Aditya Akella

ACM SIGCOMM Student Mentoring Column: On Program Committees and Social Networking at Conferences

By: 
Aditya Akella
Appears in: 
CCR April 2016

Dear students: This edition of the Student Mentoring Column focuses on various testbeds (for wired networking researching) and datasets. The questions below don't provide comprehensive coverage of either topic; as such, we may revisit them in future editions. I also hope to talk about wireless testbeds and datasets in a future column.
I got plenty of help in preparing this edition. In particlar, many thanks to Aaron Gember-Jacobson (UW-Madison), Brighten Godfrey (UIUC), Ethan Katz-Bassett (USC), and Vyas Sekar (CMU).

ACM SIGCOMM Student Mentoring Column: On Program Committees and Social Networking at Conferences

By: 
Aditya Akella
Appears in: 
CCR January 2016

Dear students: This edition of the Student Mentoring Column focuses on program committees (their composition and how they work) and the importance of social networking at conferences. The questions below don’t provide comprehensive coverage of either topic; as such, we may revisit them in future editions. I got plenty of help in preparing this edition. In particular, many thanks to Kyle Jamieson (Princeton), Ethan Katz-Bassett (USC), George Porter (UCSD), Vyas Sekar (CMU), and Minlan Yu (USC) for contributing answers.

Network Policy Whiteboarding and Composition

By: 
Jeongkeun Lee, Joon-Myung Kang, Chaithan Prakash, Sujata Banerjee, Yoshio Turner, Aditya Akella, Charles Clark, Yadi Ma, Puneet Sharma, Ying Zhang
Appears in: 
CCR August 2015

We present Policy Graph Abstraction (PGA) that graphically expresses network policies and service chain requirements, just as simple as drawing whiteboard diagrams. Different users independently draw policy graphs that can constrain each other. PGA graph clearly captures user intents and invariants and thus facilitates automatic composition of overlapping policies into a coherent policy.

Low Latency Geo-distributed Data Analytics

By: 
Qifan Pu, Ganesh Ananthanarayanan, Peter Bodik, Srikanth Kandula, Aditya Akella, Paramvir Bahl, Ion Stoica
Appears in: 
CCR August 2015

Low latency analytics on geographically distributed datasets (across datacenters, edge clusters) is an upcoming and increasingly important challenge. The dominant approach of aggregating all the data to a single datacenter significantly inflates the timeliness of analytics. At the same time, running queries over geo-distributed inputs using the current intra-DC analytics frameworks also leads to high query response times because these frameworks cannot cope with the relatively low and variable capacity of WAN links. We present Iridium, a system for low latency geo-distributed analytics.

Presto: Edge-based Load Balancing for Fast Datacenter Networks

By: 
Keqiang He, Eric Rozner, Kanak Agarwal, Wes Felter, John Carter, Aditya Akella
Appears in: 
CCR August 2015

Datacenter networks deal with a variety of workloads, ranging from latency-sensitive small flows to bandwidth-hungry large flows. Load balancing schemes based on flow hashing, e.g., ECMP, cause congestion when hash collisions occur and can perform poorly in asymmetric topologies. Recent proposals to load balance the network require centralized traffic engineering, multipath-aware transport, or expensive specialized hardware.

PGA: Using Graphs to Express and Automatically Reconcile Network Policies

By: 
Chaithan Prakash, Jeongkeun Lee, Yoshio Turner, Joon-Myung Kang, Aditya Akella, Sujata Banerjee, Charles Clark, Yadi Ma, Puneet Sharma, Ying Zhang
Appears in: 
CCR August 2015

Software Defined Networking (SDN) and cloud automation enable a large number of diverse parties (network operators, application admins, tenants/end-users) and control programs (SDN Apps, network services) to generate network policies independently and dynamically. Yet existing policy abstractions and frameworks do not support natural expression and automatic composition of high-level policies from diverse sources. We tackle the open problem of automatic, correct and fast composition of multiple independently specified network policies.

ACM SIGCOMM Student Mentoring Column

By: 
Aditya Akella
Appears in: 
CCR April 2015

As some of you may know, I gave a talk at CoNEXT 2014 titled "On future-proofing networks" (see [1] for slides). While most of the talk was focused on my past research projects, I spent a bit of time talking about the kind of problems I like to work on. I got several interesting questions about the latter, both during the talk and in the weeks following the talk. Given this, I thought I would devote this column (and perhaps parts of future columns) to putting my ideas on problem selection into words. I suspect what I write below will generate more questions than answers in your mind.

OpenNF: enabling innovation in network function control

By: 
Aaron Gember-Jacobson, Raajay Viswanathan, Chaithan Prakash, Robert Grandl, Junaid Khalid, Sourav Das, Aditya Akella
Appears in: 
CCR August 2014

Network functions virtualization (NFV) together with softwaredefined networking (SDN) has the potential to help operators satisfy tight service level agreements, accurately monitor and manipulate network traffic, and minimize operating expenses. However, in scenarios that require packet processing to be redistributed across a collection of network function (NF) instances, simultaneously achieving all three goals requires a framework that provides efficient, coordinated control of both internal NF state and network forwarding state. To this end, we design a control plane called OpenNF.

Multi-resource packing for cluster schedulers

By: 
Robert Grandl, Ganesh Ananthanarayanan, Srikanth Kandula, Sriram Rao, Aditya Akella
Appears in: 
CCR August 2014

Tasks in modern data-parallel clusters have highly diverse resource requirements along CPU, memory, disk and network. We present Tetris, a multi-resource cluster scheduler that packs tasks to machines based on their requirements of all resource types. Doing so avoids resource fragmentation as well as over-allocation of the resources that are not explicitly allocated, both of which are drawbacks of current schedulers.

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