IOWN

Functions and Characteristics

Simply replacing electricity with light will not achieve IOWN's lofty goals. It is necessary to review network and computer systems. Many points that can be improved in terms of energy efficiency in existing methods.

For example, in packet communication (TCP/IP protocol), which is currently the mainstream network method, data is always divided into packets, and the destination is added to each packet. Each point in the network (router) verifies the packet destination. This has to be switched back to electricity, even if you‘re using fiber for transmission. The IOWN All-Photonics Network (APN) rethinks this and completes all communications using optical communication without being switched back to electricity. By eliminating the need for data division and electrical conversion, ultra-low latency networks can be achieved.

Some improvements can also be made in computer architectures from the standpoint of energy efficiency. IOWN’s Data-Centric Infrastructure (DCI), which serves as the computing infrastructure for the IOWN era, can reduce power consumption through two approaches.

The first is disaggregated computing. A server is usually a single box filled with many components, but this approach breaks the system down so that the internal components can be shared. This allows you to combine and use only the components you need, such as CPUs and memory. It also enables you to turn off the power to components that are not in use, reducing power consumption. It is similar to first taking the system apart and then reorganizing it at the component level.

The second is photonics–electronics convergence. By replacing the electronic circuits that handle electrical signals with optical waveguides, DCI can reduce the power that was previously consumed by electrical wiring.

Overall optimization of different metrics

IOWN uses APN to transmit a far more variety and volume of information and process it through ICT to understand the current state of the world and society in more detail and predict the future. This will help to realize a world in which we can achieve well-being, but we are faced with the question of whether a single evaluation function can express the good and bad of this world.

We believe that conflicting values exist in this world and society in the form of competing values. We believe that it is important to accept this contradiction and embrace diversity and that this is an important point in building a world where we achieve well-being. We aim to achieve this by deriving solutions that are acceptable to each of the different indicators, even if they are not optimal for each of them.

Digital Twin Computing (DTC) is the key to achieving this. DTC is a technology that takes all the objects and phenomena in the world as a Digital Twin, predicts the future through various simulations, and seeks a harmonious solution, and psychology.

Observing, collecting, and using information on a large scale is no easy task. To do this sustainably, flexible control of ICT resources is also crucial. In this role is the Cognitive Foundation (CF), a set of functions that harmonize ICT resources holistically and optimally to distribute the necessary information. It is a technology that enables information to be handled in accordance with the location, application, environment, etc., without regard to the method or the operator.

Photonics-Electrics Convergence Devices and IOWN Roadmap

In the field of photonics-electrics convergence devices, we expect to see several leaps forward with this innovation. At IOWN1.0, we launched the All-Photonics Network (APN) service and achieved a delay target of 1/200 (Figure 2). The IOWN2.0 is a board-connected photoelectric device that advances the IOWN into the computer realm. It enables more flexible assembly of parts than ever before while achieving a highly energy-efficient computer. IOWN3.0 targets 125 times capacity and IOWN4.0 targets 100 times power efficiency. (Figures 2 and 3)