The ever increasing network bandwidth and availabilityhas made the vision of ubiquitous computing a reality: Userscan access the Internet\'s vast offerings anytime and anywhere.Moreover, battery-powered devices suchas personal digital assistants and web-enabled mobile phoneshave successfully emerged as new access points to the world\'sdigital infrastructure.This ubiquity offers a new opportunity for software developers:users can now participate in the software development, optimization,and evolution process while they use their software.Such participation requires effective techniques for gathering profileinformation from remote, resource constrained devices. Further, thesetechniques must be unobtrusive and transparent to the user. Hence,profiles must be gathered using minimalcomputation, communication, and power. To this end, we present aflexible hardware-software scheme that will enable embedded remoteprofiling. We rely on the extraction of meta informationfrom executing programs in the form of phases, and then usethis information to guide intelligent online sampling and to managethe communication of those samples.Our results indicate that phase-based remoteprofiling can reduce the communication, computation, and energyconsumption overheads by 50-75% over random and periodic sampling.