Changes between Version 38 and Version 39 of coin


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Timestamp:
Nov 8, 2018, 7:37:46 AM (12 months ago)
Author:
marie@…
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    v38 v39  
    33'''Introduction'''
    44
    5 Integrating computing and networking has been widely investigated and applied at several network layers in the past. Most notably, “Active Networking” research in the 1990s explored approaches for allowing packets and datagrams flowing through a network to modify the behavior of the network itself. This could be done at several layers, e.g., enabling/modifying transport protocol behavior, configuring or programming link layer functionality
    6 upon connection establishment etc.
    7 
    8 Hence are experiencing a convergence between the concepts of networking and computing, triggered not only by the softwarization of networking functions (SDN, NFV) but also by the evolution of the network architecture. The move to edge distributed computing/networking is also encouraging the development of local networking and computing facilities to support low delay and low loss services that are emerging from AR/VR, autonomous vehicles and intelligent/smart cities.
    9 
    10 Recent research in network data plane programmability has enabled new ways for relaxing the boundaries between strictly network layer and application layer programmability. For example, programming abstractions such as P4 and more powerful programmable DC switch platforms enable the implementation of different support functions for application layers entities, supporting applications such as DNN (Deep Neural Network) training, frontend KV (Key-Value) caching for skewed and dynamic workloads, and high-performance consensus protocols such as
     5The integration computing and networking seems natural and has been widely investigated and applied at several network layers in the past. Most notably, “Active Networking” research in the 1990s explored approaches for allowing packets and datagrams flowing through a network to modify the behavior of the network itself. This could be done at several layers, e.g., enabling/modifying transport protocol behavior, configuring or programming link layer functionality upon connection establishment etc.
     6
     7We are experiencing a new wave of convergence between networking and computing, triggered not only by the softwarization of networking functions (SDN, NFV) but also by the evolution of the network architecture itself. The move to the edge and distributed computing/networking is also encouraging the development of local networking and computing facilities to support low delay and low loss services that are emerging from AR/VR, autonomous vehicles, V2X and intelligent/smart cities.
     8
     9Recent research in network data plane programmability has also enabled new ways for relaxing the boundaries between strictly network layer and application layer programmability. For example, switch programming abstractions such as P4 and more powerful programmable data center switch platforms enable the implementation of different support functions for application layers entities, supporting applications such as DNN (Deep Neural Network) training, frontend KV (Key-Value) caching for skewed and dynamic workloads and high-performance consensus protocols such as
    1110Paxos.
    1211
    13 In addition, there are scalable stream processing frameworks such as Apache Spark or Apache Flink that apply programmed functions on data flowing in a distributed system. These platforms are typically concerned with guaranteeing certain semantics and providing high reliability and performance by orchestrating the set of functions accordingly. Such as distributed processing platforms are overlays(from a network layer perspective) but also have to deal with flow/congestion control etc. on their respective layer.
    14 
    15 In parallel, there are approaches for connecting so-called network functions (such as NFV -- Network Functions Virtualization) and derived/related computing/networking models such as CDN and Edge Computing -- which are mostly concerned with setting up and maintaining overlays and virtual networks between application logic in virtual machines etc. Consequently the idea of a “programmable” network is central to the evolution of the Internet. 
     12In addition, there are scalable stream processing frameworks such as Apache Spark or Apache Flink that apply programmed functions on data flowing in a distributed system. These platforms are typically concerned with guaranteeing certain semantics and providing high reliability and performance by orchestrating the set of functions accordingly. Such distributed processing platforms are overlays (from a network layer perspective) but also have to deal with flow/congestion control etc. on their respective layer.
     13
     14In parallel, there are approaches for connecting so-called network functions (such as NFV -- Network Functions Virtualization) and derived/related computing/networking models such as CDN and Edge Computing. They are mostly concerned with setting up and maintaining overlays and virtual networks between application logic in virtual machines but also corporate element of local processing and computing.
     15
     16Consequently the idea of a “programmable” network is central to the evolution of the Internet and for the support of emerging applications and services.
    1617
    1718
    1819'''Motivation'''
    1920
    20 Network programmability provides new opportunities to enhance performance and availability as well as to develop new types of networked applications and systems. Looking at different instantiations of integrating computing and networking, the following questions arise:
    21 
    22 1) Are there common principles, abstractions and mechanisms that can be applied across this range of different types of computing/networking approaches?
    23 
    24 2) What are best practices and relevant considerations for computing/networking systems, in particular with respect to previous discussions regarding active networking and end-to-end-arguments?
    25 
    26 3) Many of the computing/networking systems developed for and by the networking community have been designed from a networking perspective (assuming running applications that need to be connected by
    27 connections, overlays, service chains). Is there potential to include design patterns from the distributed computing and applications community (e.g., stream processing) that would allow for a more holistic design, i.e., considering both networking and computing for optimizing the layout of processing functions and distribution of data?
    28 
     21Network programmability provides new opportunities to enhance performance and availability of network as well as to develop new types of networked applications and systems. Looking at different research project that address computing and networking, the following questions emerge:
     22
     231) Are there common principles, abstractions and mechanisms that can be applied across the range of computing/networking elements?
     24
     252) What are research avenues and relevant considerations for COIN, in particular with respect to previous projects such as active networking and the agreed-on end-to-end-arguments?
     26
     273) Many of the computing/networking systems developed for and by the networking community have assumed the existence of running applications that need to be connected
     28directly, run on overlays or using service chains. Is there potential to include design patterns from the distributed computing and applications community that would allow considering both networking and computing for optimizing the layout of processing functions and distribution of data?
    2929
    3030'''Research Challenges'''
     
    100100(1) An informational RFC on the challenges of computing in the network
    101101
    102 (2) An informational RFC on data center (already there and with a draft)
     102(2) An informational RFC on data center COIN
    103103
    104104(3) A Compute First Networking informational RFC
     
    200200Design Challenges for Combining Compute and Networking (Dave Oran - 10-minutes)
    201201
    202 A Few Musings on Elastic
    203 Network Edges and In-Network Computing (Diego Lopez - 5 minutes)
     202A Few Musings on Elastic Network Edges and In-Network Computing (Diego Lopez - 5 minutes)
    204203
    205204How edge intelligence is accelerating the convergence of networking and computing (Liang Geng - 10 minutes)