Given the nature of the network and the requirements of the applications, the
following are the key goals of CEDAR.
(a) Route computation must be distributed because centralized routing in
a dynamic network is impossible even for fairly small networks.
(b) Route computation should not involve the maintenance of global state,
or even significant amounts of volatile non-local state. In particular, link
state routing is not feasible for highly dynamic networks because of the
significant state propagation overhead when th e network topology changes.
(c) As few nodes as possible must be involved in state propagation and
route computation, since this involves monitoring and updating at least some
state in the network. On the other hand, every host must have quick access
to routes on-demand.
(d) Each node must only care about the routes corresponding to its
destination, and must not be involved in frequent topology updates for parts
of the network to which it has no traffic.
(e) Stale routes must be either avoided, or detected and eliminated
quickly.
(f) Broadcasts must be avoided as far as possible because broadcasts are
highly unreliable in ad-hoc networks.
(g) If the topology stabilizes, then routes must converge to the optimal
routes.
(h) It is desirable to have a backup route when the primary route has
become stale and is being recomputed.
(i) Applications provide a minimum bandwidth requirement for a
connection, and the routing algorithm must efficiently compute a route that
can satisfy the bandwidth requirement with high probability.
(j) The amount of state propagation and topology update information must
be kept to a minimum. In particular, every change in available bandwidth
should not result in updated state propagation.
(k) Dynamic links (either unstable or low bandwidth links) must not cause
state propagation throughout the network. Only stable high bandwidth link
information must be propagated throughout the network.
(l) The QoS route computation algorithm should be simple and robust.
Robustness, rather than optimality, is the key requirement.
