Jointly choosing a functional split of the protocol stack and placement of network functions in a virtualized RAN is critical to efficiently using the access network resources. This problem ...represents the latest advancement in 5G networks research, which involves the challenge of optimal choosing simultaneously the virtualized functions placement, routing (considering latency and throughput requirements), and resource usage (considering vRAN centralization). In this letter, we solve the problem as a Mixed-Integer Linear Programming (MILP) problem, in which is possible up to two functional splits per base station, there is a generic set of viable next-generation RAN configurations, and vRAN functions can be flexibly positioned in the computing resources. In this formulation, we aim to minimize the computing resources and maximize the centralization of vRAN functions. Our contribution is to consider splittable flows between vRAN functions that improve the vRAN efficiency regarding computing resource usage, network resources usage, and vRAN centralization. We illustrate the benefits of our flexible approach by evaluating its performance by employing functional splits recommended by O-RAN specifications.
Fifth-generation (5G) networks enable a variety of use cases that require differentiated connectivity, e.g., Ultra-Reliable and Low-Latency Communications (URLLC), enhanced Mobile Broadband (eMBB), ...and massive Machine Type Communication (mMTC). To explore the full potential of these use cases, it is mandatory to understand the communication along with the 5G network segments and architecture components. User Equipment (UE), Radio Access Network (RAN), and 5G Core (5GC) are the main components that support these new network concepts and paradigms. 3rd Generation Partnership Project has recently published Release 16, including the protocols used to communicate between RANs and 5GC, i.e., Non-Access Stratum (NAS) and NG Application Protocol (NGAP). The main goal of this work is to present a comprehensive tutorial about NAS and NGAP specifications using a didactic and practical approach. The tutorial describes the protocol stacks and aspects of the functionality of these protocols in 5G networks, such as authentication and identification procedures, data session establishment, and resource allocation. Moreover, we review the message flows related to these protocols in UE and Next Generation Node B (gNodeB) registration. To illustrate the concepts presented in the tutorial, we developed the my5G Tester: a 5GC tester that implements NAS and NGAP for evaluating three open-source 5GC projects using a black-box testing methodology.
•Load balancing strategies are needed to improve performance, and make effective use of the network capillarity.•The unfairness in the path length caused by the load balancing has little effect in ...general.•Our exact approach is a valuable tool for evaluating heuristic solutions.
This paper presents a bi-objective network flow routing problem regarding network load balancing and flow path length. The problem is formulated within the integer programming framework and an exact and polynomial approach based on the ϵ-constraint technique is presented. In each iteration, our algorithm solves a single-objective linear integer programming subproblem. The goal of our approach is to obtain a minimal complete set of Pareto-optimal solutions. Our proposal was evaluated through several computational experiments, which included grid and random networks. The random topology was generated by the Barabási–Albert model and the settings of the network flows defined here are those commonly used in wireless sensor networks and wireless mesh networks. The analysis of the computational results provide a decision maker with valuable information about which factors most affect the solutions, for example, the smallest and largest bottleneck, the size of increment in the shortest path of the last Pareto-optimal solution and the difference between the path lengths of the first and last Pareto-optimal solutions generated.
The effect of the Chevron angle on inner flow structures within plate and shell heat exchangers (PSHE) has been determined for low, intermediate, and high pressure drop channels. Local flow ...statistics within PSHE channels have been quantified by experiments at Reynolds number 3450 in transparent test sections with 15/15°, 15/45° and 45/45° Chevron angles with the aid of particle tracking velocimetry. Velocity vectors projected onto the channel frontal view derived by straightforward interpolations of consecutive positions of a particle trajectory have been found to yield the mean flow characteristics. Particle trajectories at low Chevron angles resemble longitudinal wavy flow, whereas they preferentially follow the corrugation direction in angles higher than 45°. For the 15/45° configuration, there is lack of symmetry regarding the vertical velocity component about the heat exchanger central plane. Flow recirculation characterizes the outlet, and its intensity increases with decreasing Chevron angles. The ratios of Fanning friction factors for 15/15° and 15/45°, and for 15/15° and 45/45° are 1.35 and 2.24, respectively. The non-uniform velocity field across the PSHE channel affects the Nusselt number homogeneity. For channels with 45/45° Chevron angles, it can be 80% higher than the average Nusselt number at the channel center, whereas it can be 80% lower near the channel boundaries.
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Dostopno za:
BFBNIB, DOBA, GIS, IJS, IZUM, KILJ, KISLJ, NUK, PILJ, PNG, SAZU, UILJ, UKNU, UL, UM, UPUK
The open radio access network (O-RAN) architecture is consolidating the concept of software-defined cellular networks beyond 5G networks, mainly through the introduction of the near-real-time radio ...access network (RAN) intelligent controller (Near-RT RIC) and the xApps. The deployment of the Near-RT RICs and the assignment of RAN nodes to the deployed RICs play a crucial role in optimizing the performance of O-RANs. In this paper, we develop a robust optimization framework for joint RIC deployment and assignment, considering the uncertainty in user locations. Specifically, our contributions are as follows. First, we develop <inline-formula> <tex-math notation="LaTeX">\text{C}^{3}\text{P}^{2} </tex-math></inline-formula>, a robust static joint RIC placement and RAN node-RIC assignment scheme. The objective of <inline-formula> <tex-math notation="LaTeX">\text{C}^{3}\text{P}^{2} </tex-math></inline-formula> is to minimize the number of RICs needed to control all RAN nodes while ensuring that the response time to each RAN node will not exceed <inline-formula> <tex-math notation="LaTeX">\delta </tex-math></inline-formula> milliseconds with a probability greater than <inline-formula> <tex-math notation="LaTeX">\beta </tex-math></inline-formula>. Second, we develop CPPA, a robust joint RIC placement and adaptive RAN node-RIC assignment scheme. In contrast to <inline-formula> <tex-math notation="LaTeX">\text{C}^{3}\text{P}^{2} </tex-math></inline-formula>, CPPA enjoys a recourse capability, where the RAN node-RIC assignment adapts to the variations in the user locations. We use chance-constrained stochastic optimization combined with several linearization techniques to develop a mixed-integer linear (MIL) formulation for <inline-formula> <tex-math notation="LaTeX">\text{C}^{3}\text{P}^{2} </tex-math></inline-formula>. Two-stage stochastic optimization with recourse, combined with several linearization techniques, is used to develop an MIL formulation for CPPA. The optimal performance of <inline-formula> <tex-math notation="LaTeX">\text{C}^{3}\text{P}^{2} </tex-math></inline-formula> and CPPA has been examined under various system parameter values. Furthermore, sample average approximation has been employed to design efficient approximate algorithms for solving <inline-formula> <tex-math notation="LaTeX">\text{C}^{3}\text{P}^{2} </tex-math></inline-formula> and CPPA. Our results demonstrate the robustness of the proposed stochastic resource allocation schemes for O-RANs compared to existing deterministic allocation schemes. They also show the merits of adapting the allocation of resources to the network uncertainties compared to statically allocating them.
The Nπ^{0}π^{0} decays of positive-parity N^{*} and Δ^{*} resonances at about 2 GeV are studied at ELSA by photoproduction of two neutral pions off protons. The data reveal clear evidence for several ...intermediate resonances: Δ(1232), N(1520)3/2^{-}, and N(1680)5/2^{+}, with spin parities J^{P}=3/2^{+}, 3/2^{-}, and 5/2^{+}. The partial wave analysis (within the Bonn-Gatchina approach) identifies N(1440)1/2^{+} and the N(ππ)_{S wave} (abbreviated as Nσ here) as further isobars and assigns the final states to the formation of nucleon and Δ resonances and to nonresonant contributions. We observe the known Δ(1232)π decays of Δ(1910)1/2^{+}, Δ(1920)3/2^{+}, Δ(1905)5/2^{+}, Δ(1950)7/2^{+}, and of the corresponding spin-parity series in the nucleon sector, N(1880)1/2^{+}, N(1900)3/2^{+}, N(2000)5/2^{+}, and N(1990)7/2^{+}. For the nucleon resonances, these decay modes are reported here for the first time. Further new decay modes proceed via N(1440)1/2^{+}π, N(1520)3/2^{-}π, N(1680)5/2^{+}π, and Nσ. The latter decay modes are observed in the decay of N^{*} resonances and at most weakly in Δ^{*} decays. It is argued that these decay modes provide evidence for a 3-quark nature of N^{*} resonances rather than a quark-diquark structure.
Network Slicing (NS) is an essential technique extensively used in 5G networks computing strategies, mobile edge computing, mobile cloud computing, and verticals like the Internet of Vehicles and ...industrial IoT, among others. NS is foreseen as one of the leading enablers for 6G futuristic and highly demanding applications since it allows the optimization and customization of scarce and disputed resources among dynamic, demanding clients with highly distinct application requirements. Various standardization organizations, like 3GPP's proposal for new generation networks and state-of-the-art 5G/6G research projects, are proposing new NS architectures. However, new NS architectures have to deal with an extensive range of requirements that inherently result in having NS architecture proposals typically fulfilling the needs of specific sets of domains with commonalities. The Slicing Future Internet Infrastructures (SFI2) architecture proposal explores the gap resulting from the diversity of NS architectures target domains by proposing a new NS reference architecture with a defined focus on integrating experimental networks and enhancing the NS architecture with Machine Learning (ML) native optimizations, energy-efficient slicing, and slicing-tailored security functionalities. The SFI2 architectural main contribution includes the utilization of the slice-as-a-service paradigm for end-to-end orchestration of resources across multi-domains and multi-technology experimental networks. In addition, the SFI2 reference architecture instantiations will enhance the multi-domain and multi-technology integrated experimental network deployment with native ML optimization, energy-efficient aware slicing, and slicing-tailored security functionalities for the practical domain.
Quasifree photoproduction of eta mesons off nucleons bound in the deuteron has been measured with the CBELSA/TAPS detector for incident photon energies up to 2.5 GeV at the Bonn ELSA accelerator. The ...eta mesons have been detected in coincidence with recoil protons and recoil neutrons, which allows a detailed comparison of the quasifree n(gamma,eta)n and p(gamma,eta)p reactions. The excitation function for eta production off the neutron shows a pronounced bumplike structure at W=1.68 GeV (E{gamma} approximately 1 GeV), which is absent for the proton.
Network slicing (NS) is becoming an essential element of service management and orchestration in communication networks, starting from mobile cellular networks and extending to a global initiative. ...NS can reshape the deployment and operation of traditional services, support the introduction of new ones, vastly advance how resource allocation performs in networks, and notably change the user experience. Most of these promises still need to reach the real world, but they have already demonstrated their capabilities in many experimental infrastructures. However, complexity, scale, and dynamism are pressuring for a Machine Learning (ML)-enabled NS approach in which autonomy and efficiency are critical features. This trend is relatively new but growing fast and attracting much attention. This article surveys Artificial Intelligence-enabled NS and its potential use in current and future infrastructures. We have covered state-of-the-art ML-enabled NS for all network segments and organized the literature according to the phases of the NS life cycle. We also discuss challenges and opportunities in research on this topic.
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