We ask questions all the time, since old times. Most of the time we ask: Who?When?Where?What? What? How? However, we have been puzzled about the causality behind these questions. One of the key topics is about Time.
According to wikipedia, Time is the continued sequence of existence and events that occurs in an apparently irreversible succession from the past, through the present, and into the future. Actually, no matter while in the industrial revolution that we invent the clock to record this sequence, or while we redefine the standard of chronology through Atomic clock, the key is time is a chronological sequence behind events. Einstein definitely elevated a lot of our cognification of Time and so did Nikamoto Satoshi, who leveraged timestamp as a key role in the distributed money system. So at least now, we are open to redefine this sequence of time in different systems.
Thanks for all the inspirations, it is these causal links happening before to stimulate lots of sparks when we think about the next generation of communication networking systems. A civilization needs icons and communications as a must, and our revolutions surely need the reimagination or reinvention of communication systems, especially in the modern world, the telecommunication and internet built on TCP/IP protocols did change the technical, economic and cultural structure of our society. The term “digital nomad” is very interesting, which describes some edge lifestyles of our new generations.
However, the problem of TCP/IP protocols is that they don’t deliver trust during the messaging process in the network.
There are several consequences of this, one is that the cost of preventing the service providers from monitoring or censershiping or hiding the messaging in the system is pretty high, and we definitely need the society and community to cover that in a very hidden way.
The second is that there is no well-accepted economic model generated from the internal system, not from outside. The key of the previous system is the effectiveness of delivering the message from A point to B point, but to generate some trust in the network. As a result, protocols in the long run will be over controlled by the applications. The centralized situation of the Internet now definitely is too obvious, leading to the misty atmosphere of our information delivering and consuming. We are too easy to hide from the truth. Our power to make wise decision making according to the true messages are weakened.
The third is that potential innovations combining trust with communication are blocked. This is not obvious, but definitely is the most significant one. Imganitions and inventions surely are the key drive of our evolutions. In the last 15 years, we already say that a trust-minimized system could change the money system and financial system like Bitcoin and Ethereum did. If we could combine trust with communication at a very fundamental level or base layer, definitely the whole decentralized society could be reimagined. There will be too many disruptive applications coming out which we even can’t name as decentralized social media? decentralized intention economy? decentralized amazon? Without benchmarking these old terms, we cannot even describe these applicable inventions.
These are the initial thoughts on how to reinvent a decentralized or trust-minimized communication networking system from zero. Since day 1, we want to think a little differently than the blockchains. The reason definitely is that the communication system and financial system are different ,and the trust-level of these two systems are different too. We don’t need to guarantee the global strong consensus in the communications systems, which is too energy consuming. Also, the double spend problem is not the priority one at day1. So, basically in the last three years, we have been discussing different ways to address this middle-level trust model.
Let’s relay more real world scenarios. For example, if we messaged each other on whatsapp for a long time, can we build some consensus now? if we pay the bill, could we care about the memo of that payment or not? if we randomly come out to the beach could we judge the strangers by trust or now? We think the social interactions are very similar to transactions but not the same. But there are too many social or communicating or transaction-affiliating scenarios that need these middle-level trust models.
To address this middle-level trust model problem of communication systems, we introduced verifiable causality graphs to generate irreversible sequencing in the system. The causality graphs are constructed by verifiable logic clocks which are described in our Chrono paper. Basically causality graphs are more like a verifiable ordering, which mathematically describes as a special kind of DAG.
The key reasons here are:
1) We need some theoretically novel and solid foundation to generate trust. Causality Graphs are constructed by a logic clock which is introduced by Leslie Lamport, which is very simple and solidly designed in logic. Actually, this is the most beautiful way to redefine the ordering we ever see in system science. Based on his work, we made some novel changes to the logic clock, which could make it fault-tolerant in distributed systems. Our new causality graph will be verifiable and sustainable to fit the BFT environment of distributed systems. The systematic security of causality graphs could solve fast-frequency trust problems in security.
2) Causality graphs don’t give a strong global guarantee, since the key parts are partial ordering, which makes the network pretty robust and diverse. Unlike global consensus, causality graphs don’t guarantee too much, which is also a good fit for fast and middle-level trust communication scenarios. When multiple parties are communicating in the network, the internal ordering could be recorded and verified, even if some of the nodes failed or did evil, the whole distributed network could still maintain some level of ordering. The developers also may not override or overload the system trust of causality graphs.
3) The scalability of Causality Graphs is pretty obvious, since we could provide more efficient trust in communication systems. This will be huge. The economic efficiency is the key of the trust model solutions, because when it comes to the real adoptions in the long run, this efficiency will generate a strong competitive and sustainable edge. In other words, the marginal cost of causality graphs is very compelling with the previous solutions that could be leveraged on these problems. A faster and cheaper trust model is surely in need for communication systems.
4) The openness of Causality Graphs generates new publicity. We need real public protocols which could involve more possibilities when designing the system. Causality Graphs are more open, not only for diverse developers but also for different levels of trust. This openness will involve more protocols to co-create and co-govern the public protocols, which will bring more innovations not only in applications, economies but also in organizations and governance. This new publicity is based on human interactions.
5) Causality Graphs are more like bridges between people, unlike bridges between things. If we deconstruct human society using a distributed system, the causality graphs would well fit for describing the interactions and connections between humans. Strong locality is one thing, which means we care more about interactions happening near us not far from us. The second point is instant trust, most of the time we care about the connections right now, not in the future or old times. The third is strong intersubjectivity, which means actually since day 1, we are living as us in society. The connections and interactions construct the backbones of our ever evolving social graphs.
Finally, we need next-generation communication systems which could generate internal trust from the fundamental level, by which, our human interactions could be reshaped. The causality graphs could contribute in a very paradigmatic way. The uncertain parts of the network communication could be expected.