SLIM: A Scalable Location-Sensitive Information Monitoring Service

摘要: Location-sensitive information monitoring services are a centerpiece of the technology for disseminating content-rich from massive data streams to mobile users. The key challenges such characterized by combination spatial and non-spatial attributes being monitored wide spectrum update rates. A typical example is "alert me when gas price at station within 5 miles my current location drops 4 per gallon". Such service needs monitor changes in conjunction with highly dynamic nature information. Scalability sensitive content rich presence different rates thresholds poses big technical challenge. In this paper, we present SLIM, scalable framework two unique features. First, make intelligent use correlation between involved requests devise distributed trigger evaluation engine. Second, introduce single multi-dimensional safe value containment techniques efficiently perform selective processing triggers reduce amount unnecessary evaluations. Through extensive experiments, show that SLIM offers high scalability location-sensitive, terms number sources monitored, users requests.