Query Processing in Mobile Peer-to-peer Networks

Mobile local search is a procedure in which a mobile user searches for local resources, i.e., resources that are in geographic proximity to the user (e.g., a person with certain expertise in a convention hall, a ride-share opportunity, a taxi-cab, a parking slot, etc.). A promising approach to mobile local search is mobile peer-to-peer databases (MP2PD). In the MP2PD approach, a database is stored in the peers (PDA's, cell phones, vehicles, sensors, etc.) that communicate with each other via short-range wireless technologies such as IEEE 802.11, Bluetooth, Zigbee, or Ultra Wide Band (UWB). All the local databases maintained by the mobile peers form a mobile P2P database. The characteristics of MP2PD include (i) dynamic network topology, (ii) memory/energy/bandwidth limitations, and (iii) lack of global coordination. The objective of the dissertation is to study query processing in such an environment. The traditional in-network query processing paradigm postulates that a query is routed among peers and collects the answers from the peers. It works for static and connected networks. However, when the network consists of mobile peers and is sparse, a different approach is necessary. We propose a query processing method that uses cooperative caching. It makes the data items satisfying a query flow to its originator. To cope with communication bandwidth and storage constraints, the method prioritizes the data-items in terms of their value, as reflected by supply and demand. The dissertation develops the formula by which a mobile peer dynamically adjusts the number of reports included in a transmission, develops a report prioritization method called MARKET, analyzes the way a report is propagated in geospace and time, the benefit of information dissemination in capturing competitive resources (i.e. resources that can be used by only one user at a time) and provisioning real-time traffic information, how well the average local database reflects the status of physical resources, how our approach compares with the central server model and with existing work on publish/subscribe in wireless ad-hoc networks, how to incentivize mobile devices to relay reports, the application to continuous kNN queries and to transportation mode detection.