摘要： 针对嵌入式软件算法级能耗的优化问题，建立算法级能耗估算模型。以旅行商问题(TSP)为例，采用神经网络算法、遗传算法等进行能耗求解，对求解过程中的算法执行次数、算法复杂度以及运行时间这3个特征值进行能耗分析，通过能耗估算模型计算出算法针对TSP问题的能耗估算值，并将该估算值与使用sim-panalyzer功耗仿真平台求解得到的能耗测试值进行比较，结果表明，能耗测试值与估算值的误差在10%左右，证明该能耗估算模型具有较高的准确性。

关键词: 嵌入式系统, 能耗设计, 算法级, 能耗建模, 神经网络, 遗传算法

Abstract: An algorithm-level energy consumption estimation model is proposed in this paper to solve the problem of algorithm-level energy consumption optimization design of embedded software. This paper takes Traveling Salesman Problem(TSP) as an example and uses different algorithms such as neural network algorithm and Genetic Algorithm(GA) for solving energy consumption estimation problem. By analyzing execution times, algorithm complexity and run time, energy consumption estimation value of different algorithms calculated by this model can be used to compare with energy consumption test value gained by simulation platform. Experimental result by simulation platform sim-panalyzer is presented that error analysis between estimation value and test value is about 10%. The accuracy of energy consumption estimation model is proved.

Key words: embedded system, energy consumption design, algorithm-level, energy consumption modeling, neural network, Genetic Algorithm(GA)

中图分类号: 

• TP311.5