  Task offloading to mobile edge computing (MEC) has emerged as a key
technology to alleviate the computation workloads of mobile devices and
decrease service latency for the computation-intensive applications. Device
battery consumption is one of the limiting factors needs to be considered
during task offloading. In this paper, multi-task offloading strategies have
been investigated to improve device energy efficiency. Correlations among tasks
in time domain as well as task domain are proposed to be employed to reduce the
number of tasks to be transmitted to MEC. Furthermore, a binary decision tree
based algorithm is investigated to jointly optimize the mobile device clock
frequency, transmission power, structure and number of tasks to be transmitted.
MATLAB based simulation is employed to demonstrate the performance of our
proposed algorithm. It is observed that the proposed dynamic multi-task
offloading strategies can reduce the total energy consumption at device along
various transmit power versus noise power point compared with the conventional
one.
