<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Research |</title><link>https://integraceion.com/tags/research/</link><atom:link href="https://integraceion.com/tags/research/index.xml" rel="self" type="application/rss+xml"/><description>Research</description><generator>HugoBlox Kit (https://hugoblox.com)</generator><language>en-us</language><lastBuildDate>Mon, 27 Oct 2025 00:00:00 +0000</lastBuildDate><image><url>https://integraceion.com/media/icon_hu_1c0e9cb08cfb822a.png</url><title>Research</title><link>https://integraceion.com/tags/research/</link></image><item><title>Energy &amp; Resilience Analysis of 5G Cloud-Native Service Meshes</title><link>https://integraceion.com/projects/msc-thesis/</link><pubDate>Mon, 27 Oct 2025 00:00:00 +0000</pubDate><guid>https://integraceion.com/projects/msc-thesis/</guid><description>&lt;p&gt;Master’s thesis research investigating the performance overhead, energy consumption, and mitigation mechanics of Service Meshes deployed over a cloud-native 5G core network.&lt;/p&gt;
&lt;h2 id="research-context"&gt;Research Context&lt;/h2&gt;
&lt;p&gt;Modern 5G deployments rely heavily on Service-Based Architectures (SBA) running over Kubernetes. While deploying a Service Mesh (like Istio or Linkerd) provides crucial zero-trust security and observability, it injects proxy sidecars into every pod, resulting in compute and energy overhead.&lt;/p&gt;
&lt;p&gt;This study specifically evaluates how these sidecars affect CPU utilization, power metrics, and network latency when mitigating active Distributed Denial-of-Service (DDoS) vectors across Service-Based Interfaces (SBI).&lt;/p&gt;
&lt;h2 id="technical-implementation"&gt;Technical Implementation&lt;/h2&gt;
&lt;h3 id="environment-setup"&gt;Environment Setup&lt;/h3&gt;
&lt;ul&gt;
&lt;li&gt;&lt;strong&gt;5G Core:&lt;/strong&gt; Containerized deployment utilizing Open5GS running over a localized Kubernetes cluster.&lt;/li&gt;
&lt;li&gt;&lt;strong&gt;Service Mesh:&lt;/strong&gt; Implementation of Istio to manage traffic shaping, mTLS, and network policies between Network Functions (NFs).&lt;/li&gt;
&lt;/ul&gt;
&lt;h3 id="telemetry--benchmarking"&gt;Telemetry &amp;amp; Benchmarking&lt;/h3&gt;
&lt;ul&gt;
&lt;li&gt;&lt;strong&gt;Data Collection:&lt;/strong&gt; Automated metric collection scripts written in Python, interfacing directly with Prometheus.&lt;/li&gt;
&lt;li&gt;&lt;strong&gt;Stress Testing:&lt;/strong&gt; Simulated traffic stress and active DDoS vectors to capture power and throughput profiles under adverse network conditions.&lt;/li&gt;
&lt;/ul&gt;
&lt;h2 id="key-findings"&gt;Key Findings&lt;/h2&gt;
&lt;p&gt;The research successfully mapped the specific trade-offs between zero-trust security enforcement and server power consumption, providing actionable data for telecom operators balancing security with OPEX.&lt;/p&gt;
&lt;ul&gt;
&lt;li&gt;&lt;strong&gt;Thesis Document:&lt;/strong&gt;
&lt;/li&gt;
&lt;li&gt;&lt;strong&gt;Code Repository:&lt;/strong&gt;
&lt;/li&gt;
&lt;/ul&gt;
&lt;div class="highlight"&gt;&lt;pre tabindex="0" class="chroma"&gt;&lt;code class="language-fallback" data-lang="fallback"&gt;&lt;/code&gt;&lt;/pre&gt;&lt;/div&gt;</description></item></channel></rss>