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Microglial modulation of neuronal network function and plasticity

JOURNAL OF NEUROPHYSIOLOGY 2025年第2期133卷 661-680页

作者： Pena-Ortega, Fernando Univ Nacl Autonoma Mexico Inst Neurobiol Dept Neurobiol Desarrollo & Neurofisiol Juriquilla Mexico

Microglia are the resident immune cells of the central nervous system (CNS), which have been classically viewed as involved in CNS responses to damage and tissue repair. However, microglia are constantly sensing neuronal network activity and changes in the CNS milieu, establishing complex state-dependent microglia-neuron interactions that impact their functions. By doing so, microglia perform a wide range of physiological roles, including brain homeostasis maintenance, control of neural connectivity, network function modulation, as well as functional and morphological plasticity regulation in health and disease. Here, the author reviews recent evidence of the modulations induced by microglia, a highly heterogeneous cell type, on synaptic and intrinsic neuronal properties, and on neuronal network patterns during perinatal development and adulthood. The reviewed evidence clearly indicates that microglia are important, if not essential, for brain function and plasticity in both health and disease.

关键词： intrinsic properties microglia network function plasticity synapse

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FlexNF: Flexible network function Orchestration for Scalable On-Path Service Chain Serving

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IEEE-ACM TRANSACTIONS ON networkING 2024年第3期32卷 2026-2041页

作者： Xiao, Jingyu Zuo, Xudong Li, Qing Zhao, Dan Zhao, Hanyu Jiang, Yong Sun, Jiyong Chen, Bin Liang, Yong Li, Jie Tsinghua Shenzhen Int Grad Sch Shenzhen 518055 Peoples R China Peng Cheng Lab Shenzhen 518066 Peoples R China China Mobile Commun Grp Guangdong Co Ltd Guangzhou 510030 Guangdong Peoples R China

Programmable Data Plane (PDP) has been leveraged to offload network functions (NFs). Due to its high processing capability, the PDP improves the performance of NFs by more than one order of magnitude. However, the coarse-grained NF orchestration on the PDP makes it hard to fulfill the dynamic service chain demands and unreasonable network function deployment causes long end-to-end delays. In this paper, we propose the Flexible network function (FlexNF) deployment on the PDP. First, we design an NF Selection Framework, leveraging the service selection label and re-entering operations for flexible NF orchestration. Second, to support runtime NF reconfiguration to meet the dynamic flow demands, we propose the Per-Flow On-Demand servicing mechanism, where one Match-Action Table with multiple mixed NFs works as different NFs for different flows. Third, to ensure the QoS of flows, on the one hand, we design an SP-aware NF Placement Algorithm to find a near-optimal placement solution that accommodates peak traffic volume while minimizing the overall routing path lengths of all the requests, on the other hand, we design a Two-Stage Service Path Construction Algorithm to provide on-path service while considering load balancing. We implement 15 types of network functions on the P4 switch, based on which we construct the comprehensive experiments. FlexNF reduces the traffic delay by 42.6% while increasing the service chain acceptance rate by five times compared with current solutions. Besides, when switching functions, the FlexNF improves the throughput by 2.04Gbps and reduces the packet loss by 8.269% compared with current solutions.

关键词： Switches Noise measurement Delays Routing Throughput Heuristic algorithms Hardware Service chain network function programmable data plane

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AI/ML-Based IDS as 5G Core network function in the Control Plane for IP/non-IP CIoT Traffic 49

AI/ML-Based IDS as 5G Core Network Function in the Control P...

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49th Conference on Local Computer networks

作者： Tan Nhat Linh Le Salem, Boussad Ait Appadoo, Dave Aitsaadi, Nadjib Du, Xiaojiang Univ Paris Saclay UVSQ DAVID F-78035 Versailles France Paris Pantheon Assas Univ EFREI Res Lab F-94800 Villejuif France Stevens Inst Technol Hoboken NJ 07030 USA

ISBN: (纸本)9798350388015;9798350388008

In this paper, we design and implement an Intrusion Detection System (IDS) within the 5G core network, which is capable of inspecting both IP and non-IP data flows. By leveraging the Access and Mobility Management function (AMF) network function (NF) communication service, our IDS can analyze all Cellular Internet of Things (CIoT) data traffic flowing across both the User and Control Planes (UP and CP), enabling the detection of malicious activities originating from or targeting IoT networks. Our proposal is aligned with the 3GPP Release 17 (R17) standard and makes use of predefined functionalities to ensure compliance. Our proposal is non-intrusive and does not interfere with the core network's usual processes based on existing Service Based Interfaces (SBI). Additionally, we demonstrate that the classification of a data packet as malicious or benign is context-dependent using AI/ML Transformer Encoder architectures. We implement and integrate our proposed 5G-CIoT IDS as a network function inside the 5G Amarisoft platform for extensive experimentation. To evaluate the models' performance, we train our models with different categories of safe and malicious generated traffic and apply them to an emulated realistic scenario. We obtained a very promising result.

关键词： CIoT IDS 3GPP 5GC network function ML/AI

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Demo: Enhancing network Performance based on 5G network function and Slice Load Analysis 24

Demo: Enhancing Network Performance based on 5G Network Func...

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24th IEEE International Symposium on a World of Wireless, Mobile and Multimedia networks (WoWMoM)

作者： Ferreira, Rui Fonseca, Joao Silva, Joao Tendulkar, Mayuri Duarte, Paulo Araujo, Marco Barbosa, Raul Mendes, Bruno Goes, Adriano Capgemini Engn Porto Portugal Capgemini Engn Bengaluru India Univ Beira Interior Covilha Portugal Univ Aveiro Aveiro Portugal Inst Telecomunicacoes Aveiro Portugal

ISBN: (纸本)9798350331653

The Fifth Generation Mobile networks has transformed the paradigm of mobile network communications. In Beyond Fifth Generation networks networks, Machine Learning (ML) and Artificial Intelligence (AI) are crucial components, optimizing network resource management to improve the network performance as well as end-users Quality of Service while lowering the network operating costs. This work makes use of an End-to-End 5G architecture to validate three demonstrations: 1) Radio Access network monitoring using a Flexible RIC's xApp;2) 5G Core network's metrics collection via Capgemini Engineering's network Data Analytics function;3) Analysis of the Core network's collected data to predict network function load and network Slice Instance load through the Capgemini Engineering's NetAnticipate AI/ML engine.

关键词： 5G 5G Core network RAN Artificial Intelligence Machine Learning Monitoring NetAnticipate network Slicing network function

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RoNS: Robust network function services in clouds

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COMPUTER networkS 2022年 215卷 1页

作者： Tu, Huaqing Zhao, Gongming Xu, Hongli Zhao, Yangming Qiu, Yuhang Huang, Liusheng Univ Sci & Technol China Sch Comp Sci & Technol Hefei 230027 Anhui Peoples R China

In multi-tenant clouds, the traffic of tenants (e.g., enterprises) needs to be processed by network functions (NFs), for security and business logic issues. Due to potential hardware failures and software errors, NFs may break down. When encountering NF failures, we should consider two critical requirements for maintaining cloud robustness: limited influence scope and fast failure recovery. Without considering these two requirements, prior works based on deploying backup NF instances may result in large influence scope and long recovery time when a failure occurs. To bridge the gap, this paper investigates how to build robust network function services (RoNS) in multi-tenant clouds. Specifically, RoNS limits the number of tenants that each NF instance will serve so as to control the influence scope of an NF failure, and schedule requests with the help of agents designed in the data plane to achieve fast failure recovery. This is however a difficult undertaking. To solve this problem, RoNS takes a two-phase approach: NF instance allocation and tenant request scheduling. For NF instance allocation, we propose an efficient algorithm with bounded approximation factors based on the randomized rounding method. For tenant request scheduling, we present a primal-dual-based algorithm with a superior competitiveness ratio to solve it. We implement RoNS on a real testbed for experimental studies and use simulations for large-scale investigation. Both experiment results and simulation results show the superior performance of the proposed algorithms compared with other alternatives. For example, RoNS can cut down the number of affected tenants by 60%, and reduce recovery delay from 1170 ms to 316 ms on average, compared with existing failure recovery mechanisms based on deploying backup instances.

关键词： network function Failure Fast recovery Clouds

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FlexNF: Flexible network function Orchestration on the Programmable Data Plane 29

FlexNF: Flexible Network Function Orchestration on the Progr...

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29th IEEE/ACM International Symposium on Quality of Service (IWQOS)

作者： Zhao, Hanyu Li, Qing Duan, Jingpu Jiang, Yong Liu, Kai Tsinghua Univ Tsinghua Berkeley Shenzhen Inst Shenzhen Peoples R China Southern Univ Sci & Technol Shenzhen Peoples R China Peng Cheng Lab Shenzhen Peoples R China

ISBN: (纸本)9781665414944

Recently, Programmable Data Plane (PDP) has been leveraged to offload network functions (NFs). Due to its high processing capabilities, programmable data plane can improve the performance of NFs to more than one order of magnitude. However, the coarse-grained NF orchestration granularity on the PDP makes it hard to fulfill the dynamic service chain demands. In this paper, we propose the Flexible network function (FlexNF) Deployment on the programmable data plane. We first design an NF Selection Framework which leverages labels and the pipeline re-enter operation to support Selective Serving Mechanism for flexible NF orchestration. We then design a two-stage service path construction algorithm to provide on-path service based on SSM with load balancing taken into account. We implement 7 types of real network functions in the commodity P4 switch, based which we construct the comprehensive experiments. The results show that FlexNF can reduce the traffic routing delay by about 42.6% while increasing service chain acceptance rate by 5 times compared with current solutions.

关键词： Service Chain network function Programmable Data Plane

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Service Chaining for Hybrid network function

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IEEE TRANSACTIONS ON CLOUD COMPUTING 2019年第4期7卷 1082-1094页

作者： Huang, Huawei Guo, Song Wu, Jinsong Li, Jie Univ Aizu Aizu Wakamatsu Fukushima 9658580 Japan Hong Kong Polytech Univ Dept Comp Kowloon Hong Kong Peoples R China Univ Chile Santiago 8330015 Chile Univ Tsukuba Tennodai 3058571 Japan

In the Service-function-Chaining (SFC) enabled networks, various sophisticated policy-aware network functions, such as intrusion detection, access control and unified threat management, can be realized in either physical middleboxes or virtualized network function (VNF) appliances. In this paper, we study the service chaining towards the hybrid SFC clouds, where both physical appliances and VNF appliances provide services collaboratively. In such hybrid SFC networks, the challenge is how to efficiently steer the service chains for traffic demands while matching their individual policy chains concurrently such that a utility associated with the total admitted traffic rate and the induced overheads can be maximized. We find such problem has not been well solved so far. To this end, we devise a Markov Approximation (MA) based algorithm. The approximation property of the proposed algorithm is also proved. Extensive evaluation results show that the proposed MA algorithm can yield near-optimal solutions and outperform other benchmark algorithms significantly.

关键词： Service function chaining network function middlebox NFV SDN traffic steering Markov approximation

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Implementing a Smart SDN Switch with LISP Control Plane as network function 5

Implementing a Smart SDN Switch with LISP Control Plane as N...

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5th IEEE International Conference on Cloud networking (IEEE CloudNet)

作者： Cianfrani, Antonio Samii, Manuele Mohseni Pour Lo Bascio, David Polverini, Marco Sapienza Univ Rome Dept Informat Engn Elect & Telecommun DIET Via Eudossiana 18 I-00184 Rome Italy

ISBN: (纸本)9781509050932

Software Defined network (SDN) is considered as the key paradigm for the development of future networks, but there is still a lack of operational solutions, especially for an Internet Service Provider environment. In this work we propose the idea of an advanced SDN device, referred to as Smart SDN Forwarding Device (SSFD), able to implement network functions (NFs) on top of the Data Plane: in this way, it will be possible to realize hybrid SDN/IP networks and to reduce the load on the SDN Controller. We also provide a prototype, realized by means of open source software, that represents a first step toward the deployment of an operational device. The performance evaluation realized connecting the SSFD prototype to the experimental LISP network, shows that its performance are very close to the ones of a legacy device: the delay introduced for the control level operations is limited and negligible from an user perspective.

关键词： LISP network function Software Defined network

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Serpens: A High Performance FaaS Platform for network functions

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IEEE TRANSACTIONS ON PARALLEL AND DISTRIBUTED SYSTEMS 2023年第8期34卷 2448-2463页

作者： Yu, Heng Zhang, Han Shen, Junxian Geng, Yantao Wang, Jilong Miao, Congcong Xu, Mingwei Tsinghua Univ Inst Network Sci & Cyberspace Beijing 100084 Peoples R China Zhongguancun Lab Beijing 100190 Peoples R China Quan Cheng Lab Jinan 250103 Peoples R China Tencent Beijing 100193 Peoples R China

More and more enterprises deploy applications on function-as-a-Service (FaaS) platforms to improve resource efficiency and save monetary costs. network functions (NFs) suffer from staggered peaks of traffic patterns and could benefit from fine-grained resource multiplexing in FaaS platform. However, naively exploring existing FaaS platforms to support NFs can introduce significant performance overheads in three aspects, including slow instance startup, remote state access for NFs, and costly packet delivery between NFs. To address these problems, we propose Serpens, a high performance FaaS platform for NFs. First, Serpens proposes a reusable NF runtime design to slash instance startup overhead. Second, Serpens designs a novel state management mechanism to support local state access. Third, Serpens introduces an advanced service chaining approach to avoid extra packet delivery. Besides, Serpens designs an NF scaling mechanism to minimize performance fluctuation. We have implemented a prototype of Serpens and conducted comprehensive experiments. Compared with the NFs and Service function Chains (SFCs) that run on existing FaaS platforms, Serpens can improve the throughput by more than 10x and reduce the latency by more than 90%.

关键词： FaaS Platform high performance network function

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Syscall Analysis for Resource Stress Identification for Container network functions 17

Syscall Analysis for Resource Stress Identification for Cont...

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IEEE 17th International Conference on Cloud Computing (IEEE CLOUD)

作者： Govindarajan, Chander Naik, Priyanka Govindarajan, Kavya Goel, Seep Kodeswaran, Palanivel Sen, Sayandeep Javachandran, Praveen IBM Res Gurugram India

ISBN: (纸本)9798350368543;9798350368536

Containerized network functions (CNFs) have seen recent increase in adoption due to the success of orchestration platforms and the natural flexibility of containers for deployment to heterogeneous, resource constrained environments like the edge. However, the weak isolation model of containers makes them susceptible to performance degradation due to interference from other containers. The interference manifests as stress on various resources like CPU, memory, cache, bandwidth of a CNF. While identifying the exact resource that is under stress is essential to employ the right remediation strategies, it is a challenging problem given the wide spectrum of applications, platforms and hardware, especially with the high performance requirements of CNFs with stringent SLAs. We present SARI, a first of a kind practical NF-agnostic framework leveraging temporal patterns in syscalls. SARI works for multi-service NFs and generalizes to a wide range of conditions. We leverage supervised time series classification and achieve performance upto 98.9% with minimal captures at runtime (starting from 25ms). SARI's prediction error is 63.33% lower than any existing stress identification framework for VNFs and to the best of our knowledge, the first to address the problem for CNFs.

关键词： cloud containerized network functions network function resource stress stress identification syscall

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