An Adaptive Resource/Performance Trade-Off for Resolving Complex Queries in P2P Networks

Structured Peer-to-Peer (P2P) systems are increasingly important for scalable data dissemination and search. Current distributed approaches for resolving complex search queries, like multi-attribute and range queries, typically require multiple query messages to resolve a single search request. To reduce the message overhead and the search latency, some approaches like the Multi-Attribute Addressable Network (MAAN) use static replication. However, this results in high main memory requirements and large data transfers each time a device joins the P2P network. Those drawbacks can be tolerated for P2P networks that mainly consist of fixed, powerful nodes like PCs but are intolerable for resource-constrained nodes with high churn, like mobile devices. As mobile devices will play a significant role in accessing and distributing data in the future, we propose and evaluate an improved search mechanism for such a scenario. Compared to MAAN, our approach significantly reduces the memory footprint and bandwidth requirements (up to a factor of five in our sample scenario). At the same time, the good latency properties of MAAN are remained on average. This is achieved via a dynamic replication scheme which introduces an adjustable trade-off between memory footprint and search latency. Thereby, our approach makes efficient, distributed resolution of complex queries in resource-constrained P2P networks feasible.