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The SILO project is funded by the National Science Foundation FIND Grant. SILO: A novel framework for flexible protocol composition. George Rouskas , Rudra Dutta , Anjing Wang, Mohan Iyer North Carolina State University,. Dan Stevenson RTI. Ilia Baldine, - PowerPoint PPT Presentation
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SILO: A novel framework for flexible protocol composition
Ilia Baldine, Renaissance Computing
Institute
The SILO project isfunded by theNational Science FoundationFIND Grant
George Rouskas, Rudra Dutta,
Anjing Wang, Mohan IyerNorth Carolina State
University,
Dan StevensonRTI
Motivation• Observations of the current state
– Balkanization of protocols (VoIP, sensor nets, wireless, high-speed)
– Proliferation of half-layer solutions (IPSec, MPLS etc)
– Ossification of protocol research (e.g. growing number of TCP variants)
– Lack of explicit cross-layer interactions– Inability to separate salient features of protocols
• Looking forward– Provide ways for smooth evolution of protocols for
new transport technologies, control algorithms
Musings• Layering is important, however rigid layer
boundaries are limiting• Design for change: create a meta-design
that can accommodate future changes• Architecture must constrain – otherwise you
get proliferation of functions at various places– But must not constrain wrong thing and stifle
innovation, ossify, etc.– Job of architecture – constrain (channel) the
mechanisms used for different players to bring their various pieces and use them
Traditional and SILO network stacks
Transport
Network
Data Link
Physical
Physical Channels
App App App
Transport
Cross-ServiceTuning
silo &servicemgmt
Tuningstrategies,
hints
ComposabilityConstraints
App App App
Physical Channels
m11 m11 m13
m21 m21
m31
m21 m31 m31
m42 m43
m62 m62 m61
SILO Features• Emphasis on re-usability, not
miniaturization• Automated construction of silos via
ontology• Explicit cross-layer control and interactions• Separation of mechanisms from policies• Do not require specific OS architecture –
just a convention for implementation (template or pattern)
SILO architecture high-level view
Method
Service
S1
S2
S3
S4
S5
M1,1
M1,2 ControlAgent
Policies andStrategies
Application
M1,1
M2,2
M5,3
M3.2
M4,4
M5,1
M1,2
M2,3
M7.3
Physical Interfaces
Precedence Constraint
Service/Method Paradigm
Preceding Service Communication Spec
Service-specific Control
Interface
Succeeding Service Communication Spec
Service
MethodService-Specific Controls
Preceding Service Communications
Method Implementation
Method
Method-specific Controls Succeeding Service
Communications
The SILO hourglass• What is the convergence
point?– Service API– Ontology schema (a
language to describe network services)
10
SILO Ontology• Encodes knowledge on
relations between services and methods
• Encodes service types and functions to enable ‘fuzzy’ inference
• Written using Protégé in RDF
• Work in progress
SILO Ontology tools
SILO as a research tool• SILO is deployed with ontology and existing set of
services• Researcher brings
– Custom services– Tuning algorithms– Ontology updates
• Can connect to measurement functions to provide a cross-layer protocol experimentation tool
• Allows experimentation with various layering approaches exploring the optimization space
Wireless example: adaptive transport
• Goal: design a set of services and cross-layer tuning algorithm to maximize goodput across a wireless network– Adaptive FEC service – Adaptive MTU service – Adaptive window management service– Tuning algorithm to manage the knobs
Optical example: impairment-aware routing
• Goal: design an optical-impairment-aware routing protocol that maximizes network utilization– Distributed impairment measurement
capabilities (e.g. PMD)– Routing service capable of using the
information
Silo proof-of-concept• User-space open framework
– C++ and Python• Methods are DLLs with a well-defined interface• Silo construction agent uses ontology to create an
XML “recipe” for a silo• Silo Management Agent
– Loads and executes the code for silos based on packet events and timers
– Maintains silo state• Silo Tuning Agent is a container for tuning
algorithms/strategies associated with services• Universe of Services contains the ontology and
dynamically loadable code implementing methods
Available APIs• Application API
– Socket like for managing data transfers– Ability to specify constraints on silo construction
imposed by the application writer• Service API
– Well-defined set of functions for managing service interfaces (upper, lower, tuning knobs and gauges)
– SBuf (mbuf or skbuf like) state– Service state
SILO Prototype
Demo setup
DEMO
Future steps• Joint projects
– Converged Services Platform– Optical IMF for GENI
• Silo similarity/synchronization• Construction of siloplexes• Software-defined optics• Network Virtualization• Consistency• Stability• New services• New transports• New addressing schemes• New routing implementations• ….