<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom" xmlns:content="http://purl.org/rss/1.0/modules/content/"><channel><title>Máté Nagy</title><link>https://matenagy.hu/</link><description>Recent content on Máté Nagy</description><generator>Hugo</generator><language>en-us</language><atom:link href="https://matenagy.hu/index.xml" rel="self" type="application/rss+xml"/><item><title/><link>https://matenagy.hu/papers/</link><pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate><guid>https://matenagy.hu/papers/</guid><description>&lt;h2 id="papers"&gt;Papers&lt;/h2&gt;
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&lt;p&gt;&lt;strong&gt;&lt;a href="https://ieeexplore.ieee.org/document/11435462"&gt;Elastic Scaling of Real Time Communication Services&lt;/a&gt;&lt;/strong&gt;&lt;/p&gt;
&lt;p&gt;Real-time Communications (RTC) services, including multiparty conferencing, live streaming, and cloud-gaming, rely on a large-scale media plane infrastructure that provides real-time audio/video processing to clients. Unfortunately, off-the-shelf RTC services are not elastically scalable. As a result, operators must provision media servers to meet peak demand, resulting in resource under-utilization and high cost. Given that today microservice orchestrators like Kubernetes allow web-services to scale transparently and econimically, this paper looks at applying the same approach to scale large-scale RTC services.&lt;/p&gt;</description></item></channel></rss>