{"schema_version":"1.0","canonical_url":"https://patentable.app/patents/US-9854038","patent":{"patent_number":"US-9854038","title":"Data replication using ephemeral tree structures","assignee":null,"inventors":[],"filing_date":"2015-09-21T00:00:00.000Z","publication_date":"2017-12-26T00:00:00.000Z","cpc_codes":["H04L","H04L","H04L"],"num_claims":20,"abstract":"The disclosure is directed to replicating data across multiple computer nodes (“nodes”) in a distributed computing system. The data is replicated to a significantly large number of servers in two modes—a pull mode and a push mode. In the push mode, data replication is initiated by a publisher node, which replicates the data to the nodes. In the pull mode, data replication is initiated by a node which pulls the data from one of the nodes. The nodes are deployed as an ephemeral tree structure (“tree”) such that data can flow efficiently between nodes of different hierarchical levels of a communication network, e.g., a region, a datacenter, a cluster, and a rack. Data is transmitted across the hierarchical levels from a leader node of one level to a leader node of another level, and from the leader node to the other nodes within the level."},"analysis":{"summary":"Data Replication Using Ephemeral Tree Structures is a patented technology designed to efficiently replicate data across multiple computer nodes in a distributed computing system. The core innovation lies in utilizing an ephemeral tree structure to optimize data flow, combined with both push and pull replication modes. This approach addresses the challenges of scalability and efficiency inherent in traditional data replication methods.\n\nThe problem being solved is the slow and unreliable replication of data across a large number of servers, which is common in modern distributed systems. Existing solutions often struggle to maintain data consistency and availability, leading to performance bottlenecks and potential data loss. Data Replication Using Ephemeral Tree Structures overcomes these limitations by organizing nodes into a hierarchical tree structure, allowing for efficient data transmission across different levels, such as regions, datacenters, clusters, and racks.\n\nThe key technical approach involves a combination of push and pull replication modes. In push mode, a publisher node initiates replication, distributing data to other nodes. In pull mode, a node requests data from another node. The ephemeral tree structure ensures that data flows efficiently between nodes, with data transmitted across hierarchical levels from a leader node of one level to a leader node of another level, and from the leader node to the other nodes within the level.\n\nThe business value and applications of this technology are significant. It can be used to improve data consistency and availability in a wide range of industries, including finance, e-commerce, and healthcare. By optimizing data replication, businesses can reduce latency, improve performance, and enhance the overall resilience of their distributed systems.\n\nThe market opportunity for Data Replication Using Ephemeral Tree Structures is substantial, as more and more organizations adopt distributed computing architectures. This technology offers a scalable and efficient solution for managing data across a large number of servers, making it an essential component of modern data infrastructure.","layman_explanation":"Data Replication Using Ephemeral Tree Structures offers a new way to keep data consistent across many different computers or servers. Imagine a company with offices all over the world. Each office needs to have the same information about customers, products, and orders. Keeping all that data synchronized can be a real challenge.\n\n**What Problem Does This Solve?**\n\nTraditional methods of data replication can be slow and unreliable. When data changes in one location, it can take a long time to update all the other locations. This can lead to confusion, errors, and lost business. Existing solutions often struggle to handle large amounts of data and complex network configurations.\n\n**How Does It Work?**\n\nThis technology organizes the computers into a tree-like structure. Think of a family tree, where each person is connected to others. In this case, the computers are connected in a similar way. When data changes, it flows down the tree, from the top to the bottom, ensuring that everyone gets the latest information quickly and efficiently. It also allows computers to 'pull' data if they need it, ensuring everyone has what they need, when they need it. This is different than the old way of pushing data and hoping it makes it to its destination.\n\n**Why Does This Matter?**\n\nThis technology can significantly improve the performance and reliability of data replication. It can reduce the time it takes to update data, minimize errors, and ensure that everyone has access to the latest information. This can lead to better customer service, improved decision-making, and increased efficiency. The market impact is potentially huge, as it touches any industry that relies on distributed data.\n\n**What's Next?**\n\nThe future applications of this technology are vast. It could be used to improve the performance of cloud computing, big data analytics, and the Internet of Things. As the amount of data continues to grow, the need for efficient and reliable data replication will only increase. Investment implications are positive, as this technology addresses a real need in a growing market.","technical_analysis":"Data Replication Using Ephemeral Tree Structures introduces a novel architectural approach to data replication in distributed systems. The system leverages an ephemeral tree structure to organize nodes, facilitating efficient data propagation. This structure dynamically adapts to network conditions and node availability, ensuring optimal data flow.\n\nThe core of the system lies in its hybrid push-pull mechanism. A publisher node initiates data replication in push mode, distributing data to other nodes. Simultaneously, nodes can request data in pull mode, enhancing data availability and reducing latency. This combination optimizes data dissemination across the network.\n\nImplementation involves designing an efficient tree structure, selecting a reliable data replication protocol, and managing node membership. The tree structure must consider network topology and data access patterns. The replication protocol should guarantee data consistency and minimize overhead. Node membership management must be robust to handle dynamic changes in the network.\n\nAlgorithmically, the system likely employs a distributed consensus algorithm to maintain data consistency across nodes. The ephemeral nature of the tree suggests a decentralized approach, possibly utilizing gossip protocols for node discovery and membership management. The push-pull mechanism requires efficient queue management and scheduling algorithms to handle data transfer requests.\n\nIntegration with existing systems would likely involve standard APIs and protocols. The system could be integrated with data storage solutions like Apache Cassandra or message queues like Apache Kafka. Performance characteristics depend on network bandwidth, node processing power, and the efficiency of the replication protocol. Benchmarking would be necessary to optimize performance for specific workloads.\n\nCode-level, the system would involve distributed algorithms for tree construction, node discovery, data replication, and consensus. These algorithms would need to be implemented in a language suitable for distributed computing, such as Java or Go. Careful attention would need to be paid to concurrency and fault tolerance to ensure system reliability.","business_analysis":"Data Replication Using Ephemeral Tree Structures presents a compelling business opportunity in the rapidly expanding market for distributed computing solutions. The technology addresses a critical need for efficient and reliable data replication, offering significant advantages over traditional methods.\n\nThe market opportunity is substantial, driven by the increasing adoption of cloud computing, big data analytics, and IoT. These trends are creating a growing demand for scalable and resilient data management solutions. Data Replication Using Ephemeral Tree Structures is well-positioned to capitalize on this demand.\n\nThe technology offers several competitive advantages. Its ephemeral tree structure allows for dynamic adaptation to network conditions, ensuring optimal data flow. The combination of push and pull replication modes enhances data availability and reduces latency. These advantages translate into improved performance, reduced costs, and increased customer satisfaction.\n\nThe revenue potential is significant. The technology can be licensed to cloud service providers, data storage vendors, and enterprises. Business models could include subscription-based licensing, usage-based pricing, or a combination of both. Strategic positioning should focus on highlighting the technology's scalability, efficiency, and resilience.\n\nROI projections depend on market adoption and pricing strategy. However, the potential for significant cost savings and revenue generation makes Data Replication Using Ephemeral Tree Structures an attractive investment. The technology aligns with the trend towards decentralized and distributed data management, offering a long-term competitive advantage.","faqs":null,"topics":["data replication","ephemeral tree structures","distributed computing","data management","data consistency"],"tech_cluster":null},"seo":{"title":"Data Replication Using Ephemeral Tree Structures - Patent US-9854038","description":"Discover how Data Replication Using Ephemeral Tree Structures optimizes data flow across distributed systems using an ephemeral tree. Full patent analysis and claims.","keywords":["data replication","ephemeral tree structures","distributed computing","data management","data consistency","patent","patent US-9854038"]},"attribution":{"source":"Patentable","source_url":"https://patentable.app","canonical_url":"https://patentable.app/patents/US-9854038","license":"CC-BY-4.0-like","license_terms":"AI-generated analysis on this page (summary, layman_explanation, technical_analysis, business_analysis, faqs) may be reused with attribution and a visible link back to the canonical URL above. Patent abstracts, claims, and bibliographic data are USPTO public domain.","required_link":"https://patentable.app/patents/US-9854038","citation_suggestion":"Patentable. \"Data replication using ephemeral tree structures\" (US-9854038). https://patentable.app/patents/US-9854038","copyright_holder":"Nomic Interactive Technology LLC"},"links":{"html":"https://patentable.app/patents/US-9854038","json":"https://patentable.app/api/llm-context/US-9854038","site":"https://patentable.app","llms_txt":"https://patentable.app/llms.txt"},"generated_at":"2026-05-30T01:53:07.406Z"}