Run-Time Task Allocation Considering User Behavior in Embedded Multiprocessor Networks-on-Chip

In this paper, we propose a run-time strategy for allocating application tasks to embedded multiprocessor systems-on-chip platforms where communication happens via the network-on-chip approach. As a novel contribution, we incorporate the user behavior information in the resource allocation process; this allows the system to better respond to real-time changes and to adapt dynamically to different user needs. Several algorithms are proposed for solving the task allocation problem while minimizing the communication energy consumption and network contention. When the user behavior is taken into consideration, we observe more than 70% communication energy savings (with negligible energy and run-time overhead) compared to an arbitrary contiguous task allocation strategy.

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