  Towards addressing spectral scarcity and enhancing resource utilization in 5G
networks, network slicing is a promising technology to establish end-to-end
virtual networks without requiring additional infrastructure investments. By
leveraging Software Defined Networks (SDN) and Network Function Virtualization
(NFV), we can realize slices completely isolated and dedicated to satisfy the
users' diverse Quality of Service (QoS) prerequisites and Service Level
Agreements (SLAs). This paper focuses on the technical and economic challenges
that emerge from the application of the network slicing architecture to
real-world scenarios. We consider a market where multiple Network Providers
(NPs) own the physical infrastructure and offer their resources to multiple
Service Providers (SPs). Then, the SPs offer those resources as slices to their
associated users. We propose a holistic iterative model for the network slicing
market along with a clock auction that converges to a robust
$\epsilon$-competitive equilibrium. At the end of each cycle of the market, the
slices are reconfigured and the SPs aim to learn the private parameters of
their users. Numerical results are provided that validate and evaluate the
convergence of the clock auction and the capability of the proposed market
architecture to express the incentives of the different entities of the system.
