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 List of Queues Aggregator OPT Door application bottleneck Maintainer 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) – Fagin’s work on fuzzy systems Other variants – Bounded queue size (admission control) – Bounded response time (earliest deadline)

6. Network Provisioning System 12 basic domains in AT&T’s 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