I am not updating this website form past 1 year. Please write to me at akshayjajoo.research@gmail.com for any questions regarding research.

I am a Ph.D. graduate from school of Computer Science at Purdue University. At Purdue I was working at the Distributed Systems and Networking Lab (DSNL) under the guidance of Dr. Y. Charlie Hu. My research interests lie primarily in the domains of Distributed Systems, Data Center Networks and Computer Networks. Here is a brief writeup about my research at DSNL.

I graduated from Indian Institute of Technology, Guwahati in 2015 with a Bachelor of Technology degree in Computer Science and Engineering. I was awarded the prestigious President Dr. Shankar Dayal Sharma Gold Medal for excellence in academics, extra-curricular activities and leadership roles in the college.

When I am not in my lab you can find me at some swimming pool, or playing tabla (resumed practice since 2018 after a long break). I also enjoy having a friendly debate and trying new cuisines. Sometimes, I spend time reading articles on psychology and human behavior. On the world wide web you can also find more about me at LinkedIn.

  • Spring 2018 Network Security

  • Fall 2017 Information Security

  • Spring 2017 Theory of Computation

  • Spring 2017 Mathematical Toolkit

  • Fall 2016 Compilers

  • Fall 2016 Distibuted Computing Systems

  • Spring 2016 Distributed Systems

  • Spring 2016 Algorithms

  • Fall 2015 Operating Systems

  • Fall 2015 Data Communication and Computer Networks

Summer reasearch fellowship by Purdue Graduate School

This medal is awarded to a graduating student adjudged to be the best in terms of general proficiency including character,

conduct and excellence in academic performance, extra-curricular activities and social service.

This scholarship was granted to pursue a research internship in France for a summer.

This scholarship was granted to pursue a research internship for a summer in Germany.

This system grants awards to students who have excelled in the area of science and technology and who continue to

aspire to higher academic achievement.

My tuition at IIT Guwahati was waived by a Government of India scholarship.

Authors: Akshay Jajoo, Y. Charlie Hu, Xiaojun Lin

USENIX node, Bibtex, Paper, Presentation

Coflow scheduling improves data-intensive application performance by improving their networking performance. State-of-the-art online coflow schedulers in essence approximate the classic Shortest-Job-First (SJF) scheduling by learning the coflow size online. In particular, they use multiple priority queues to simultaneously accomplish two goals: to sieve long coflows from short coflows, and to schedule short coflows with high priorities. Such a mechanism pays high overhead in learning the coflow size: moving a large coflow across the queues delays small and other large coflows, and moving similar-sized coflows across the queues results in inadvertent round-robin scheduling

We propose Philae, a new online coflow scheduler that exploits the spatial dimension of coflows, i.e., a coflow has many flows, to drastically reduce the overhead of coflow size learning. Philae pre-schedules sampled flows of each coflow and uses their sizes to estimate the average flow size of the coflow. It then resorts to Shortest Coflow First, where the notion of shortest is determined using the learned coflow sizes and coflow contention. We show that the sampling-based learning is robust to flow size skew and has the added benefit of much improved scalability from reduced coordinator-local agent interactions. Our evaluation using an Azure testbed, a publicly available production cluster trace from Facebook shows that compared to the prior art Aalo, Philae reduces the coflow completion time (CCT) in average (P90) cases by 1.50x (8.00x) on a 150-node testbed and 2.72x (9.78x) on a 900-node testbed. Evaluation using additional traces further demonstrates Philae's robustness to flow size skew.

USENIX node, Bibtex, Paper, Presentation

Authors: Akshay Jajoo, Rohan Gandhi, Y. Charlie Hu, Cheng-Kok Koh

ACM DL, Bibtex, Paper, Presentation

Prior Coflow schedulers approximate the classic online Shortest-Job-First (SJF) scheduling by using a global scheduler to sort Coflows into multiple priority queues, and a local scheduler at each network port to schedule the local flows of Coflows in each priority queue using FIFO. Such a division of the scheduling suffers two problems: (1) The flows of a Coflow may suffer the out-of-sync problem -- they may be scheduled at different times and become drifting apart, negatively affecting the Coflow completion time (CCT); (2) FIFO scheduling of flows at each port bears no notion of SJF, leading to suboptimal CCT.

Saath is an online Coflow scheduler that overcomes the above drawbacks by explicitly exploiting the spatial dimension of Coflows. Our evaluation using an Azure testbed and simulations of production cluster traces show that compared to Aalo, Saath reduces the CCT on average by 1.78x (P90 = 4.50x), which reduces the job completion time on average by 1.46x (P90 = 1.86x).

ACM DL, Bibtex, Paper, Presentation

Authors: Akshay Jajoo, Rohan Gandhi, Y. Charlie Hu

USENIX node, Bibtex, Paper, Presentation

Coflow is a networking abstraction. A group of flows sharing a common end goal are termed as Coflow. Graviton provides proof of the concept that how by taking spatial dimension of Coflows into account we can improve Coflow completion time significantly. We have shown that width, number of different ports involved, is a very strong and significant indicator of optimal Coflow ordering. Coflow scheduling is an NP-Hard problem. On a high level, the proposed heuristic sorts Coflows according to their width. We have achieved a speedup of 1.25x (P50) and 8.0x (P90) in Coflow completion time as compared to the state-of-the-art Coflow scheduler Aalo.

USENIX node, Bibtex, Paper, Presentation

Guide: Dr. Y. Charlie Hu, Professor, EE, Purdue University.

We are working on designing job scheduling policies in the data center.

Our focus is to improve job completion time.

Guide: Dr. Y. Charlie Hu, Professor, EE, Purdue University.

We are working to optimize performance of analytics jobs in data center by improving their communication stage.

Our focus is to improve Coflow completion time.

Publications: Graviton (USENIX HotCloud 2016, Bibtex), Saath (ACM CoNEXT 2017, Bibtex), Philae (USENIX ATC 2019, Bibtex)

Guide: Dr. Gene Spafford, Professor, CS, Purdue University.

Part of course on Information Security. A term paper on how the morris worm had influenced network security and what is state of computer security in present world.


I worked with a team called NetArch, that works on optimizing and scaling Google’s public network’s infrastructure, my work was focused on prioritizing errors in Internet traffic in the order they should be tackled. During the internship, along with many advanced Google technologies,

I got insight on working of Map-Reduce and distributed jobs by using internal version of Google's Cloud Dataflow and Borg.

Implementation of Non-blocking distributed BST C++.


Guide: Dr. Raoul Velazco, Professor, TIMA Laboratory

Developed a program for Arduino processor which provides communication via 3G between one of their experimental FPGA board,

kept at remote location, and webserver. Also developed a user friendly website for managing the experiment.

Guide: Dr. T. Venkatesh, Asst. Professor, Dept. of CSE, IIT Guwahati.

Identified features to classify HTTP (and HTTPS) traffic from flows using other protocols. LCPSVM was implemented in MATLAB to do

this classiffication. Upto 8% better classiffication was achieved as compared to normal SVM with these features.

Guide: Dr. Rainer Lienhart, Professor, Institut for Informatik, Universitat at Augsburg.

Automated the process of creating random poselets and positive and negative samples for it, implemented and used procrustes

distance to compare images closeness.

Proposed use of Β(2, 2) distribution for human poselets selection instead of uniform distribution.

Implementation of TCP without Time out. Course Project at Prudue.

Implemented Paging, RMS scheduling, Solaris Scheduling and few other modules on top of Xinu OS . Course Project at Purdue

Guide: Dr. P.K Das, Professor, Dept. of CSE, IIT Guwahati.

An application software, developed in C#, for complete management of a restaurant.

  • E-mail ajajoo[YouKnow]purdue[YouKnow]edu

  • Snail mail 305 N University Street,
    Purdue University,
    West Lafayette,
    IN 47907, USA.

  • Phone +1-765-494-3431