  In many application areas such as large-scale disaster detection, IoT
networks connote the characteristics of LLN (Low power and Lossy Network). With
few exceptions, prior work on RPL(Routing Protocol for LLN), a standard routing
protocol standardized in the IETF, has focused on the evaluation of various
aspects of routing performances and control overheads. In this paper, we
address the problem of DODAG (Destination Oriented Directed Acyclic Graph)
created by the direct application of RPL. We first evaluate the skewness of
DODAG both via numerical simulations and via actual large-scale testbed. RPL
secures its flexibility and wide applicability by allowing the adoption of
implementer-specific rank definitions and parent selection criteria. In
addition to the metrics used in ContikiRPL and TinyRPL, the two most widely
used open source implementations, we evaluated the skewness of RPL trees
generated by applying various routing metrics. Performance analysis results
show that RPL trees suffer from severe skewness regardless of routing metrics
in both randomly generated networks and in real-world networks. We propose a
novel routing protocol that may improve the balance of RPL trees. Rigorous
performance analysis based on computer simulations shows that our algorithm
improves the tree balance significantly.
