Runtime Task Allocation in Multicore Packet Processing Systems

Abstract

Computer networks require increasingly complex packet processing functions in the data plane to adapt to new requirements. To meet performance demands, packet processing systems on routers employ multiple processor cores. To efficiently utilize processing resources in such systems, we propose a novel methodology for allocating tasks to processors. The main idea is to obtain runtime profiling information and to duplicate tasks with heavy processing requirements. Using our duplication algorithm, a balanced workload can be obtained and the complexity of packing tasks with different processing requirements can be reduced. By translating traffic characteristics into processing requirements, the system is able to adapt to dynamic changes in the workload and balance the utilization of all processing resources to maximize system throughput. Our approach can adapt to any traffic change in a single iteration, whereas existing adaptive approaches may require multiple steps. Results from our prototype implementation based on the Click modular router show that our system only requires on average 5.3-31.5 percent of the adaptation steps that are necessary in iterative systems. In addition, our system achieves a throughput that is 1.32 times higher than the throughput achieved with symmetric multiprocessing support with general-purpose task allocation.