# Integrated Photonics for IoT, RoF, and Distributed Fog-Cloud Computing: A Comprehensive Review
## 7 Industry Implementations
AWS is also funding research into hybrid InP/Si photonic integration to extend performance into longer reach links [99], and evaluating photonic tensor cores for low-latency inference tasks within their serverless compute platforms [67]. These initiatives reflect a broader strategy to maintain infrastructure leadership amid rapidly growing AI/ML workloads. The global photonic ecosystem is rapidly evolving thanks to a vibrant startup landscape and strategic initiatives by regional governments. Startups such as Ayar Labs, Lightmatter, Rockley Photonics, and Optalysysys are leveraging programmable photonics, optical interconnects, and neuromorphic architectures to create domain-specific accelerators and compact sensor platforms [91; 100; 101]. These firms bridge the gap between research and industrial deployment by using open-access design platforms and collaborative prototyping models. Supporting this transition, open-foundry initiatives like IMEC's Europractice, AIM Photonics in the US, JePPIX in Europe, and Ligentec for SiN-based platforms provide cost-effective access to fabrication through multi-project wafer (MPW) runs [91; 102]. Additionally, public-private consortia such as the European Union's PIXAPP and PhotonHub Europe [103] and U.S. government programs under DARPA's LUMOS and iFAB [104] are accelerating the commercialization pipeline by standardizing packaging, offering design kits, and expanding photonic design education. Together, these efforts are democratizing PIC development and supporting its broader adoption in Fog, Cloud, and edge computing infrastructures. Despite rapid progress, the widespread industrial deployment of photonic integrated circuits still faces key bottlenecks across multiple dimensions. Thermal sensitivity remains a major challenge, especially for silicon and III-V platforms, where temperature fluctuations  
Figure 12: Photonic integrated hardware and control architecture of multipurpose programmable photonic circuits, taken from [93]. **(a)** Number of integrated phase shifters in recent waveguide mesh circuits. **(b)** Labeled field-programmable photonic gate array (FPPGA) architecture, including a waveguide mesh core and high-performance building blocks. **(c)** FPPGA core employing a longitudinally parallel hexagonal waveguide mesh interconnection topology. **(d)** Electronic control subsystem, signals, and software procedures to control the programmable photonic integrated circuit. **(e)** Data array representing the full scattering matrix of the FPPGA core, encompassing input and output spatial ports and optical spectral dimensions. induce refractive index changes that degrade performance and stability [105]. Packaging and fiber-chip coupling also represent significant hurdles: grating couplers, edge couplers, and photonic wire bonding introduce insertion losses that affect system-level efficiency [106]. Manufacturing variability, particularly lithographic and etching errors during wafer fabrication, leads to component mismatch and yield loss, although recent advances in inverse design and digital calibration offer partial remedies [107]. Testing is another bottleneck, as high-throughput wafer-level characterization tools for photonics are still underdeveloped compared to electronic ICs [108]. These challenges highlight the need for co-optimization across materials, fabrication, packaging, and electronic-photonic co-design to unlock the full potential of PICs in large-scale distributed systems. Figure 13 illustrates the concept and implementation of hybrid multi-chip modules (MCMs) enabled by 3D nano-printing of photonic wire bonds (PWBs) [82]. Panel (a) shows a conceptual eight-channel transmitter module where PWBs, depicted in red, efficiently interconnect photonic integrated circuits (PICs) fabricated on different material platforms, such as InP lasers and silicon photonic modulators.