# Geo-DMP: A DTN-Based Mobile Prototype for Geospatial Data Retrieval
## 2 Literature Review
### Map-Based Region Partitioning for Content Dissemination  
It is known that mobility is a predominant feature of DTN networking. The uncertain and fragmented network topology is a major obstacle for telling exactly how and where to get in touch with a given node when necessary in a distributed environment. Fortunately, implicit in the movement of people is the periodicity and regularity to a certain degree, both in social [62] and geographical [63] aspects. In other words, people have the propensity to meet a group of persons and go to a collection of places more often. Motivated by these findings, in spite of the scarcity of a real-time global knowledge of a network, scholars have attempted to make progress in making DTN more effective and meaningful by extrapolating future behaviors from historical knowledge of social relationships [64] or spatial movements [65]. In this paper, we are more interested in geographical rather than topological relations among nodes. It goes without saying that precisely capturing the mobility pattern of nodes will greatly contribute to the accuracy of routing strategies. Meanwhile, simply recording a large quantity of raw GPS coordinates will incur excessive storage consumption and intensive computation to learn the regularity behind moving traces, which is unfavorable as nodes in DTN are typically resource-constrained. One viable solution is region-based methods. By dividing the whole area into a series of subregions, the position of a node can thus be represented by the subarea it currently lies in, and further, the moving process of a node can be simplified as a discrete sequence of subregions. Whereas various ways to generate subregions are presented in existing works, including breaking into regular shapes [66, 67, 68, 69], geometric partitioning [70, 71], and artificial clustering [72, 73], etc., an apparent shortcoming is that none of them are in line with actual environments, as they neglect natural boundaries such as roads, rails, rivers, outer periphery of buildings, among others. Especially for most used grid-based methods, although it is easier to control the area size, code the area, and maintain the hierarchy information, some researchers point out that the determination of the size, position, and orientation of grids is arbitrary [74], and the fixed-size unit is not sufficient to reflect the density of users and their activities [75]. As a result, macroscopically, the methods above all fall short in portraying the \"activity space\" [76], which refers to areas that are delimited by the course of daily routines of people, and microscopically, actions of moving across boundaries become less meaningful, as one may produce crossings simply by wandering around his home or workplace. For the sake of making more solid associations between daily spatiotemporal activities of inhabitants and the segmentation of subregions, small-scale boundaries with administrative properties, for instance, census tracts, postal code areas, or voting precincts are seemingly better choices. They are not merely reasonable approximations to sociological structures like residential neighborhoods, street blocks, and communities [77, 78], but exhibit demographic and socioeconomic characteristics as well [79, 80]. As more researchers realize the advantages of such methods, recent years have witnessed their wide adoption by multidisciplinary studies, such as criminology [81], public health [82, 83], municipal planning [84], and so forth. Many cases [85, 86, 87] have proved that region-based methods can outperform grid-based methods. Hopefully, such methods will be analogously beneficial to research in the field of mobile computing. Instructed by this idea, we attempt to devise a multi-level map partitioning scheme based on the road network and administrative boundaries. We expect that it will lay a concrete foundation for future protocol or application design.