Evan Forbes：Zcash 區塊變大，網路如何跟上？
Multi-Gigabit Zcash
- Evan Forbes Valar Group
影片
影片與逐字稿來源：Network State Podcast （CC BY）
場次摘要
Valar Group 工程師 Evan Forbes 介紹 Zcash 網路層的擴充難題。密碼學與隱私查詢之外，節點仍得快速傳播區塊，才能提高交易量並縮短等待時間。他說，區塊傳播過慢會增加同時產塊造成的衝突，影響礦工收益；團隊正研究接近 DAG 的處理方式。
值得記下的 5 件事
- Zakura 全節點的重點是讓 Zcash 區塊更大、傳播更快。
- 證明、錢包查詢、吞吐量與延遲是不同瓶頸，需要各自處理。
- 動態學習高吞吐量、低延遲的傳播路徑，有機會兼顧網路穩定性與速度。
- 礦工同時產塊可能造成收益損失，這限制了縮短出塊時間。
- DAG 與改編自 Autobahn 的設計，目標是減少同時產塊衝突並提高吞吐量。
逐字稿
開場
大家好。我是 Zcash 的工程師。Zcash 開發很分散，名詞有時會混。更具體說，我在 Valar Group；再具體，我做 Zakura，這是高效能 Zcash 全節點；再具體，我負責把區塊做大、做快。Hello. So I'm an engineer on Zcash. Zcash's development is very decentralized, so the taxonomy can be a little bit confusing. But more specifically than Zcash, I work at Valar Group. More specifically than that, I work on Zakura, which is the really high-performance Zcash full node, and then more specifically than that, I make the blocks big and fast.
我們真正想要的是像 Zcash 這樣的支付系統：無許可、抗審查、保留隱私。這很難，因為瓶頸散落在不同領域。So what we really want is these payment systems that work like Zcash. So they're permissionless, they're censorship-resistant, and they preserve privacy. And this is really difficult because there's so many different bottlenecks in different areas.
如今天其他講者，我們有 Tachyon、有 PIR，分別對不同瓶頸；密碼與隱私這邊還有吞吐，讓全世界同時用 Zcash，還有延遲，讓它真的好用。So as other speakers have presented today, we have things like Tachyon and we have things like PIR, which those things address different bottlenecks, and then around, like, cryptography and privacy. Along with that, we have bottlenecks around throughput so that everyone in the world can use Zcash at the same time, and then we have latency so that it's actually usable.
你去付任意東西，要很快。這是我們夢想、熟悉、也期待支付系統該有的 UX，就得這麼快。其中一個瓶頸是區塊傳播。When you go to, like, pay for any random item, it's quite quick. So this is, like, the UX that we all sort of dream about and know and are used to and expect out of our payment systems. It has to be, like, this fast. One of the bottlenecks is block propagation.
區塊傳播與穩健性
這決定區塊能多大；越大吞吐越高。Zcash 以前不太需要那麼高吞吐或那麼低延遲，但需要穩健。想區塊傳播協議時通常有取捨。So this is how big the block can get. The bigger you can make it, the higher throughput it is. And Zcash previously didn't really need that high of throughput or that low of latency. However, it did need this robustness. So there's typically these trade-offs when we think about these block propagation protocols.
穩健是指資料可從網路任意點進入、拓樸可任意變化；網路會壅塞、不可預測地變。Zcash 得扛住任意配置，這很難。Robustness is where data can enter the network at any given point, and the topology of the network can change arbitrarily. Networks get congested, and they change in unpredictable ways. So Zcash has to be able to handle any arbitrary configuration there, and this is quite difficult.
我們先求穩健，不太想吞吐或延遲；基本上是 pull 協議，若你熟悉這類協議：慢、低吞吐，但相當穩。So the first thing that we optimized for was just robustness. We didn't really have to think about throughput or latency, and this is basically a— if you're familiar with these protocols, it's a pull-based protocol. It's quite slow, quite low-throughput, but works pretty, pretty dang well.
但我們其實可以保留「網路當下長怎樣都行」的穩健，同時動態學習資料該走吞吐最高、延遲最低的路徑。However, we can actually preserve that robust quality of where the network can kind of look however it needs to look in that moment, and we can learn on the fly what's the highest-throughput and lowest-latency path for the data to take.
魚群路由與千兆吞吐
想像魚群或鳥群飛，網路大概就長這樣。我們遵循少數簡單規則，即使只有局部視野，也能找到（或接近）最高吞吐、最低延遲的路。So this is, like, if you imagine, like, a school of fish or a swarm of, like, birds flying, this is more or less what the network looks like. We follow a few simple rules, and from those rules, even though we only have a local view, we can find the highest-throughput, lowest-latency path, or at least close.
這會來到你附近的測試網：千兆級吞吐、快很多的區塊。工作量證明的一個 fundamental 問題來自它的 superpower：PoW 無許可、抗審查，誰都能出塊；你出塊時可能別人也同一刻出塊。So this is coming to a testnet near you, where we have this multi-gigabit throughput and much, much faster blocks. We're able—one of the fundamental problems with proof of work comes from its superpower. Proof of work is permissionless. It's censorship-resistant. And that means that anyone can produce a block. So as you produce a block, it can happen that someone else produced a block at the same exact time.
這很麻煩，等於你賠錢（礦池還有幾層複雜度），基本上是兩人同時出塊的 fundamental 問題，也是把出塊時間壓更低的 bound。做法有不同。And this is problematic because now you lose money, effectively. It's, like, some layers of complexity with mining pools. It's basically the fundamental problem of two people producing blocks at the same time. This is the bound on making the block times lower. So there's different approaches.
DAG 與 Autobahn 思路
有 DAG 路線，讓所有或大多數區塊都貢獻到鏈上。還有我們現在做的另一條，類似 Autobahn，來自 PoS、我們改編到 PoW。You have this DAG approach where we simply let all blocks contribute to the chain, or most blocks. And then there's a separate approach that we're working on now, which is similar to Autobahn, which is another thing from proof of stake that we're sort of adapting for proof of work.
和 DAG 很像，我們消除這個問題。兩者都讓區塊可以更快、吞吐高很多。就這樣，謝謝。And it's very similar to DAGs, in that we eliminate this problem. Both of these things allow us to make the blocks much, much, much faster and much, much higher throughput. That's it. Thank you.
