Streamr

As the third quarter of 2023 concludes, the Streamr project is making significant strides towards enhancing its application layer, particularly with StreamrTV. The Governance Council has announced a strategic shift in operational leadership, appointing Mark Little as the new CEO and Petri Savolainen as CTO. This transition aims to leverage their expertise to bolster the project's market execution while ensuring continuity with co-founders Henri and Nikke. The focus on StreamrTV is evident as the project seeks to monetize content and improve user engagement through new features such as payment rails for tipping and an interactive chat sidebar. Key achievements during this quarter include the successful launch of payment functionalities for StreamrTV, allowing broadcasters to monetize their content through 'Super Balloons.' Additionally, a chat feature has been introduced, enhancing viewer interaction. The project also conducted network scaling tests, confirming its reliability across thousands of nodes globally. Financially, Streamr minted approximately 7.5 million DATA tokens, raising $442,689 from token sales, while managing to reduce overall expenses to $499,000, reflecting a strategic focus on cost efficiency amid challenging market conditions. Looking ahead, the project anticipates the next governance checkpoint proposal in December 2025, with plans to unlock additional tokens for development. The Data Ecosystem fund remains intact, with no disbursements made this quarter. Streamr is actively working to attract users from both Web3 and Web2 communities, utilizing product analytics to refine its offerings. Despite facing technical complexities, the team is optimistic about overcoming challenges related to many-to-many video streaming in the upcoming quarter. Overall, Streamr's commitment to innovation and user engagement positions it well for future growth in the blockchain space.

In a significant announcement to the Streamr Network community, Mark Little has been appointed as the new CEO, marking a crucial phase in the project’s journey towards mainstream adoption. Over the past two years, Streamr has made notable progress, including the launch of its 1.0 Mainnet and the establishment of strategic partnerships aimed at enhancing protocol adoption. However, Little acknowledges that the network has not yet achieved the desired volume of data flow, a challenge faced by many Web3 infrastructure projects. To address this, the focus will shift to the application layer, aiming to attract a larger user base and enhance the overall utility of the technology. Little highlighted the potential of live video streaming, referencing previous explorations through the Subcast project, which were ultimately set aside due to commercial challenges. However, with the MVP1 of StreamrTV now live and receiving positive feedback, the Streamr Council believes that prioritizing live video streaming could lead to significant adoption. Current market players like X Spaces, Zoom, and Twitch are criticized for their suboptimal user experiences, particularly in terms of security, privacy, and censorship resistance—areas where decentralized technology excels. Streamr aims to leverage its core technology to create superior solutions while addressing the Web3 user experience problem. To accelerate progress, Little has announced the appointment of Petri Savolainen as CTO, who brings extensive expertise in peer-to-peer and video streaming technologies. This leadership change is part of a broader initiative to foster a leaner, more focused start-up culture within the team. Little expressed gratitude towards former team members Matthew Fontana and Eric Andrews for their contributions, wishing them well in their future endeavors. He invites the community to engage with the team during the fortnightly Build in Public sessions, emphasizing the importance of collaboration in achieving product-market fit and driving the project forward.

The Streamr Network has introduced the AutoStaker plugin, a significant advancement aimed at simplifying the staking process for operators. This new feature automates staking decisions, allowing operators to focus on managing their nodes rather than manually monitoring sponsorship opportunities. By automatically discovering and staking into new sponsorships, the AutoStaker enhances the efficiency of the network, ensuring that operators can capitalize on high-yield opportunities without the risk of overlooking them due to manual oversight. The plugin is available starting from Streamr Node version 103.1.0. The AutoStaker operates seamlessly within operator nodes, scanning for available sponsorships and allocating stakes based on configurable parameters. It prioritizes the DATA/day emission rate of sponsorships, which helps in minimizing gas costs and avoiding excessive competition among operators. The plugin also periodically rebalances stakes to maintain optimal allocations across various opportunities. Operators need to enable the AutoStaker, assign staking agent roles to their nodes, and configure the plugin according to their fleet's needs to get started. This streamlined approach allows for a more responsive network and better overall performance. Looking ahead, the AutoStaker is poised to become a foundational tool for dynamic and automated sponsorships within the Streamr Network. Future developments may include enhancements that support live video streams, taking into account bandwidth and CPU requirements before staking. As operators are incentivized to support these broadcasts, the AutoStaker will not only maximize APY but also contribute to the overall robustness of the network. By adopting the AutoStaker, operators can ensure their competitiveness and efficiency in the rapidly evolving landscape of decentralized data streaming.

In early 2025, extensive scaling tests were conducted on the new trackerless Streamr Network 1.0 to evaluate its performance and scalability. The tests involved deploying thousands of nodes across 17 global regions, utilizing data centers to simulate a live network environment. The experiments focused on validating the three-layer trackerless architecture, particularly the locality awareness in Layer 2, and measuring the network's performance under load. Key metrics analyzed included join times, routing delays, message propagation delays, and time to data, all crucial for the network's functionality. The experiment setup involved running tests with up to 2,000 nodes, coordinated by a centralized script that tracked progress and issued instructions. Initial latency measurements established a baseline, revealing a mean one-way delay of 75 ms between AWS regions. The results indicated that join times for nodes joining the Layer 0 Distributed Hash Table (DHT) were efficient, with most nodes able to start participating in higher layers shortly after establishing a single DHT connection. Routing delays and hops were also measured, showing that the mean hop count grew logarithmically with the number of nodes, while the average round-trip time (RTT) remained around 360 ms at 2,000 nodes, confirming the efficiency of Layer 0 routing. The tests further evaluated stream message propagation delays and time to data, with results indicating that the mean message propagation delay was lower for larger streams due to effective locality-aware clustering. The mean time to data consistently averaged around 1 second, significantly below the 2-second target. Overall, the new trackerless Streamr Network demonstrated stable performance, efficient routing, and low latency growth, confirming its capability to scale effectively while maintaining high data availability and performance standards. This success validates the architecture's design and its potential for future applications in decentralized data streaming.

The intersection of robotics and blockchain technology is fostering a new wave of innovative projects that are gaining traction among niche investors. These lesser-known robotics tokens, each with a market capitalization under $20 million, provide a unique perspective on the future of decentralized automation, AI-driven robotics, and machine-to-machine economies. As these projects emerge, they are setting the stage for a transformative shift in how we perceive and utilize technology in various sectors. One notable project is Streamr (DATA), an open-source platform that utilizes cryptography to create a decentralized, peer-to-peer data infrastructure. With a market cap of $18.65 million, Streamr aims to facilitate real-time data exchange through a scalable messaging network and a marketplace for trading data. Another promising project is U2U Network, which combines advanced directed acyclic graph (DAG) technology with Ethereum Virtual Machine (EVM) compatibility, enabling ultra-fast transactions and customizable sub-networks for developers. With a market cap of $10.52 million, U2U Network is positioned to enhance decentralized physical infrastructure networks (DePIN). Additionally, Swarm (BZZ) seeks to re-decentralize the internet by providing a self-sustaining infrastructure for a supply-chain economy of data. With a market cap of $7.09 million, Swarm is backed by a strong community. Mysterium (MYST) offers a borderless internet experience through its open-source ecosystem, allowing users to safeguard their online anonymity while participating in a peer-to-peer network. Lastly, Shieldeum (SDM) focuses on delivering secure computing power through AI-driven decentralized infrastructure, catering to the needs of crypto users and Web3 enterprises. These projects highlight the potential of blockchain technology in revolutionizing robotics and automation, paving the way for a more decentralized future.

In the evolving landscape of decentralized networks, scalability emerges as a vital attribute, particularly in peer-to-peer (P2P) systems. The Streamr Network has embraced this principle by transitioning from a traditional tracker model to a fully decentralized architecture. This shift, marked by the introduction of a three-layer structure, empowers every participant to act as a full node, thereby eliminating the bottlenecks associated with centralized servers. By leveraging a multi-layer Distributed Hash Table (DHT), Streamr enhances node independence and facilitates seamless scaling, allowing for efficient data stream coordination without the need for centralized trackers. The three layers of the Streamr Network each serve a unique purpose in ensuring efficient data delivery. Layer 0, the Global Kademlia DHT, functions as the backbone of the network, enabling nodes to connect and communicate with minimal hops. Layer 1 introduces a hybrid DHT tailored for stream coordination, optimizing peer discovery based on geographic proximity. Finally, Layer 2 establishes a mesh network for real-time data flow, ensuring that subscribers receive messages promptly. This layered approach not only reduces the resource burden on individual nodes but also supports the inclusion of thousands of nodes without significant connection overhead. Recent experiments have demonstrated the effectiveness of this trackerless architecture, showcasing low latency even as the network scales. With locality-based clustering, message propagation delays remained impressively low, averaging around 120 milliseconds in a 2,000-node network. This performance underscores the potential of Streamr's innovative design to maintain efficiency and responsiveness in decentralized environments. Future updates will delve deeper into the scalability tests and the architecture's overall performance, reinforcing Streamr's commitment to advancing decentralized data streaming solutions.