Introduction to the Special Issue on Evolution of IoT Networking Architectures

We are pleased to bring to you the ACM ToIT Special Issue on “Evolution of IoT Networking Architectures.” The Internet of Things (IoT) has resulted in environments that must manage large amounts of data generation, the placement and migration of computation and storage, and the need to support distributed queries and ubiquitous analytics. This special issue has gathered leadingedge scientific research and insights on the impact the IoT has had on the evolution of communication architectures and protocols; how best to support diverse communication requirements in the context of different IoT scenarios, ranging from industrial to consumer-based IoT; how to adequately define and address interoperability, within and across different layers in the network architecture, leveraging cross-layer design; and, finally, how to design a more unified next generation Internet architecture and end-to-end protocol stack, given the increasing numbers of wireless and mobile devices. The special topic received a total of 21 submissions, out of which 10 articles have been selected. The articles cover a broad range of IoT networking architectural topics: efficient and automated communication in wireless and wired environments, offloading of applications in mobile environments, security, and interoperability. The first set of articles concentrate on more efficient and automated communications in heterogeneous IoT environments. E. Marcel et al. propose an admission control strategy based on online learning of the requested popularity distribution for Fog/Cloud environments that is detailed in “Efficient Latency Control in Fog Deployments via Hardware Accelerated Popularity Estimation.” Their admission control scheme has been implemented on FPGA hardware using Ageing Bloom Filters for memory efficiency, showing interesting performance improvements with guaranteed throughput and latency for specific scenarios. In the article “To Transmit or Not to Transmit: Controlling Communications in the Mobile IoT Domain,” K. Panagidi et al. describe a time-optimized, dynamic, and distributed decision-making mechanism based on the principles of the Optimal Stopping and Change-Detection theories to efficiently control the exchange of messages in IoT environments. In “Parameter Self-Adaptation for Industrial Wireless Sensor-Actuator Networks,” M. Sha et al. propose a parameter selection and adaptation framework to optimally configure network parameters in Wireless Sensor-Actuator Networks (WSAN) based on application requests and allowing for dynamic configuration adaptation during runtime. X. Deng et al., in “Receivers Optimal Placement for K Barriers Coverage in Passive Bistatic Radar Sensor Networks,” focus on the problem of constructing multiple barriers coverage to improve the coverage quality in wireless sensor networks, specifically focusing on passive bistatic radar sensor networks. The authors focus on the minimum number of receiver problems assuming a number of pre-deployed transmitters and non-cooperative environments.