@article{gksw-dlcli-20, author = {Cenk G{\"u}ndogan and Peter Kietzmann and Thomas C. Schmidt and Matthias W{\"a}hlisch}, title = {{Designing a LoWPAN convergence layer for the Information Centric Internet of Things}}, journal = {Computer Communications}, issn = {0140-3664}, volume = {164}, number = {1}, year = {2020}, pages = {114--123}, month = {December}, publisher = {Elsevier}, abstract = {The low-power Internet of Things (IoT) introduces lossy radio links with ultra-constrained frame sizes and high transmission cost for each byte. Information Centric Networking (ICN) is considered a promising communication technology in this regime, as it increases reliability by ubiquitous caching and eases transmission efforts by hop-wise forwarding. Common ICN layers such as NDN, however, were designed for fixed network infrastructure and require an adaptation layer to the constrained wireless - as the common Internet Protocol does. In this paper, we design and evaluate such an ICN convergence layer for low power lossy links that (1) augments the NDN stateful forwarding plane with a highly efficient name eliding, (2) devises stateless compression schemes for standard NDN use cases with utile data encodings, (3) adapts NDN packets to the small MTU size of IEEE 802.15.4, and (4) generates compatibility with 6LoWPAN so that IPv6 and NDN can coexist on the same LoWPAN links. Our findings indicate that stateful compression can reduce the size of NDN data packets by more than 70 \% in realistic examples, while packet fragmentation operates in a predictable way even for high fragment numbers. Our experiments show that for common use cases ICNLoWPAN saves 33 \% of transmission resources over NDN, and about 20 \% over 6LoWPAN.}, url = {https://doi.org/10.1016/j.comcom.2020.10.002}, doi = {10.1016/j.comcom.2020.10.002}, file = {../papers/gksw-dlcli-20.pdf}, theme = {iot|icn}, }