  Discovery of nodes and content in large-scale distributed systems is
generally based on Kademlia, today. Understanding Kademlia-type systems to
improve their performance is essential for maintaining a high service quality
for an increased number of participants, particularly when those systems are
adopted by latency-sensitive applications.
  This paper contributes to the understanding of Kademlia by studying the
impact of \emph{diversifying} neighbours' identifiers within each routing table
bucket on the lookup performance. We propose a new, yet backward-compatible,
neighbour selection scheme that attempts to maximize the aforementioned
diversity. The scheme does not cause additional overhead except negligible
computations for comparing the diversity of identifiers. We present a
theoretical model for the actual impact of the new scheme on the lookup's hop
count and validate it against simulations of three exemplary Kademlia-type
systems. We also measure the performance gain enabled by a partial deployment
for the scheme in the real KAD system. The results confirm the superiority of
the systems that incorporate our scheme.
