MobiEyes: A Distributed Location Monitoring Service Using Moving Location Queries

With the growing popularity and availability of mobile communications, our ability to stay connected while on the move is becoming a reality instead of science fiction as it was just a decade ago. An important research challenge for modern location-based services is the scalable processing of location monitoring requests on a large collection of mobile objects. The centralized architecture, though studied extensively in literature, would create intolerable performance problems as the number of mobile objects grows significantly. This paper presents a distributed architecture and a suite of optimization techniques for scalable processing of continuously moving location queries. Moving location queries can be viewed as standing location tracking requests that continuously monitor the locations of mobile objects of interest and return a subset of mobile objects when certain conditions are met. We describe the design of MobiEyes, a distributed real time location monitoring system in a mobile environment. The main idea behind the MobiEyes' distributed architecture is to promote a careful partition of a real time location monitoring task into an optimal coordination of server-side processing and client-side processing. Such a partition allows evaluating moving location queries with a high degree of precision using a small number of location updates, thus providing highly scalable location monitoring services. A set of optimization techniques are used to limit the amount of computation to be handled by the mobile objects and enhance the overall performance and system utilization of MobiEyes. Important metrics to validate the proposed architecture and optimizations include messaging cost, server load, and amount of computation at individual mobile objects. We evaluate the scalability of the MobiEyes location monitoring approach using a simulation model based on a mobile setup. Our experimental results show that MobiEyes can lead to significant savings in terms of server load and messaging cost when compared to solutions relying on central processing of location information.