Data Mining - Concepts and Techniques.

Statistics for Spatial Data.

Even though human movement and mobility patterns have a high degree of freedom and variation, they also exhibit structural patterns due to geographic and social constraints. Using cell phone location data, as well as data from two online location-based social networks, we aim to understand what basic laws govern human motion and dynamics. We find that humans experience a combination of periodic movement that is geographically limited and seemingly random jumps correlated with their social networks. Short-ranged travel is periodic both spatially and temporally and not effected by the social network structure, while long-distance travel is more influenced by social network ties. We show that social relationships can explain about 10% to 30% of all human movement, while periodic behavior explains 50% to 70%. Based on our findings, we develop a model of human mobility that combines periodic short range movements with travel due to the social network structure. We show that our model reliably predicts the locations and dynamics of future human movement and gives an order of magnitude better performance than present models of human mobility.

/pdf/friendship-and-mobility-user-movement-in-location-based-2u0rrxuc9l.pdf

Friendship and mobility: user movement in location-based social networks

The theory of affordances

A great variety of systems in nature, society and technology -- from the web of sexual contacts to the Internet, from the nervous system to power grids -- can be modeled as graphs of vertices coupled by edges The network structure, describing how the graph is wired, helps us understand, predict and optimize the behavior of dynamical systems In many cases, however, the edges are not continuously active As an example, in networks of communication via email, text messages, or phone calls, edges represent sequences of instantaneous or practically instantaneous contacts In some cases, edges are active for non-negligible periods of time: eg, the proximity patterns of inpatients at hospitals can be represented by a graph where an edge between two individuals is on throughout the time they are at the same ward Like network topology, the temporal structure of edge activations can affect dynamics of systems interacting through the network, from disease contagion on the network of patients to information diffusion over an e-mail network In this review, we present the emergent field of temporal networks, and discuss methods for analyzing topological and temporal structure and models for elucidating their relation to the behavior of dynamical systems In the light of traditional network theory, one can see this framework as moving the information of when things happen from the dynamical system on the network, to the network itself Since fundamental properties, such as the transitivity of edges, do not necessarily hold in temporal networks, many of these methods need to be quite different from those for static networks

Temporal Networks

While the K-Nearest-Neighbor (KNN) problem is well studied in the traditional wired, disk-based client-server environment, it has not been tackled in a wireless broadcast environment. In this paper, the problem of organizing location dependent data and answering KNN queries on air are investigated. The linear property of wireless broadcast media and power conserving requirement of mobile devices make this problem particularly interesting and challenging. An efficient data organization, called sorted list, and the corresponding search algorithm are proposed and compared with the well-known spatial index, R-Tree. In addition, we develop an approximate search scope to guide the search at the very beginning of the search process and a learning algorithm to adapt the search scope during the search to improve energy and access efficiency. Simulation based performance evaluation is conducted to compare sorted list and R-Tree. The results show that the utilization of search scope and learning algorithm improves search efficiency of both index mechanisms significantly. While R-Tree is more power efficient when a large number of nearest neighbors is requested, the sorted list has better access efficiency and less power consumption when the number of nearest neighbors is small.

http://www.cse.psu.edu/~wul2/Publications/wlee%20mdm03.pdf

Search K Nearest Neighbors on Air

The rapid advance of wireless and portable computing technology has brought a lot of research interests and momentum to the area of mobile computing. One of the research focus is on pervasive data access. With wireless connections, users can access information at any place at any time. However, various constraints such as limited client capability, limited bandwidth, weak connectivity, and client mobility impose many challenging technical issues. In the past years, tremendous research efforts have been put forth to address the issues related to pervasive data access. A number of interesting research results were reported in the literature. This survey paper reviews important works in two important dimensions of pervasive data access: data broadcast and client caching. In addition, data access techniques aiming at various application requirements (such as time, location, semantics and reliability) are covered. Copyright © 2006 John Wiley & Sons, Ltd.

/pdf/pervasive-data-access-in-wireless-and-mobile-computing-4wtqxgo48w.pdf

Pervasive data access in wireless and mobile computing environments

Due to the flexibility and scalability in cloud computing, cloud computing nowadays plays an important role to handle a large-scale data analysis. For data processing operations, several cloud data managements (CDMs), such as HBase and Cassandra, are developed. Such CDMs usually provide key-value storages, where each key is used to access its corresponding value. Both HBase and Cassandra provide some basic operations (e.g., Get, Scan) to retrieve the values via keys specified by users. The exiting CDMs fully inherit the characteristics of cloud computing (i.e., high scalability and availability). With the aforementioned characteristics of cloud computing, CDMs are widely employed for Web data, especially for search engines. However, with the proliferation of smart phones and location-based services, data with spatial information, referring as spatial data, are dramatically increasing. Consequently, how to formulate keys for spatial data in the existing CDMs is a challenge issue. In this paper, we develop several key formulation schemes. In particular, we propose a novel Key formulation scheme based on R+-tree (abbreviated as KR+-index). With our design for keys of spatial data, the existing CDMs are able to efficiently retrieve spatial data. In light of KR+-tree, two spatial queries, k-NN query and range query, are designed. Moreover, we implement the proposed key formulation schemes on HBase and Cassandra, and import real spatial data for spatial queries. The experimental results demonstrate that KR+-tree outperforms other existing key formulations and MD-HBase.

Key Formulation Schemes for Spatial Index in Cloud Data Managements

Information broadcasting, caching of frequently accessed data, and pull-based data delivery are commonly used techniques to reduce data access time of wireless information services. Most of the studies in the literature focused either on individual technique or a combination of them with some restrictive assumptions. In this paper, we propose a dynamic data delivery model where these three techniques work together in an integrated manner. A particular feature of our model is that data are disseminated through various storage mediums according to the dynamically collected data access patterns. Performance evaluation of the model is conducted by simulation studies.

Dynamic Data Delivery in Wireless Communication Environments

Overlay networks have received a lot of attention due to the recent widespread use of peer-to-peer (P2P) applications such as SETI, Napster, Gnutella, and Morpheus. Through replications at numerous peers, digital content can be distributed or exchanged with high resilience and availability. However, existing P2P applications incur excessive overhead on network traffic. For example, Gnutella, which broadcasts queries to search shared content, suffers from an overwhelming volume of query and reply messages. In this paper, we investigate the issues of trading-off storage space at peers to reduce network overhead. We propose to use signatures for directing searches along selected network paths, and introduce three schemes, namely complete-neighborhood signature (CN), partial-neighborhood superimposed signature (PN-S), and partial-neighborhood appended signature (PN-A), to facilitate efficient searching of shared content in P2P networks. Extensive simulations are conducted to evaluate the performance of our proposal with existing P2P content search methods, including Gnutella, Random Walk, and Local Index. Results show that PN-A gives much better performance at a small storage cost.

http://www.cse.psu.edu/~wul2/Publications/wlee%20IDEAS03.pdf

Wang-Chien Lee

Papers

Search K Nearest Neighbors on Air

Pervasive data access in wireless and mobile computing environments

Key Formulation Schemes for Spatial Index in Cloud Data Managements

Dynamic Data Delivery in Wireless Communication Environments

Neighborhood signatures for searching P2P networks