Energy consumption of TAGS in a heterogeneous environment under unknown service demand

This paper models the task assignment based on guessing size (TAGS) job allocation algorithm using Markovian processing algebra; PEPA. It aims to analyse performance and energy consumption. The working environment is assumed be heterogeneous, distribution a two phase hyper-exponential. Furthermore, queues are bounded. A nodes system implemented with exponentially distributed incoming tasks. We analysed metrics consumption under different arrival rates. found TAGS can perform well improve performance, although it increases total Finally, we calculated per evaluate in heterogeneous environment, demonstrated that reduces when heavy load.