  Forwarding decisions in classical IP-based networks are predetermined by
routing. This is necessary to avoid loops, inhibiting opportunities to
implement an adaptive and intelligent forwarding plane. Consequently, content
distribution efficiency is reduced due to a lack of inherent multi-path
transmission. In Named Data Networking (NDN) instead, routing shall hold a
supporting role to forwarding, providing sufficient potential to enhance
content dissemination at the forwarding plane. In this paper we design,
implement, and evaluate a novel probability-based forwarding strategy, called
Stochastic Adaptive Forwarding (SAF) for NDN. SAF imitates a self-adjusting
water pipe system, intelligently guiding and distributing Interests through
network crossings circumventing link failures and bottlenecks. Just as real
pipe systems, SAF employs overpressure valves enabling congested nodes to lower
pressure autonomously. Through an implicit feedback mechanism it is ensured
that the fraction of the traffic forwarded via congested nodes decreases. By
conducting simulations we show that our approach outperforms existing
forwarding strategies in terms of the Interest satisfaction ratio in the
majority of the evaluated scenarios. This is achieved by extensive utilization
of NDN's multipath and content-lookup capabilities without relying on the
routing plane. SAF explores the local environment by redirecting requests that
are likely to be dropped anyway. This enables SAF to identify new paths to the
content origin or to cached replicas, circumventing link failures and resource
shortages without relying on routing updates.
