Ling Liu's SC13 paper "Large Graph Processing Without the Overhead" featured by HPCwire.
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Second GraphLab workshop should be even bigger than the first! GraphLab is a new programming framework for graph-style data analytics.
Road Network-Aware Spatial Alarms
IEEE Transactions on Mobile Computing, vol. 15, no. 1, pp. 188-201, Jan. 1 2016.
Kisung Lee, Ling Liu, Balaji Palanisamy*, Emre Yigitoglu
Georgia Institute of Technology
* University of Pittsburgh
Road network-aware spatial alarms extend the concept of time-based alarms to spatial dimension and remind us when we travel on spatially constrained road networks and enter some predefined locations of interest in the future. This paper argues that road network-aware spatial alarms need to be processed by taking into account spatial constraints on road networks and mobility patterns of mobile subscribers. We show that the Euclidian distance-based spatial alarm processing techniques tend to incur high client energy consumption due to unnecessarily frequent client wakeups. We design and develop a road network-aware spatial alarm processing system, called ROADALARM, with three unique features. First, we introduce the concept of road network-based spatial alarms using road network distance measures. Instead of using a rectangular region, a road network-aware spatial alarm is a star-like subgraph with an alarm target as the center of the star and border points as the scope of the alarm region. Second, we describe a baseline approach for spatial alarm processing by exploiting two types of filters. We use subscription filter and Euclidean lower bound filter to reduce the amount of shortest path computations required in both computing alarm hibernation time and performing alarm checks at the server. Last but not the least, we develop a suite of optimization techniques using motion-aware filters, which enable us to further increase the hibernation time of mobile clients and reduce the frequency of wakeups and alarm checks, while ensuring high accuracy of spatial alarm processing. Our experimental results show that the road network-aware spatial alarm processing significantly outperforms existing Euclidean space-based approaches, in terms of both the number of wakeups and the hibernation time at mobile clients and the number of alarm checks at the server.
FULL PAPER: pdf