A simple load balancing scheme for task allocation in parallel machines
SPAA '91 Proceedings of the third annual ACM symposium on Parallel algorithms and architectures
Fast and Effective Task Scheduling in Heterogeneous Systems
HCW '00 Proceedings of the 9th Heterogeneous Computing Workshop
Examinating Task Distribution by an Artificial Hormone System Based Middleware
ISORC '08 Proceedings of the 2008 11th IEEE Symposium on Object Oriented Real-Time Distributed Computing
Measuring the quality of an artificial hormone system based task mapping
Autonomics '08 Proceedings of the 2nd International Conference on Autonomic Computing and Communication Systems
Analyzing the Behavior of an Artificial Hormone System for Task Allocation
ATC '09 Proceedings of the 6th International Conference on Autonomic and Trusted Computing
Reliability of an artificial hormone system with self-X properties
PDCS '07 Proceedings of the 19th IASTED International Conference on Parallel and Distributed Computing and Systems
Towards an artificial hormone system for self-organizing real-time task allocation
SEUS'07 Proceedings of the 5th IFIP WG 10.2 international conference on Software technologies for embedded and ubiquitous systems
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Acquiring Self-X properties like self-organization and self-healing is a main goal of Organic Computing - a new and very promising research area. Inspired by nature, Organic Computing research wants to learn and adopt from techniques and properties of nature. The artificial hormone system (AHS), motivated by the hormone system of mammals as a role model, was designed to map tasks on processing elements using artificial hormones. In previous publications, the idea of an organic middleware and first theoretical results were presented. In this paper, we will present ways of improving the performance and minimizing the memory consumption of an AHS implementation.