  The number of smart devices wear and carry by users is growing rapidly which
is driven by innovative new smart wearables and interesting service o erings.
This has led to applications that utilize multiple devices around the body to
provide immersive environments such as mixed reality. These applications rely
on a number of di erent types of functions such as sensing, communication and
various types of processing, that require considerable resources. Thus one of
the major challenges in supporting of these applications is dependent on the
battery lifetime of the devices that provide the necessary functionality. The
battery lifetime can be extended by either incorporating a battery with larger
capacity and/or by utilizing the available resources e ciently. However, the
increases in battery capacity are not keeping up with the demand and larger
batteries add to both the weight and size of the device. Thus, the focus of
this paper is to improve the battery e ciency through intelligent resources
utilization. We show that, when the same resource is available on multiple
devices that form part of the wearable system, and or is in close proximity, it
is possible consider them as a resource pool and further utilize them
intelligently to improve the system lifetime. Speci cally, we formulate the
function allocation algorithm as a Mixed Integer Linear Programming (MILP)
optimization problem and propose an e cient heuristic solution. The
experimental data driven simulation results show that approximately 40-50%
system battery life improvement can be achieved with proper function allocation
and orchestration.
