De-Nian Yang

Design of light-tree based logical topologies for multicast streams in wavelength routed optical networks

In this paper, we formulate an optimization problem for the design of light-tree based logical topology in wavelength division multiplexing (WDM) networks. The problem is comprised of two parts: (1) multicast routing and wavelength assignment of light-trees, and (2) the design of light-tree based logical topology for multicast streams. In the first part, we use mixed integer linear programming (MILP) to solve the optimal routing and wavelength assignment problem of light-trees with an end-to-end delay bound, and obtain the optimal placement of power splitters and wavelength converters. The numerical results show that networks with just a few power splitters and wavelength converters can efficiently carry multicast data. In the second part, we extend the above formulation to design the logical topology based on light-trees for multicast streams. In our approach, a light-tree can carry data of multiple multicast streams, and data of a multicast stream may traverse multiple light-trees to reach a receiver. The numerical results show that our approach use network resources more efficiently, as compared to the approach with a separate light-tree for a multicast stream and to the approach of transporting multicast streams over lightpath based logical networks.

Privacy-preserving social network publication against friendship attacks

Due to the rich information in graph data, the technique for privacy protection in published social networks is still in its infancy, as compared to the protection in relational databases. In this paper we identify a new type of attack called a friendship attack. In a friendship attack, an adversary utilizes the degrees of two vertices connected by an edge to re-identify related victims in a published social network data set. To protect against such attacks, we introduce the concept of k2-degree anonymity, which limits the probability of a vertex being re-identified to 1/k. For the k2-degree anonymization problem, we propose an Integer Programming formulation to find optimal solutions in small-scale networks. We also present an efficient heuristic approach for anonymizing large-scale social networks against friendship attacks. The experimental results demonstrate that the proposed approaches can preserve much of the characteristics of social networks.

On socio-spatial group query for location-based social networks

Challenges faced in organizing impromptu activities are the requirements of making timely invitations in accordance with the locations of candidate attendees and the social relationship among them. It is desirable to find a group of attendees close to a rally point and ensure that the selected attendees have a good social relationship to create a good atmosphere in the activity. Therefore, this paper proposes Socio-Spatial Group Query (SSGQ) to select a group of nearby attendees with tight social relation. Efficient processing of SSGQ is very challenging due to the tradeoff in the spatial and social domains. We show that the problem is NP-hard via a proof and design an efficient algorithm SSGSelect, which includes effective pruning techniques to reduce the running time for finding the optimal solution. We also propose a new index structure, Social R-Tree to further improve the efficiency. User study and experimental results demonstrate that SSGSelect significantly outperforms manual coordination in both solution quality and efficiency.

Service differentiation in optical burst switched networks

This paper proposes a preemptive multiclass wavelength reservation protocol to provide differentiated service for Optical Burst Switched (OBS) networks. Unlike existing approaches, which may degrade to classless schemes or which may suffer from low wavelength utilization, our mechanism is robust, efficient, and supports an incremental deployment of QoS support. We maintain a usage profile for each class at the router, and implement a preemptive wavelength reservation mechanism to ensure QoS. We derive an analytical model and conduct simulations to evaluate the performance. The result shows that our approach performs the best in terms of lower blocking probability and higher resource utilization, making it an excellent QoS mechanism for OBS networks.

GaussSense: attachable stylus sensing using magnetic sensor grid

This work presents GaussSense, which is a back-of-device sensing technique for enabling input on an arbitrary surface using stylus by exploiting magnetism. A 2mm-thick Hall sensor grid is developed to sense magnets that are embedded in the stylus. Our system can sense the magnetic field that is emitted from the stylus when it is within 2cm of any non-ferromagnetic surface. Attaching the sensor behind an arbitrary thin surface enables the stylus input to be recognized by analyzing the distribution of the applied magnetic field. Attaching the sensor grid to the back of a touchscreen device and incorporating magnets into the corresponding stylus enable the system 1) to distinguish touch events that are caused by a finger from those caused by the stylus, 2) to sense the tilt angle of the stylus and the pressure with which it is applied, and 3) to detect where the stylus hovers over the screen. A pilot study reveals that people were satisfied with the novel sketching experiences based on this system.

Efficient Resource Allocation for Wireless Multicast

In this paper, we propose a bandwidth-efficient multicast mechanism for heterogeneous wireless networks. We reduce the bandwidth cost of an Internet protocol (IP) multicast tree by adaptively selecting the cell and the wireless technology for each mobile host to join the multicast group. Our mechanism enables more mobile hosts to cluster together and leads to the use of fewer cells to save the scarce wireless bandwidth. Besides, the paths in the multicast tree connecting to the selected cells share more common links to save the wireline bandwidth. Our mechanism supports the dynamic group membership and offers mobility of group members. Moreover, our mechanism requires no modification to the current IP multicast routing protocols. We formulate the selection of the cell and the wireless technology for each mobile host in the heterogeneous wireless networks as an optimization problem. We use integer linear programming to model the problem and show that the problem is NP-hard. To solve the problem, we propose a distributed algorithm based on Lagrangean relaxation and a network protocol based on the algorithm. The simulation results show that our mechanism can effectively save the wireless and wireline bandwidth as compared to the traditional IP multicast.

U-Skyline: A New Skyline Query for Uncertain Databases

The skyline query, aiming at identifying a set of skyline tuples that are not dominated by any other tuple, is particularly useful for multicriteria data analysis and decision making. For uncertain databases, a probabilistic skyline query, called P-Skyline, has been developed to return skyline tuples by specifying a probability threshold. However, the answer obtained via a P-Skyline query usually includes skyline tuples undesirably dominating each other when a small threshold is specified; or it may contain much fewer skyline tuples if a larger threshold is employed. To address this concern, we propose a new uncertain skyline query, called U-Skyline query, in this paper. Instead of setting a probabilistic threshold to qualify each skyline tuple independently, the U-Skyline query searches for a set of tuples that has the highest probability (aggregated from all possible scenarios) as the skyline answer. In order to answer U-Skyline queries efficiently, we propose a number of optimization techniques for query processing, including 1) computational simplification of U-Skyline probability, 2) pruning of unqualified candidate skylines and early termination of query processing, 3) reduction of the input data set, and 4) partition and conquest of the reduced data set. We perform a comprehensive performance evaluation on our algorithm and an alternative approach that formulates the U-Skyline processing problem by integer programming. Experimental results demonstrate that our algorithm is 10-100 times faster than using CPLEX, a parallel integer programming solver, to answer the U-Skyline query.

Maximizing acceptance probability for active friending in online social networks

Friending recommendation has successfully contributed to the explosive growth of online social networks. Most friending recommendation services today aim to support passive friending, where a user passively selects friending targets from the recommended candidates. In this paper, we advocate a recommendation support for active friending, where a user actively specifies a friending target. To the best of our knowledge, a recommendation designed to provide guidance for a user to systematically approach his friending target has not been explored for existing online social networking services. To maximize the probability that the friending target would accept an invitation from the user, we formulate a new optimization problem, namely, Acceptance Probability Maximization (APM), and develop a polynomial time algorithm, called Selective Invitation with Tree and In-Node Aggregation (SITINA), to find the optimal solution. We implement an active friending service with SITINA on Facebook to validate our idea. Our user study and experimental results reveal that SITINA outperforms manual selection and the baseline approach in solution quality efficiently.

On social-temporal group query with acquaintance constraint

Three essential criteria are important for activity planning, including: (1) finding a group of attendees familiar with the initiator, (2) ensuring each attendee in the group to have tight social relations with most of the members in the group, and (3) selecting an activity period available for all attendees. Therefore, this paper proposes Social-Temporal Group Query to find the activity time and attendees with the minimum total social distance to the initiator. Moreover, this query incorporates an acquaintance constraint to avoid finding a group with mutually unfamiliar attendees. Efficient processing of the social-temporal group query is very challenging. We show that the problem is NP-hard via a proof and formulate the problem with Integer Programming. We then propose two efficient algorithms, SGSelect and STGSelect, which include effective pruning techniques and employ the idea of pivot time slots to substantially reduce the running time, for finding the optimal solutions. Experimental results indicate that the proposed algorithms are much more efficient and scalable. In the comparison of solution quality, we show that STGSelect outperforms the algorithm that represents manual coordination by the initiator.

DigitSpace: Designing Thumb-to-Fingers Touch Interfaces for One-Handed and Eyes-Free Interactions

Thumb-to-fingers interfaces augment touch widgets on fingers, which are manipulated by the thumb. Such interfaces are ideal for one-handed eyes-free input since touch widgets on the fingers enable easy access by the stylus thumb. This study presents DigitSpace, a thumb-to-fingers interface that addresses two ergonomic factors: hand anatomy and touch precision. Hand anatomy restricts possible movements of a thumb, which further influences the physical comfort during the interactions. Touch precision is a human factor that determines how precisely users can manipulate touch widgets set on fingers, which determines effective layouts of the widgets. Buttons and touchpads were considered in our studies to enable discrete and continuous input in an eyes-free manner. The first study explores the regions of fingers where the interactions can be comfortably performed. According to the comfort regions, the second and third studies explore effective layouts for button and touchpad widgets. The experimental results indicate that participants could discriminate at least 16 buttons on their fingers. For touchpad, participants were asked to perform unistrokes. Our results revealed that since individual participant performed a coherent writing behavior, personalized