller acts as a data server, while the separate GridlAB-D object acts as a client. In addition, based on the open and closed design ideas of UML, this system not only has the function of secondary development, but also is very suitable for the research of multi-vehicle coordination control. The road network model is generated by using openStreetMap editor and JOSM. Compared with manual modeling, this method is faster and more consistent with the actual road network.
Selecting and verifying network paths for packet flows are fundamental for creating secure and efficient networkarchitectures. These processes are essential for detecting and addressing anomalies, misconfigurations, ...
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ISBN:
(数字)9798350380538
ISBN:
(纸本)9798350380545
Selecting and verifying network paths for packet flows are fundamental for creating secure and efficient networkarchitectures. These processes are essential for detecting and addressing anomalies, misconfigurations, or malicious activities, yet they remain challenging to implement effectively, even within a single administrative domain. To support a secure routing framework, it is necessary to: (i) select specific paths for packet flows, enabling "path awareness"; (ii) verify that packets follow the specified routes, ensuring adherence to the routing promise; and (iii) maintain tamper-proof audit records of path verification data. This paper introduces a novel path-aware secure routing approach based on Residue Number System (RNS) primitives, which enables both native path verification and auditability. Our method employs a lightweight multi-signature scheme built on simplified hash chain signatures, leveraging RNS-based native routing mechanisms. These signatures, which provide proofs of packet forwarding, are verified and recorded on a blockchain to ensure data integrity and prevent unauthorised tampering. A P4-based prototype demonstrates that our solution represents a viable hardware implementation for modern programmable switches.
A robust planning model based on source-load cluster division is proposed to address the limitations of the current soft open point (SOP) in replacing only the alternative positions of the tie switches and the dimensi...
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ISBN:
(数字)9798350349030
ISBN:
(纸本)9798350349047
A robust planning model based on source-load cluster division is proposed to address the limitations of the current soft open point (SOP) in replacing only the alternative positions of the tie switches and the dimension disaster caused by arbitrary access node planning. This model is used to optimize the selection of soft switch access positions and capacities in the distribution network. Firstly, a comprehensive cluster division method for multi-objective distribution network is proposed, considering modularity, intra-cluster net power fluctuation, and net power peak fluctuation. Secondly, based on the cluster division, a robust planning model for soft switch distribution is established, with the objective of minimizing the annual comprehensive cost of the distribution network. Thirdly, the second-order cone programming model is transformed into a mixed-integer linear programming model using techniques such as equivalent substitution, polyhedral linearization, and Big-M method. The column and constraint generation algorithm (C&CG) is used to solve the proposed model. Finally, a case study of the distribution system of Taiwan Power Company (TPC) is used to validate the effectiveness of the proposed model, ensuring the economic feasibility of the distribution network planning and construction scheme. According to the calculations, the proposed method can reduce the O&M costs of the distribution system by 23.6% compared to the scenario without planning. Meanwhile, compared to the traditional planning method, the proposed method can reduce the cost of distribution system planning by 5.23%.
This paper proposes an application model of camera object detection to observe the cattle rut through its pose. This research is based on deep neural network method along with transfer learning technique. This paper e...
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In quantitative finance, the standard approach involves predicting stock returns to optimize asset allocation, aiming to maximize returns and minimize risks. This predict-then-optimize method traditionally focuses on ...
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ISBN:
(数字)9798350316537
ISBN:
(纸本)9798350316544
In quantitative finance, the standard approach involves predicting stock returns to optimize asset allocation, aiming to maximize returns and minimize risks. This predict-then-optimize method traditionally focuses on minimizing prediction errors and optimizing a risk-adjusted objective function. Such a dichotomy often leads to suboptimal outcomes due to the misalignment between prediction and optimization goals [1]. In response to these challenges, while end-to-end deep portfolio architectures [2] – [4] have been proposed, their "black box" nature often fails to adapt to rapidly changing market conditions, resulting in inefficiencies and non-explainable outcomes [5].This paper introduces a novel network architecture that aligns the goals of minimizing prediction error with optimizing allocation by integrating a differentiable optimization layer [6]. We applied this architecture to Qlib, an AI-oriented quantitative investment platform, to simulate market environments and perform rigorous backtesting. Our results show significant enhancements in key financial metrics such as cumulative returns and average risk-adjusted objective values, surpassing traditional two-stage ***, we conducted portfolio experiments during the COVID-19 period to emphasize the importance of dynamic constraint adjustment in portfolio optimization and demonstrate our model’s effectiveness compared to end-to-end models.
This paper presents novel deep-learning networkarchitectures for time series forecasting. First, a singular deep gaining knowledge of network architecture is proposed and tested for the usage of the Google tendencies...
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ISBN:
(数字)9798350329773
ISBN:
(纸本)9798350329780
This paper presents novel deep-learning networkarchitectures for time series forecasting. First, a singular deep gaining knowledge of network architecture is proposed and tested for the usage of the Google tendencies dataset as a benchmark. The proposed structure combines 1-dimensional convolution neural networks, recurrent neural networks, and long-term cells to seize and study lengthy-term styles in the time series information. The structure is compared to current deep getting-to-know architectures and is shown to outperform them in phrases of accuracy. Moreover, the proposed structure is applied to a secondary time collection dataset, the COVID-19 confirmed infection dataset, to attain compelling effects. Eventually, an open-source implementation of the proposed architecture is made available for use in addition to research.
Beyond 5G and 6G systems provide significant advances in network architectural design and deployment with the ever-increasing connected devices. In order to address the tremendous growth of cellular traffic, both hard...
Beyond 5G and 6G systems provide significant advances in network architectural design and deployment with the ever-increasing connected devices. In order to address the tremendous growth of cellular traffic, both hard- and software are facing increased scalability and flexibility requirements. Therefore, a comparative study on open-source 5G core network implementations is conducted that includes qualitative as well as quantitative requirements. While the qualitative comparison is based on licensing, programming language, deployment possibilities, and relevance, the qualitative metrics are resource utilization and the Round Trip Time experienced by end-user devices. In order to evaluate these metrics, each of the open-source projects is deployed as service based architecture in a virtual machine/container-based infrastructure. The results indicate implementation benefits and the trade-off between load consumption and latency evaluation.
Nowadays, many software systems are split into loosely coupled microservices only communicating via Application programming Interfaces (APIs) to improve maintainability, scalability, and fault tolerance. However, the ...
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ISBN:
(数字)9798400705021
ISBN:
(纸本)9798350351781
Nowadays, many software systems are split into loosely coupled microservices only communicating via Application programming Interfaces (APIs) to improve maintainability, scalability, and fault tolerance. However, the loose coupling between microservices provides no immediate feedback on breaking API changes, and con-suming services break or exhibit unexpected behavior only after the first actual call to the changed API. Hence, development teams must actively identify and communicate all breaking changes to affected teams to stay compatible. This research addresses this problem with three contributions. First, we identified API evolution strategies and open challenges in practice with an explorative study. Based on the study findings, we formulated two open research directions for evolving publicly accessible APIs, i.e., REpresentational State Transfer (REST) APIs. As the second contribution, we will introduce a REST API change extraction approach to improve the change no-tification accuracy. We plan experiments on open-source projects to evaluate our approach's accuracy and compare it to openapi-diff for structural changes. Third, we plan to investigate methods for automating communication with affected teams, which will then improve the change notification reliability. Finally, we will evaluate the accuracy and reliability of our notifications with a user study.
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