Aggregate Scheduling

1
Aggregate Scheduling Enhancing Throughput in
Collective Tasking Systems

• L. Subramanian
• Randy H.Katz
• Michael J. Franklin

2
Collective Tasking Systems

• Properties -
• Services requests of a predefined set of types
• Every request has an associated type
• All requests of a particular type can be
  aggregated into a single request
• Bottleneck operation of every type is performed
  only once for all requests of that type
• Examples-
• Broadcast disks application of broadcast
  scheduling.
• Reservation systems access to the reservation
  database
• Network Provisioning systems bandwidth brokers
• Front-end Database monitors access point for
  multiple databases
• Disk scheduling systems locality based access in
  disks
• Caching Systems
• Gang Scheduling Multiprocessor systems

3
Aggregate Scheduling
Scheduler
application
bottleneck
List of Queues
OPT
Door
Maintainer
Aggregator
List of Queues A queue of requests for every
type OPT Aggregate Statistics of requests of
every type Doorkeeper Triggers event when a new
request arrives
4
Components in an Aggregate Scheduling System

• Aggregator
• Aggregates requests into types
• Updates OPT data structure
• Informs Maintainer about new event

• Scheduler
• Computes the type with maximum value of OPT
  function
• Computes Aggregate request for all requests of
  that type
• Schedules that type to the application

• Maintainer
• Uses an optimization function for types
• Maintains the invariant property of OPT for new
  events

• OPT
• Data Structure optimized for the optimization
  metric
• Every optimization metric induces an invariant
  in OPT

5
Optimization Metrics

• RxW scheduling
• (of Requests) (Max Waiting Time)
• Approximate RxW
• Apply RxW for reduced set of types
• Kinetic Tournaments
• Total waiting time for requests in a queue
• Gang Scheduling
• Associate distance metric between processes
  (frequency of IPC)
• Schedule group of processes with min value of max
  distance
• The Cost Dimension
• Cost associated with every type (cost of
  bottleneck operation)
• Costs can be dynamic (eg. disk scheduling)
• Fagins work on fuzzy systems
• Other variants
• Bounded queue size (admission control)
• Bounded response time (earliest deadline)

6
Network Provisioning System

• 12 basic domains in ATTs backbone
• 10 of bandwidth reserved(statistically) for
  VoIP and VPNs.
• A provisioning system accepts inter-domain
  requests and reserves along a path.
• All requests between a pair of domains are
  aggregated into a single request.
• Regulate traffic for the reserved portion.

7
Throughput Block Rate Characteristics
8
Response Time Characteristics
9
Conclusions

• RxW and Kinetic tournaments give much better
  performance than FIFO
• RxW vs Kinetic Tournaments(KT)
• RxW has slightly higher throughput than KT
• KT has much lesser response time at operating
  range
• Variation of response time in KT is restricted
• Max response time of KT is very low (6 times)
• RxW has starvation problem
• Experiment aggregate scheduling for other
  collective tasking systems