When Mobile Objects’ Energy Is Not So Tight: A New Perspective on Scalability Issues of Continuous Spatial Query Systems
The two dominant costs in continuous spatial query systems are the wireless communication cost for location update, and the evaluation cost for query processing. Existing works address both of these scalability factors by employing the distributed computation strategy, in which some part of query processing is carried out by mobile objects. In this paper, we make one important assumption about mobile objects’ energy; that is for many applications, mobile objects’ energy is not limited, as opposed to the battery-powered objects assumed in existing works. Under this new assumption, we re-examine the scalability issues for continuous spatial query systems. Our examination points out that the major bottleneck of these systems is now the wide-area wireless uplink bandwidth, which has not been addressed adequately in the past. We attack the problem by leveraging the local-area wireless communication between mobile objects, leading to our proposal of a hybrid communication architecture to be used in these continuous spatial query systems. The hybrid communication architecture unifies the two communication paradigms, wide-area and local-area wireless networks. We then propose a proof of concept system, called P2MRQ (Peer-to-peer technique for Moving Range Queries), to answer continuous moving range queries over moving objects. While MobiEyes , an existing continuous range query system, only utilizes distributed computation, our P2MRQ is able to leverage both distributed computation and local-area wireless communication. Our performance study shows that the required wide-area wireless uplink bandwidth from P2MRQ is consistently less than that of MobiEyes; for all considered cases, P2MRQ requires at most 50% of the wide-area wireless uplink bandwidth as MobiEyes does.
KeywordsMobile Device Query Processing Range Query Mobile Client Scalability Issue
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