Evolving communication technologies and standards enable novel IoT use cases, such as real-time edge or fog assistance for distributed sensing and control in smart environments. Synchronizing the system state at centralized management entities with distributed components is a network resource-hungry task. Semantic communication is envisioned to cope with rapid network traffic increase and associated performance degradation by optimizing resource utilization for the application goal. Identification (ID) codes are a novel semantic technology that reduces network traffic for remote synchronization by representing a potentially multidimensional system state with a short tag. This work exploits ID codes in the intelligent transportation context. The vehicles in a truck platoon use ID codes to synchronize their distributed control decisions with the centralized edge server. We present one of the first frameworks demonstrating the advantages of using ID codes in practical scenarios. We show that the truck platoon management utilizing ID codes is$\sim 40 {\%}$more efficient than a fully distributed control scenario and never lags behind a fully centralized control. Moreover, ID codes reduce network traffic by$\sim 4$times compared to the latter.

The Interplanetary File System (IPFS) is one of the largest peer-to-peer networks currently in use. In networks with heterogeneous peers, IPFS may take a long time to obtain all packets. Random Linear Network Coding (RLNC) can be added to IPFS to mitigate the effects of the suboptimal requesting strategy, as proposed by the Multi Access Recording System (MARS) protocol. We measure the power consumption, and the file processing and receiving delay for MARS in a test bed and find that MARS introduces significant delay overhead because it encodes its packets only after receiving a request for a file. As a modification of MARS, we propose Storing Coded Packets In-advance for IPFS (SPIFI) that addresses this issue by offloading the computation of the RLNC encoded packets to a point in time before the packets are requested. This way, the power consumption, and the delay incurred by the RLNC encoding does not deteriorate performance at run time. In additional measurements, we find that SPIFI reduces the energy consumption at run time and the data retrieval time compared to both MARS and IPFS. The encoding time can be selected freely, to perform the computation when power grids have spare capacity, avoiding peak loads in the grid. SPIFI works best for small files of a few MB and the benefit vanishes for larger file sizes due to the decoding complexity. If the client only requests single code packets to increase the file redundancy in the network, then SPIFI always outperforms IPFS and MARS.

Identification via channels (ID) is a goal-oriented (Post-Shannon) communications paradigm that verifies the matching of message (identity) pairs at source and sink. To date, ID research has focused on the upper bound$\lambda $for the probability of a false-positive (FP) identity match, mainly through ID tagging codes that represent the identities through ID codeword sets consisting of position-tag tuples. We broaden the ID research scope by introducing novel ID performance metrics: the expected FP-error probability$\overline {p_{\mathrm {fp}}}$which considers distance properties of ID codeword sets in conjunction with the probability for selecting ID pairs, the threshold probabilities$p_{\epsilon }$that characterize quantiles of FP-probabilities, and the distance tail uplift ratio DiTUR giving the fraction of ID pairs whose distance is increased above the minimum distance (which corresponds to$\lambda $). We define a No-Code (NC) approach that directly conducts the ID operations with the messages (identities) without any additional coding as a baseline for ID. We investigate a concatenated Reed-Solomon ID code and a Reed-Muller ID code, and find that they do not always yield advantages over using no ID code. We analytically characterize the reduction of error-prone ID pairs through sending multiple tags. Overall, our insights point to investigating the distance distribution of ID codes and to incorporating the ID pair distributions of real ID systems in future ID research.

Digital Twin (DT) implementations can reduce latency drastically in future communication systems for steering and control of cyber-physical systems (CPS). When the CPS and its DT periodically exchange information to repair possible desynchronisations between the two systems, this can lead to large data traffic flooding the networks. This work proposes a goal-oriented communication approach based on message identification (ID), which only sends repair data when necessary, but adds control traffic and a probability of not repairing some desynchronisations between the two systems. We compare optimal ID codes and a hash function for detection whether desynchronisation correction is necessary. Our method can reduce the traffic to within 0.3% of its optimal value while repairing 99.97% of all desynchronisations for 4 kbit of data and grows even better for larger data.