Throughput-centric routing algorithm design
Proceedings of the fifteenth annual ACM symposium on Parallel algorithms and architectures
Queueing Dynamics and Maximal Throughput Scheduling in Switched Processing Systems
Queueing Systems: Theory and Applications
Achieving stability in networks of input-queued switches
IEEE/ACM Transactions on Networking (TON)
Services Computing: Grid Applications for Today
IT Professional
Autonomic Computing: Research Challenges and Opportunities
ICPS '04 Proceedings of the The IEEE/ACS International Conference on Pervasive Services
Maximum Pressure Policies in Stochastic Processing Networks
Operations Research
Near-Optimal Worst-Case Throughput Routing for Two-Dimensional Mesh Networks
Proceedings of the 32nd annual international symposium on Computer Architecture
An Architectural Approach to Autonomic Computing
ICAC '04 Proceedings of the First International Conference on Autonomic Computing
Utility Functions in Autonomic Systems
ICAC '04 Proceedings of the First International Conference on Autonomic Computing
Autonomic Pervasive Computing Based on Planning
ICAC '04 Proceedings of the First International Conference on Autonomic Computing
Services and Autonomic Computing: A Practical Approach for Designing Manageability
SCC '05 Proceedings of the 2005 IEEE International Conference on Services Computing - Volume 02
Packet scheduling across networks of switches
ICN'05 Proceedings of the 4th international conference on Networking - Volume Part I
Dynamic power allocation and routing for time-varying wireless networks
IEEE Journal on Selected Areas in Communications
Self-Optimization module for Scheduling using Case-based Reasoning
Applied Soft Computing
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Autonomic computing networks manage multiple tasks over a distributed network of resources. In this paper, we view an autonomic computing system as a network of queues, where classes of jobs/tasks are stored awaiting execution. At each point in time, local resources are allocated according to the backlog of waiting jobs. Service modes are selected corresponding to feasible configurations of computing (processors, CPU cycles, etc.), communication (slots, channels, etc.) and storage resources (shared buffers, memory places, etc.) We present a family of distributed algorithms which maximize the system throughput by dynamically choosing service modes in response to observed buffer backlogs. This class of policies, called projective cone scheduling algorithms, are related to maximum pressure policies in constrained queueing networks, and are shown to maintain stability under any arrival combination within the network capacity. They operate without knowledge of the arrival rates and require minimal information sharing between regions.