resource management – a solution for providing qos over ip
DESCRIPTION
Resource Management – a Solution for Providing QoS over IP. Tudor Dumitraş, Frances Jen-Fung Ning and Humayun Latif. Outline. Motivation QoS solutions Int-Serv Diff-Serv Darwin Darwin mechanisms Xena Globus Components Operation Comparison Q&A. Motivation. - PowerPoint PPT PresentationTRANSCRIPT
Resource Management – a Solution for Providing QoS over IP
Tudor Dumitraş, Frances Jen-Fung Ning and Humayun Latif
Outline
• Motivation• QoS solutions
– Int-Serv– Diff-Serv
• Darwin– Darwin mechanisms– Xena
• Globus– Components– Operation
• Comparison• Q&A
Motivation
• IP was not originally designed for QoS– Datagram oriented, variable-length packets– Best-effort service: make better use of
bandwidth– Cannot give any QoS guarantees
(bandwidth, jitter, latency)– Streaming multimedia needs QoS– Need a circuit switched – like paradigm
QoS Solutions: Int-Serv
• Reserves resources for every flow at every router hop
• Uses the Resource Reservation Protocol (RSVP) for signaling
• Needs to maintain soft states at every router along the path
• Requires a lot of signaling: scalability is a key concern
QoS Solutions: Diff-Serv (1)
• Light-weight alternative to Int-Serv
• Consistent policies will be applied inside each trusted domain
• Traffic is classified at edge routers
• Uses the ToS field from IP headers to indicate the class of service
Diff-Serv framework
QoS Solutions: Diff-Serv (2)
• Bandwidth brokers– Establish relationships
of limited trust with their peers in adjacent domains
– Allocate traffic within the domain
– Maintain a policy database
– Configure leaf routers
Diff-Serv with bandwidth broker
Darwin
• A CMU Project• Resource Management mechanisms that
support deployment of customizable, value-added services in a network.
• Supports application oriented QoS via:– Application oriented service brokers– Delegates – to customize runtime management– Hierarchical scheduling– Signaling protocol
Darwin Mechanisms…
• Resource Brokers:– Perform global resource
allocation.– App. Specifies QoS value
metric– Use domain knowledge for
optimizations– Coordinate allocations for
interdependent resources– Darwin : Xena
• Delegates:– Enable service specific dynamic
behavior in network.– Runtime adaptation at switching
points in interior network (as opposed to flow endpoints).
– Darwin : Java code segments executing on routers.
Darwin Mechanisms
• Hierarchical Scheduling– Resource, contention exists at many
levels; physical ~ among service providers; provider level ~ lower level providers; application level ~ individual flows
– Hierarchical scheduler allows all entities to specify independent sharing policies and ensures they are met.
– Darwin : HFSC (Fair Service Curve)• Signaling Protocol:
– Provides interface between resource broker’s abstract network view and low level network resources.
– Allocates “real” resources e.g. bandwidth, buffers, cycles, memory.
– Hides network heterogeneity details from Xena.
– Darwin : Beagle
• Applications (1) submit requests to Xena (2)• Xena identifies resources needed & passes
request to Beagle (3)• Beagle allocates resources (4)• For each resource, Beagle interacts • with local resource manager.• Resource Manager modifies local state:
classifier and scheduler to guarantee appropriate service
• Beagle can set up delegates
Darwin at work
Xena – A closer look
• Resource Discovery : Locating resources that can potentially be used
• Optimization: Satisfy requirement while min. cost and max. quality
• Apps request resources in varying degrees of abstraction – Abstract: Service of class S needed – Specific: Place this node at network address X
• App. can even specify flow semantic content (e.g. Motion JPEG with specific frame rate)
• Allows Xena to insert semantic preserving transformations e.g. transcoders at two ends of network segment
• Xena optimization criteria: application-specified objective function that maps candidate solutions to numeric value
• Allows application to customize definition of service quality
Globus Architecture for Reservation and Allocation (GARA)
• Provides End to End QoS guarantees in network applications
• Enables construction of application-level reservation libraries that applications use to assemble resource collections guided by application QoS requirements and resource administration policies.
• Supports:Dynamic Discovery and Immediate Reservation of Heterogeneous
Resources that are Independently Administered and Controlled
GARA Components
• Generic Resource Object
• Information Service
• Co-Reservation Agent
• Co-Allocation Agent
• Global Resource Allocation Manager
• Local Resource Managers
• Physical Resources
GARA – Reservation vs. Allocations
• GARA Introduces Generic Resource Object to address heterogeneous physical resources in a generalized way
• Reservation made via “Create Object” request
• Create Object returns Reservation Handle to application. No “allocation” made at this point.
• Allocation made later by passing resource handle to co-allocation agent.
• Advantage of separating reservation VS allocation ~ enables advance reservations of resources when a resource is in high demand.
GARA – Operation
• Application passes request with description of service to Co-reservation agent
• CR-Agent maps QoS requirements to resources by queries to Information Service and app. Specific knowledge.
• CR-Agent creates reservation by directing request to Globus Resource Allocation Manager (GRAM).
• GRAM authenticates request, creates reservation and returns handle.
• Handle used to allocate resources later.
GARA Example• Candidate resources for Data Analysis Application include
multiple cached copies of data set• Right: Physical location of resources• Left: Search tree constructed by the co-reservation agent.• “R”s represent reservations
Comparison – Reservation Requests & Resource Allocations
• Darwin + Very flexible in QoS metric specification+ Avoids duplication of effort & expertise in areas where there
are specialized SPs+ Allows customized mgt that supports tasks that require
detailed network knowledge while others require domain-specific knowledge
- Only supports immediate reservations ~ not optimal in timing of resource allocation
• Globus + Advance reservation possibility - guarantees resource
availability for high contention resources- Not a very flexible way to specify app. QoS level.
Conclusion
• Neither really better/worse than other• Darwin:
– More flexible for specifying degree of abstraction in resource requirement of different types of services
• Globus:– Provides advance reservations– Doesn’t leave decision making to resource mgrs in
network architecture.
Questions