The usage of mobile devices like
cell phones, navigation systems, or laptop computers, is limited by
the lifetime of the included batteries. This lifetime depends naturally
on the rate at which energy is consumed, however, it also depends on the
usage pattern of the battery. Continuous drawing of a high
current results in an excessive drop of residual capacity. However, during
intervals with no or very small currents, batteries do recover to a certain extend.
We model this complex
behaviour with an inhomogeneous Markov reward model,
following the approach of the so-called Kinetic battery Model (KiBaM).
reward rates thereby correspond to the power consumption of the attached
device and to the available charge, respectively. We develop a tailored
algorithm for the computation of the distribution of the
consumed energy and show how different
workload patterns influence the overall lifetime of a battery.
|Publisher||IEEE Computer Society Press|
|Conference||37th Annual IEEE/IFIP International Conference on Dependable Systems and Networks (DSN), Edinburgh, UK|
|Period||1/06/07 → …|
- Markov reward models