Bio-inspired distributed task remapping for multiple video stream decoding on homogeneous NoCs

Centralised management of distributed systems require a significant amount of monitoring traffic to maintain an accurate view of the system global state. The communication overhead of these systems becomes a bottleneck as the number of processing elements in the network and workload increase. State-of-the art in decentralised resource management techniques address this issue by allowing individual or clusters of nodes to make decisions at runtime to manage the dynamic workload. The primary contribution of this paper is using a bio-inspired, distributed, task remapping technique to manage dynamic multiple video stream decoding workloads. Our proposed technique has a low-communication overhead and is used to reduce the cumulative job lateness of the video streams. Secondary contributions include, several improvements to an existing clusterbased resource management approach to introduce awareness of task blocking and relocation distance. We evaluate these two remapping methods by comparing the improvement of job lateness, communication overhead and distribution of utilisation via simulation of several workload patterns.