How Does Watchtower Work In The Bitcoin Lightning Network?

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Watchtowers have been developed inside the first paper Lightning network (LN) and also have since been enhanced and improved because Bitcoin’s chain reaction trading  LN seeks to be a worldwide P2P payments Network. They provide a third-party service that allows users to outsource scanning for transactions related to their lightning channels, which helps to scale LN into a global peer-to-peer payments network. Watchtowers play a major role in providing greater security and safety for all participants on the platform. Watchtowers serve as a security measure for blockchain networks, helping to identify and penalize users who attempt to cheat other participants in Lightning Network (LN) channels. If someone transmits an outdated channel state with the intent of reclaiming funds after closing an invalidated channel, watchtowers can detect this malicious activity and take action against it.

To operate, watchtower services typically charge fees from their users. Several monetization methods can be used to ensure the sustainability of these services. Users may choose to use multiple watchtower services as a cautionary measure in case one fails. With technological advances like compact-client-side filtering, used in Neutrino protocol, the load on individual watchtowers has been diminished but their significance remains paramount; especially when looking at scalability issues within the Lightning Network environment.

How Does The Watchtower Work?

Watchtowers are third-party services that provide Bitcoin blockchain monitoring around the clock to their clients. They look for any discrepancies between off-chain transactions and closing channels with invalid states. When an on-chain Lightning Network (LN) channel payment is made, a valid commitment must be provided to create its current state of balance. Both parties within a channel can update this state using subsequent commitments which accompany each transfer.

An accurate channel balance state can be determined by reviewing the past commitments exchanged between counterparties over a particular period. A malicious counterparty, however, has the potential to exploit this system by broadcasting an old (invalid) balance if doing so benefits them more – for instance, when Party A sends out money and reduces their balance causing them to broadcast an older but advantageous balance instead.

Because of time restrictions in a channel, users must wait for an allotted period before they can claim funds from their wallet. This necessitates that the participants remain online to confirm that no unauthorized transactions have been broadcast and also to check if any counterparty is maliciously acting up. Most people don’t have the time or technical expertise to monitor their transactions while they’re offline. That’s where watchtowers come in – these specialized services remain online on behalf of users 24/7, monitoring their blockchain activity and alerting them if any malicious behaviours occur. In return for this service, users pay a fee for peace of mind that their money won’t be stolen while they’re not watching.

Monetisation, Economics And Challenges

For watchtowers to be successful, they must function as businesses and have operational overhead, a user base, and some type of monetization model. The two most common revenue sources for watchtowers are penalty transaction fees or subscription services. In this article, we’ll explore both methods in detail so you can decide which one is right for your business.

Bitcoin’s Lightning Network (LN) has privacy-preserving implementations, but watchtower services necessitate substantial overhead costs for bandwidth, computation, and most significantly disk space. These towers must maintain records of all previous channel states for their clients; an accumulation that can lead to costly storage expenses. As the number of watchtower users grows, bandwidth and computational capabilities can also scale accordingly. However, one potential challenge lies in an increase in disk space requirements due to quadratic user growth. That is to say that a large-scale watchtower needs enough storage resources to store millions or billions of ‘blobs’ (state data).

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