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