Portrait of Thomas Karagiannis

Thomas Karagiannis

Senior Researcher


I am a senior researcher with the systems and networking group at Microsoft Research, Cambridge, UK. My research interests span most aspects of computer communications and networks with my current focus being on data centers. In the past, I worked on Internet measurements and monitoring, traffic classification, network management, home networks, social networks, and peer-to-peer networks.

I received my Ph.D from the Computer Science department of the University of California, Riverside, and completed my undergraduate studies at the department of Applied Informatics of the University of Macedonia in Thessaloniki, Greece.

Selected Publications



Software-Defined Storage (SDS) Architectures

Established: August 14, 2013

In data centers, the IO path to storage is long and complex. It comprises many layers or “stages” with opaque interfaces between them. This makes it hard to enforce end-to-end policies that dictate a storage IO flow’s performance (e.g., guarantee a tenant’s IO bandwidth) and routing (e.g., route an untrusted VM’s traffic through a sanitization middlebox). We are researching architectures that decouple control from data flow to enable such policies.

Big Data Analytics

Established: October 18, 2012

We conduct research in the area of algorithms and systems for processing massive amounts of data. Our work aims at pushing the boundary of computer science in the area of algorithms and systems for large-scale computations. Our mission is to achieve major technological breakthroughs in order to facilitate new systems and services relying on efficient processing of big data. Research Areas Database queries - How can we efficiently resolve database queries on massive amounts of input data? Here the input data may be…

Predictable Data Centers (PDC)

Established: September 1, 2010

Performance predictability is a key requirement for high-performant applications in today's multi-tenant datacenters. Online services running in infrastructure datacenters need such predictability to satisfy applications SLAs. Cloud datacenters require guaranteed performance to bound customer costs and spur adoption. However, the network and storage stack used in today’s datacenters is unaware of such application requirements. This projects examines how to enable preditable datacenters. Performance predictability is a key requirement for high-performant applications in today's multi-tenant data…

HomeMaestro: A distributed system for the monitoring and instrumentation of home networks

HomeMaestro strives to put order in the chaos of home networks through an end-host distributed solution that requires no additional assistance from network equipment such as routers or access points or modification of network applications. HomeMaestro performs extensive measurements at the host level to infer application network requirements, and identifies network related problems through time-series analysis. HomeMaestro automatically detects and resolves contention over network resources.



















Microsoft Research Storage Toolkit

November 2014

The Microsoft Research Storage Toolkit enables effective and accessible research in Software Defined Storage by adding I/O classification functions to the Windows 8.1 storage stack and exposing selected flows of I/O requests to a user-supplied program written in C# which can easily inspect or modify them. Parts of the Toolkit have supported our own recent…

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