The Linux kernel's scheduler is one of its most critical components, determining which tasks run on which CPUs and for how long. But in today's complex computing environments, the default Linux scheduler doesn't always provide optimal performance for specialized workloads. This is where sched_ext (SCX) comes in – a framework that allows implementing custom CPU schedulers in BPF (Berkeley Packet Filter) and loading them dynamically. In this technical analysis. I'll examine the architecture and implementation of SCX schedulers, with a particular focus on scx_rustland and scx_bpflandand, compared to traditional schedulers. What is sched_ext? Sched_ext Linux kernel 6.12 introduced sched_ext (“extensible scheduler”) as a new scheduling class that allows pluggable CPU schedulers via eBPF

Based on NGAP Load Balancing with LoxiLB and 5g-sctp-loadbalancer, but change 5G Core to use free5gc instead of Open5gs This implementation is primarily based on above two references setup and target: I'm trying to implement SCTP load balancing for Free5GC AMF using LoxiLB, but encountering connection issues. Here's my setup: Environment: Single Kubernetes cluster running Free5GC components

Based on NGAP Load Balancing with LoxiLB, but change 5G Core to use free5gc instead of Open5gs Overall Architecture (Single-Cluster) Single Kubernetes Cluster: All Free5GC network functions run in a single K8s cluster LoxiLB: LoxiLB will within that same cluster to load-balance traffic destined for the AMF’s N2 interface (SCTP). Preparing LoxiLB instance LoxiLB runs as a standalone Docker container (--net=host). $ apt-get update

Introduction Loxilb is a networking solution that utilizes eBPF, leverage eBPF to modify the packet processing rules as they traverse the network stack in the Linux kernel. This can be particularly useful for network behavior without altering existing applications or the operating system itself. Core Components Object Files loxilb generates two primary object files during build: /opt/loxilb/llb_ebpf_main.o # TC layer processing (305KB) /opt/loxilb/llb_xdp_main.o # XDP layer processing (95KB) Hook Points

What is LoxiLB an open-source, cloud-native load balancer designed specifically for Kubernetes environments. It leverages eBPF technology, a powerful tool that allows for efficient packet processing within the Linux kernel, enhancing network performance and security Advantages Dual Layer Load Balancing Key advantages of LoxiLB is its ability to operate as both an L4 and L7 load balancer. Client → L7LB → L4LB → Backend servers L7LB:

contributed by < williamlin0518 > 第一週測驗題 測驗一 :::danger 不用列出參考題解，專注於程式碼行為分析和你的改進。 ::: node_t *list_tail(node_t **left) {

contributed by < williamlin0518 > 實驗環境 william@william-System-Product-Name:~$ gcc --version gcc (Ubuntu 13.2.0-23ubuntu4) 13.2.0 Copyright (C) 2023 Free Software Foundation, Inc. This is free software; see the source for copying conditions. There is NO warranty; not even for MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. william@william-System-Product-Name:~$ lscpu

contributed by < williamlin0518 > 開發環境 $ gcc --version gcc (Ubuntu 11.4.0-1ubuntu1~22.04) 11.4.0 Copyright (C) 2021 Free Software Foundation, Inc. This is free software; see the source for copying conditions. There is NO warranty; not even for MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. $ lscpu

contributed by < williamlin0518 > 第三週測驗題 測驗 1 int i_sqrt(int x) { if (x <= 1) /* Assume x is always positive */ return x; int z = 0;

contributed by < williamlin0518 > 閱讀〈因為自動飲料機而延畢的那一年〉與課程啟發 閱讀心得 從大一到大四，儘管修習過的課程越多，卻對未來越來越迷惘，也了解到實踐與理論的差距，即使在大學學到許多理論知識,真正將它們付諸實踐並不容易。這需要不斷的嘗試、失敗和修正。這個過程是痛苦的，但卻是獲得真正經驗的必經之路。像是作者決定從一個具體的問題出發，跳脫舒適圈，做一款自動飲料機。 大學安排了很多紮實的課程給學生，資料結構、演算法、計算機網路都是必修，但大多數的資工系在大三、大四時，實做能力依舊貧乏，這句話真是深有同感，在大四時思考可以做出甚麼貢獻，卻發現什麼都會，卻又甚麼都不會，更何談創業呢?跨領域挑戰的艱難、理論與實踐的鴻溝、都讓我卻步，但看到作者這一段踐行夢想、面對現實、獲得成長的人生路程，他們不斷自學、實驗、修正,遭遇無數次失敗和挫折。但正是這種百折不撓的毅力,讓他們最終做出了可用的樣機。 所以效法作者,挑選一個切實可行的目標，不一定是創業，可以是先學好linux，盡自己所能去實現，哪怕過程艱辛。只要勇於踏出舒適圈，在實踐中學習和修正，必能成長。 課程心得 課程也邁入中期，回想當初自己修課的原因，讀懂linux核心，精熟作業系統，了解SOC，深入嵌入式系統，貢獻開源軟體，多麼豪情壯志，現在看來達成率是近乎0%，但是沒有收穫嗎?一個個課堂測驗，都要花費大量時間參考文獻，分頁開了又開，卻仍似懂非懂，也開始重頭審視自己，誠實面對自己，是我目前最大的收穫了，了解自己其實什麼都不會，這四年只摸了個皮毛，看清這些後，也讓我更好奇這些領域，渴望更深入的學習。