  5G mobile networks encompass the capabilities of hosting a variety of
services such as mobile social networks, multimedia delivery, healthcare,
transportation, and public safety. Therefore, the major challenge in designing
the 5G networks is how to support different types of users and applications
with different quality-of-service requirements under a single physical network
infrastructure. Recently, network slicing has been introduced as a promising
solution to address this challenge. Network slicing allows programmable network
instances which match the service requirements by using network virtualization
technologies. However, how to efficiently allocate resources across network
slices has not been well studied in the literature. Therefore, in this paper,
we first introduce a model for orchestrating network slices based on the
service requirements and available resources. Then, we propose a Markov
decision process framework to formulate and determine the optimal policy that
manages cross-slice admission control and resource allocation for the 5G
networks. Through simulation results, we show that the proposed framework and
solution are efficient not only in providing slice-as-a-service based on the
service requirements, but also in maximizing the provider's revenue.
