  For future wireless networks, enormous numbers of interconnections are
required, creating a disorganized topology and leading to a great challenge in
data aggregation. Instead of collecting data individually, a more efficient
technique, computation over multi-access channels (CoMAC), has emerged to
compute functions by exploiting the signal-superposition property of wireless
channels. However, the implementation of CoMAC in disorganized networks with
multiple relays (hops) is still an open problem. In this paper, we combine
CoMAC and orthogonal communication in the disorganized network to attain the
computation of functions at the fusion center. First, to make the disorganized
network more tractable, we reorganize the disorganized network into a
hierarchical network with multiple layers that consists of subgroups and
groups. In the hierarchical network, we propose multi-layer function
computation where CoMAC is applied to each subgroup and orthogonal
communication is adopted within each group. By computing and communicating
subgroup and group functions over layers, the desired functions are
reconstructed at the fusion center. The general computation rate is derived and
the performance is further improved through time allocation and power control.
The closed-form solutions to optimization are obtained, which suggest that
existing CoMAC and orthogonal communication schemes can be generalized.
