Quantitative system performance: computer system analysis using queueing network models
Quantitative system performance: computer system analysis using queueing network models
Virtual clock: a new traffic control algorithm for packet switching networks
SIGCOMM '90 Proceedings of the ACM symposium on Communications architectures & protocols
Decay-usage scheduling in multiprocessors
ACM Transactions on Computer Systems (TOCS)
An Opportunity Cost Approach for Job Assignment in a Scalable Computing Cluster
IEEE Transactions on Parallel and Distributed Systems
Virtual-Time Round-Robin: An O(1) Proportional Share Scheduler
Proceedings of the General Track: 2002 USENIX Annual Technical Conference
A resource-allocation queueing fairness measure
Proceedings of the joint international conference on Measurement and modeling of computer systems
Process prioritization using output production: Scheduling for multimedia
ACM Transactions on Multimedia Computing, Communications, and Applications (TOMCCAP)
Surplus fair scheduling: a proportional-share CPU scheduling algorithm for symmetric multiprocessors
OSDI'00 Proceedings of the 4th conference on Symposium on Operating System Design & Implementation - Volume 4
Lottery scheduling: flexible proportional-share resource management
OSDI '94 Proceedings of the 1st USENIX conference on Operating Systems Design and Implementation
A unified framework for max-min and min-max fairness with applications
IEEE/ACM Transactions on Networking (TON)
A global scheduling framework for virtualization environments
IPDPS '09 Proceedings of the 2009 IEEE International Symposium on Parallel&Distributed Processing
Improved Forwarding Architecture and Resource Management for Multi-Core Software Routers
NPC '09 Proceedings of the 2009 Sixth IFIP International Conference on Network and Parallel Computing
The Resource Usage Aware Backfilling
Job Scheduling Strategies for Parallel Processing
Design and implementation of a generic resource sharing virtual time dispatcher
Proceedings of the 3rd Annual Haifa Experimental Systems Conference
Redline: first class support for interactivity in commodity operating systems
OSDI'08 Proceedings of the 8th USENIX conference on Operating systems design and implementation
On the feasibility of dynamic rescheduling on the Intel Distributed Computing Platform
Proceedings of the 11th International Middleware Conference Industrial track
Dominant resource fairness: fair allocation of multiple resource types
Proceedings of the 8th USENIX conference on Networked systems design and implementation
No justified complaints: on fair sharing of multiple resources
Proceedings of the 3rd Innovations in Theoretical Computer Science Conference
Multi-resource fair queueing for packet processing
Proceedings of the ACM SIGCOMM 2012 conference on Applications, technologies, architectures, and protocols for computer communication
Proceedings of the 11th International Conference on Autonomous Agents and Multiagent Systems - Volume 2
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System bottlenecks, namely those resources which are subjected to high contention, constrain system performance. Hence effective resource management should be done by focusing on the bottleneck resources and allocating them to the most deserving clients. It has been shown that for any combination of entitlements and requests a fair allocation of bottleneck resources can be found, using an off-line algorithm that is given full information in advance regarding the needs of each client. We extend this result to the on-line case with no prior information. To this end we introduce a simple greedy algorithm. In essence, when a scheduling decision needs to be made, this algorithm selects the client that has the largest minimal gap between its entitlement and its current allocation among all the bottleneck resources. Importantly, this algorithm takes a global view of the system, and assigns each client a single priority based on his usage of all the resources; this single priority is then used to make coordinated scheduling decisions on all the resources. Extensive simulations show that this algorithm achieves fair allocations according to the desired entitlements for a wide range of conditions, without using any prior information regarding resource requirements. It also follows shifting usage patterns, including situations where the bottlenecks change with time.