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ISLABEL: an IndependentSet based Labeling Scheme for PointtoPoint Distance Querying
"... We study the problem of computing shortest path or distance between two query vertices in a graph, which has numerous important applications. Quite a number of indexes have been proposed to answer such distance queries. However, all of these indexes can only process graphs of size barely up to 1 mil ..."
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We study the problem of computing shortest path or distance between two query vertices in a graph, which has numerous important applications. Quite a number of indexes have been proposed to answer such distance queries. However, all of these indexes can only process graphs of size barely up to 1 million vertices, which is rather small in view of many of the fastgrowing realworld graphs today such as social networks and Web graphs. We propose an efficient index, which is a novel labeling scheme based on the independent set of a graph. We show that our method can handle graphs of size orders of magnitude larger than existing indexes. 1.
Hop Doubling Label Indexing for PointtoPoint Distance Querying on ScaleFree Networks
"... We study the problem of pointtopoint distance querying for massive scalefree graphs, which is important for numerous applications. Given a directed or undirected graph, we propose to build an index for answering such queries based on a novel hopdoubling labeling technique. We derive bounds on th ..."
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We study the problem of pointtopoint distance querying for massive scalefree graphs, which is important for numerous applications. Given a directed or undirected graph, we propose to build an index for answering such queries based on a novel hopdoubling labeling technique. We derive bounds on the index size, the computation costs and I/O costs based on the properties of unweighted scalefree graphs. We show that our method is much more efficient and effective compared to the stateoftheart techniques, in terms of both querying time and indexing costs. Our empirical study shows that our method can handle graphs that are orders of magnitude larger than existing methods. 1.
Finding DistancePreserving Subgraphs in Large Road Networks
"... AbstractGiven two sets of points, S and T , in a road network, G, a distancepreserving subgraph (DPS) query returns a subgraph of G that preserves the shortest path from any point in S to any point in T . DPS queries are important in many real world applications, such as route recommendation syst ..."
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AbstractGiven two sets of points, S and T , in a road network, G, a distancepreserving subgraph (DPS) query returns a subgraph of G that preserves the shortest path from any point in S to any point in T . DPS queries are important in many real world applications, such as route recommendation systems, logistics planning, and all kinds of shortestpathrelated applications that run on resourcelimited mobile devices. In this paper, we study efficient algorithms for processing DPS queries in large road networks. Four algorithms are proposed with different tradeoffs in terms of DPS quality and query processing time, and the best one is a graphpartitioning based index, called RoadPart, that finds a high quality DPS with short response time. Extensive experiments on large road networks demonstrate the merits of our algorithms, and verify the efficiency of RoadPart for finding a highquality DPS.
Distance Preserving Graph Simplification
, 1110
"... Abstract—Large graphs are difficult to represent, visualize, and understand. In this paper, we introduce “gate graph ” a new approach to perform graph simplification. A gate graph provides a simplified topological view of the original graph. Specifically, we construct a gate graph from a large grap ..."
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Abstract—Large graphs are difficult to represent, visualize, and understand. In this paper, we introduce “gate graph ” a new approach to perform graph simplification. A gate graph provides a simplified topological view of the original graph. Specifically, we construct a gate graph from a large graph so that for any “nonlocal ” vertex pair (distance higher than some threshold) in the original graph, their shortestpath distance can be recovered by consecutive “local ” walks through the gate vertices in the gate graph. We perform a theoretical investigation on the gatevertex set discovery problem. We characterize its computational complexity and reveal the upper bound of minimum gatevertex set using VCdimension theory. We propose an efficient mining algorithm to discover a gatevertex set with guaranteed logarithmic bound. We further present a fast technique for pruning redundant edges in a gate graph. The detailed experimental results using both real and synthetic graphs demonstrate the effectiveness and efficiency of our approach. I.
Efficient route compression for hybrid route planning
 In MedAlg
, 2012
"... Abstract. We describe an algorithmic framework for lossless compression of route descriptions. This is useful for hybrid route planning where routes are computed by a server and then transmitted to a client device in a car using some mobile radio communication where bandwidth may be low. Compressed ..."
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Abstract. We describe an algorithmic framework for lossless compression of route descriptions. This is useful for hybrid route planning where routes are computed by a server and then transmitted to a client device in a car using some mobile radio communication where bandwidth may be low. Compressed routes are represented by only a few via nodes which are the connection points when the route is decomposed into unique optimal segments. To reconstruct the route efficiently a client device needs basic but fast route planning capability. Contraction hierarchies make this approach fast enough for practice: Compressing takes only a few milliseconds. And previous experiments suggest that a client can decompress each route segment virtually instantaneously. So, as the segments can be decompressed successively while driving, it is not likely that the driver experiences any delay except for the time needed by the mobile communication. 1
A Framework of Traveling Companion Discovery on Trajectory Data Streams
"... The advance of mobile technologies leads to huge volumes of spatiotemporal data collected in the form of trajectory data stream. In this study, we investigate the problem of discovering object groups that travel together (i.e., traveling companions) from trajectory data streams. Such technique has ..."
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The advance of mobile technologies leads to huge volumes of spatiotemporal data collected in the form of trajectory data stream. In this study, we investigate the problem of discovering object groups that travel together (i.e., traveling companions) from trajectory data streams. Such technique has broad applications in the areas of scientific study, transportation management and military surveillance. To discover traveling companions, the monitoring system should cluster the objects of each snapshot and intersect the clustering results to retrieve movingtogether objects. Since both clustering and intersection steps involve high computational overhead, the key issue of companion discovery is to improve the efficiency of algorithms. We propose the models of closed companion candidates and smart intersection to accelerate data processing. A data structure termed traveling buddy is designed to facilitate scalable and flexible companion discovery from trajectory streams. The traveling buddies are microgroups of objects that are tightly bound together. By only storing the object relationships rather than their spatial coordinates, the buddies can be dynamically maintained along trajectory stream with low cost. Based on traveling buddies, the system can discover companions without accessing the object details. In addition, we extend the proposed framework to discover companions on more complicated scenarios with spatial and temporal constraints, such as on the road network and battlefield. The proposed methods are evaluated with extensive experiments on both real and synthetic datasets. Experimental results show that our proposed buddybased approach is an order of magnitude faster than the baselines and achieves higher accuracy in companion discovery.
Bonding Vertex Sets Over Distributed Graph: A Betweenness Aware Approach
"... ABSTRACT Given two sets of vertices in a graph, it is often of a great interest to find out how these vertices are connected, especially to identify the vertices of high prominence defined on the topological structure. In this work, we formally define a Vertex Set Bonding query (shorted as VSB), wh ..."
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ABSTRACT Given two sets of vertices in a graph, it is often of a great interest to find out how these vertices are connected, especially to identify the vertices of high prominence defined on the topological structure. In this work, we formally define a Vertex Set Bonding query (shorted as VSB), which returns a minimum set of vertices with the maximum importance w.r.t total betweenness and shortest path reachability in connecting two sets of input vertices. We find that such a kind of query is representative and could be widely applied in many real world scenarios, e.g., logistic planning, social community bonding and etc. Challenges are that many of such applications are constructed on graphs that are too large to fit in single server, and the VSB query evaluation turns to be NPhard. To cope with the scalability issue and return the near optimal result in almost real time, we propose a generic solution framework on a shared nothing distributed environment. With the development of two novel techniques, guided graph exploration and betweenness ranking on exploration, we are able to efficiently evaluate queries for error bounded results with bounded space cost. We demonstrate the effectiveness of our solution with extensive experiments over both real and synthetic large graphs on the Google's Cloud platform. Comparing to the exploration only baseline method, our method achieves several times of speedup.
Concise Caching of Driving Instructions
"... Online driving direction services offer fundamental functionality to mobile users, and such services see substantial and increasing loads as mobile access continues to proliferate. Cache servers can be deployed in order to reduce the resulting network traffic. We define socalled concise shortest pa ..."
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Online driving direction services offer fundamental functionality to mobile users, and such services see substantial and increasing loads as mobile access continues to proliferate. Cache servers can be deployed in order to reduce the resulting network traffic. We define socalled concise shortest paths that are equivalent to driving instructions. A concise shortest path occupies much less space than a shortest path; yet it provides sufficient navigation information to mobile users. Then we propose techniques that enable the caching of concise shortest paths in order to improve the cache hit ratio. Interestingly, the use of concise shortest paths in caching has two opposite effects on the cache hit ratio. The cache can accommodate a larger number of concise paths, but each individual concise path contains fewer nodes and so may answer fewer shortest path queries. The challenge is to strike a balance between these two effects in order to maximize the overall cache hit ratio. In this paper, we revisit two classes of caching methods and develop effective caching techniques for concise paths. Empirical results on real trajectoryinduced workloads confirm the effectiveness of the proposed techniques.