This paper introduces Rumor Routing, a data-centric routing algorithm for sensor networks that balances setup overhead and delivery reliability. The algorithm is designed for scenarios where geographic routing is not applicable due to lack of coordinate systems or non-geographically correlated events. Rumor Routing creates paths to events by having long-lived agents propagate information about local events. These agents update their paths based on the events they encounter, allowing queries to be delivered to events through random walks or direct routing. The algorithm is tunable, allowing trade-offs between setup cost and delivery reliability. Rumor Routing is compared to flooding mechanisms, including query flooding and event flooding. It is particularly effective when the number of queries is lower than the number of events, as it reduces energy consumption compared to event flooding. Simulations show that Rumor Routing can achieve high delivery rates with significantly lower energy costs, especially when the number of queries per event is low. The algorithm is also robust to node failures, degrading delivery performance linearly with the number of failed nodes. The algorithm's performance is influenced by parameters such as the number of agents, agent TTL, and query TTL. Simulations demonstrate that Rumor Routing can achieve high delivery rates with minimal setup costs, making it suitable for a wide range of applications. The algorithm is also stable across different configurations and is resilient to node failures. Future work includes exploring wider simulation scenarios, alternative algorithm designs, and testing the algorithm in real-world sensor networks. The paper concludes that Rumor Routing provides an efficient and tunable solution for delivering queries to events in sensor networks under various conditions.This paper introduces Rumor Routing, a data-centric routing algorithm for sensor networks that balances setup overhead and delivery reliability. The algorithm is designed for scenarios where geographic routing is not applicable due to lack of coordinate systems or non-geographically correlated events. Rumor Routing creates paths to events by having long-lived agents propagate information about local events. These agents update their paths based on the events they encounter, allowing queries to be delivered to events through random walks or direct routing. The algorithm is tunable, allowing trade-offs between setup cost and delivery reliability. Rumor Routing is compared to flooding mechanisms, including query flooding and event flooding. It is particularly effective when the number of queries is lower than the number of events, as it reduces energy consumption compared to event flooding. Simulations show that Rumor Routing can achieve high delivery rates with significantly lower energy costs, especially when the number of queries per event is low. The algorithm is also robust to node failures, degrading delivery performance linearly with the number of failed nodes. The algorithm's performance is influenced by parameters such as the number of agents, agent TTL, and query TTL. Simulations demonstrate that Rumor Routing can achieve high delivery rates with minimal setup costs, making it suitable for a wide range of applications. The algorithm is also stable across different configurations and is resilient to node failures. Future work includes exploring wider simulation scenarios, alternative algorithm designs, and testing the algorithm in real-world sensor networks. The paper concludes that Rumor Routing provides an efficient and tunable solution for delivering queries to events in sensor networks under various conditions.