![](bg6.png)
0
0.2
0.4
0.6
0.8
1
0 0.2 0.4 0.6 0.8 1
xij
xji
j’s constraint
i’s constraint
Ui’
Uj’
Figure 4: The set of feasible allocations and device i and j’s
isoquants that include the allocation that maximizes social
surplus.
rational devices choose to cooperate with one another.
The model is pessimistic in that each device myopi-
cally assumes that its actions will not affect its part-
ner’s future decision, except to wholesale discontinue
trading.
We note that there are frequently better allocations
than the ones that our model arrives. Figure 4 sketches
the set of feasible allocations as well as two new iso-
quants for the devices that maximize the sum of the
devices’ utilities– the social surplus.
We have two reasons to have optimism regarding
more efficient allocation. First, more-forward look-
ing models will likely yield allocations lying deeper
into the lens-shaped region. We are currently inves-
tigating negotiation models where each device rea-
sons about the effects its own offer has in driving the
pair of devices towards a favorable equilibrium allo-
cation. Muthoo discovers that agents that alternate
positions in repeated bargaining situations strive for
more socially optimal allocations whereas in the tradi-
tional single-shot bargaining game, a device receives
more resources the less it values the resource as a re-
sult of brinksmanship. In Muthoo’s repeated bargain-
ing model, the reverse, more socially efficient, effect
manifests (Muthoo, 1999).
The second source of intuition seems paradoxical:
competition will drive allocations to which devices
strongly prefer over not sharing. The idea is that given
the choice of sharing with two devices, a rational de-
cision maker will choose the one that yields a more
desirable allocation. So far, we have only modeled bi-
lateral bandwidth exchange. That competition might
provide sweeter allocations gives us further incentive
to continue our research. It is likely that testing mul-
tilateral exchange will be beyond scope of an analytic
model, so we are currently implementing our band-
width allocation policies inside the ns network simu-
lator.
That even a pessimistic model can motivate devices
to exchange bandwidth motivates us to further study
incentives for participation in cooperative networks.
We are excited to investigate foresighted models of
exchange as well as multilateral exchange to motivate
more efficient exchange and to study larger networks.
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