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Task-Allocation in a Large Scaled Hierarchical Many-Core Topology

As more and more electronic devices get connected together, whole systems get more complicated in terms of development, maintenance and usage. New principles in design are needed to cope with this complexity. That is why we developed the Artificial Hormone System (AHS). The AHS enables an autonomous and decentralized task-allocation among a set of Processing Elements (PEs). The AHS works good in small scaled non-hierarchical scenarios. For larger scaled and hierarchical scenarios we developed the Hierarchical Artificial Hormone System (HAHS) and presented a first abstract concept of the Recursive Artificial Hormone System (RAHS). Both utilize the AHS in isolated smaller clusters of PEs to achieve the same functionality as the AHS with less communication. Thus, the whole task-set will be split to smaller and disjoint task-subsets which then will be distributed to the clusters. The HAHS uses a 2-Level hierarchy with a second regulation cycle between all clusters. The RAHS on the other hand is designed to manage a N-Level hierarchy. In this paper we will present the first implemented version of the RAHS, its evaluation and the comparison to the original AHS.