[NRG] [WING] Notification: NRG Meeting: Maple: Simplifying SDN Programming Using Alg... @ Tue Mar 17, 2015 11am - 12pm (NRG at BU)

Yuefeng Wang wyf at bu.edu
Thu Mar 12 13:13:24 EDT 2015


Sorry to update again. Cody's talk will start at 3:30pm on Tuesday.

BTW,  NRG calendar is publicly accessible at http://www.bu.edu/cs/nrg/.

Regards,
Yuefeng

On Thu, Mar 12, 2015 at 11:50 AM, Yuefeng Wang <wyf at bu.edu> wrote:

> Hi everyone,
> Just an update. Cody's talk will be at 3pm on Tuesday instead of 11am.
>
> Regards,
> Yuefeng
>
> On Thu, Mar 12, 2015 at 11:00 AM, Google Calendar <
> calendar-notification at google.com> wrote:
>
>> more details »
>> <https://www.google.com/calendar/event?action=VIEW&eid=dnNvbTVpaGsyaTBxZjcyYmIycTVyODRqNjggNTYwam42bnQ1aGo0b2YzcnNyaWNoZnB0aW9AZw>
>> NRG Meeting: Maple: Simplifying SDN Programming Using Algorithmic
>> Policies (Cody Doucette)
>> Maple: Simplifying SDN Programming Using Algorithmic Policies
>>
>> Presenter: Cody Doucette
>>
>> Authors: Andreas Voellmy, Junchang Wang, Y. Richard Yang, Bryan Ford,
>> Paul Hudak
>>
>> Abstract:
>>
>> Software-Defined Networking offers the appeal of a simple, centralized
>> programming model for managing complex networks. However, challenges in
>> managing low-level details, such as setting up and maintaining correct and
>> efficient forwarding tables on distributed switches, often compromise this
>> conceptual simplicity. In this talk, I will present Maple, a system that
>> simplifies SDN programming by (1) allowing a programmer to use a standard
>> programming language to design an arbitrary, centralized algorithm, which
>> we call an algorithmic policy, to decide the behaviors of an entire
>> network, and (2) providing an abstraction that the programmer-defined,
>> centralized policy runs, conceptually, “afresh” on every packet entering a
>> network, and hence is oblivious to the challenge of translating a
>> high-level policy into sets of rules on distributed individual switches.
>>
>> To implement algorithmic policies efficiently, Maple includes not only a
>> highly-efficient multicore scheduler that can scale efficiently to
>> controllers with 40+ cores, but more importantly a novel tracing runtime
>> optimizer that can automatically record reusable policy decisions, offload
>> work to switches when possible, and keep switch flow tables up-to-date by
>> dynamically tracing the dependency of policy decisions on packet contents
>> as well as the environment (system state). Evaluations using real HP
>> switches show that Maple optimizer reduces HTTP connection time by a factor
>> of 100 at high load. During simulated benchmarking, Maple scheduler, when
>> not running the optimizer, achieves a throughput of over 20 million new
>> flow requests per second on a single machine, with 95-percentile latency
>> under 10 ms.
>>
>> This paper was originally presented at SIGCOMM '13, and is available for
>> download here:
>> http://conferences.sigcomm.org/sigcomm/2013/papers/sigcomm/p87.pdf
>> <https://www.google.com/url?q=http%3A%2F%2Fconferences.sigcomm.org%2Fsigcomm%2F2013%2Fpapers%2Fsigcomm%2Fp87.pdf&usd=2&usg=AFQjCNENx6c6I152pH86WOjPbU8TZLVF7w>
>>
>> *When*
>> Tue Mar 17, 2015 11am – 12pm Eastern Time
>> *Calendar*
>> NRG at BU
>> *Who*
>>>> Yuefeng Wang - creator
>>
>> Invitation from Google Calendar <https://www.google.com/calendar/>
>>
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