14953818
Backbone construction in selfish wireless networks
We present a protocol to construct routing backbones in wireless networks composed of selfish participants. Backbones are inherently cooperative, so constructing them in selfish environments is particularly difficult; participants want a backbone to exist (soothers relay their packets) but do not want to join the backbone (so they do not have to relay packets for others).
 We model the wireless backbone as a public good and use impatience as an incentive for cooperation. To determine if and when to donate to this public good, each participant calculates how patient it should be in obtaining the public good. We quantify patience using the Volunteer's Timing Dilemma (VTD), which we extend to general multihop network settings. Using our generalized VTD analysis, each node individually computes as its dominant strategy the amount of time to wait before joining the backbone. We evaluate our protocol using both simulations and an implementation. Our results show that, even though participants in our system deliberately wait before volunteering, a backbone is formed quickly. Further, the quality of the backbone (such as the size and resulting network lifetime) is comparable to that of existing backbone protocols that assume altruistic behavior.
38607714
Cooperative peer groups in NICE
A distributed scheme for trust inference in peer-to-peer networks is presented. Our work is in context of the NICE system, which is a platform for implementing cooperative applications over the Internet. We describe a technique for efficiently storing user reputation information in a completely decentralized manner, and show how this information can be used to efficiently identify noncooperative users in NICE. We present a simulation based study of our algorithms, in which we show our scheme scales to thousands of users using modest amounts of storage, processing, and bandwidth at any individual node. Lastly, we show that our scheme is robust and can form cooperative groups in systems where the vast majority of users are malicious.
5490648
Cooperative peer groups in NICE
We present a distributed scheme for trust inference in peer-to-peer networks. Our work is in the context of the NICE system, which is a platform for implementing cooperative applications over the Internet. We describe a technique for efficiently storing user reputation information in a completely decentralized manner, and show how this information can be used to efficiently identify non-cooperative users in NICE. We present a simulation-based study of our algorithms, in which we show our scheme scales to thousands of users using modest amounts of storage, processing, and bandwidth at any individual node. Lastly we show that our scheme is robust and can form cooperative groups in systems where the vast majority of users are malicious.
13015161
Neighbor supporting ad hoc multicast routing protocol
An ad hoc network is a multi-hop wireless network formed by a collection of mobile nodes without the intervention of fixed infrastructure. Limited bandwidth and a high degree of mobility require that routing protocols for ad hoc networks be robust, simple, and energy-conserving. This paper proposes a new ad hoc multicast routing protocol called Neighbor-Supporting Multicast Protocol (NSMP). NSMP adopts a mesh structure to enhance resilience against mobility. And NSMP utilizes node locality to reduce the overhead of route failure recovery and mesh maintenance. NSMP also attempts to improve route efficiency and reduce data transmissions. Our simulation results show that NSMP delivers packets efficiently while substantially reducing control overhead in various environments.
7311086
The case for a multi-hop wireless local area network
We propose a multi-hop wireless LAN architecture and demonstrate its benefits to wireless clients. For this architecture, we define implementation paths that allow interoperation with existing wireless LANs which can lead to an incremental deployment of this system. We quantify the performance benefits of the proposed schemes through measurements in realistic wireless LAN environments. We also examine the performance of such multi-hop wireless LANs through detailed simulation studies. Our results show that these multi-hop extensions can significantly improve the wireless access experience (in terms of data throughput, latency, etc.) for clients who enable such mechanisms. More interestingly, when multi-hop extensions are enabled by some of the clients, it also positively impacts the performance at other clients that are completely unaware of these extensions.
6107286
Efficient geographic routing in multihop wireless networks
We propose a new link metric called normalized advance (NADV) for geographic routing in multihop wireless networks. NADV selects neighbors with the optimal trade-off between proximity and link cost. Coupled with the local next hop decision in geographic routing, NADV enables an adaptive and efficient cost-aware routing strategy. Depending on the objective or message priority, applications can use the NADV framework to minimize various types of link cost.We present efficient methods for link cost estimation and perform detailed simulations in diverse scenarios. Our results show that NADV outperforms current schemes in many aspects: for example, in high noise environments with frequent packet losses, the use of NADV leads to 81% higher delivery ratio. When compared to centralized routing under certain settings, geographic routing using NADV finds paths whose cost is close to the optimum.
852427
Multisensor raster and vector data fusion based on uncertainty modeling
We propose a new methodology for fusing temporally changing multisensor raster and vector data by developing a spatially and temporally varying uncertainty model of acquired and transformed multisensor measurements. The proposed uncertainty model includes errors due to (1) each sensor by itself, e.g., sensor noise; (2) transformations of measured values to obtain comparable physical entities for data fusion and/or to calibrate sensor measurements; (3) vector data spatial interpolation that is needed to match different spatial resolutions of multisensor data; and (4) temporal interpolation that has to take place if multisensor acquisitions are not accurately synchronized. The proposed methodology was tested using simulated data with varying (a) amount of sensor noise, (b) spatial offset of point sensors generating vector data, and (c) model complexity of the underlying physical phenomenon. We demonstrated the multisensor fusion approach with a data set from a structural health monitoring application domain.
9314363
Feature sensitive mesh segmentation with mean shift
Feature sensitive mesh segmentation is important for many computer graphics and geometric modeling applications. In this paper, we develop a mesh segmentation method, which is capable of producing high-quality shape partitioning. It respects fine shape features and works well on various types of shapes, including natural shapes and mechanical parts. The method combines a procedure for clustering mesh normals with a modification of the mesh clarification technique. For clustering of mesh normals, we adopt Mean Shift, a powerful general purpose technique for clustering scattered data. We demonstrate advantages of our method by comparing it with two state-of-the-art mesh segmentation techniques.
11001952
A hotspot mitigation protocol for ad hoc networks
Abstract Hotspots represent transient but highly congested regions in wireless ad hoc networks that result in increased packet loss, end-to-end delay, and out-of-order packets delivery. We present a simple, effective, and scalable hotspot mitigation protocol (HMP) where mobile nodes independently monitor local buffer occupancy, packet loss, and MAC contention and delay conditions, and take local actions in response to the emergence of hotspots, such as, suppressing new route requests and rate controlling TCP flows. We use analysis, simulation, and experimental results from a wireless testbed to demonstrate the effectiveness of HMP in mobile ad hoc networks. HMP balances resource consumption among neighboring nodes, and improves end-to-end throughput, delay, and packet loss. Our results indicate that HMP can also improve the network connectivity preventing premature network partitions. We present analysis of hotspots, and the detailed design of HMP. We evaluate the protocol’s ability to effectively mitigate hotspots in mobile ad hoc networks that are based on on-demand and proactive routing protocols.
6659898
On-Demand Multicast Routing Protocol in Multihop Wireless Mobile Networks
An ad hoc network is a dynamically reconfigurable wireless network with no fixed infrastructure or central administration. Each host is mobile and must act as a router. Routing and multicasting protocols in ad hoc networks are faced with the challenge of delivering data to destinations through multihop routes in the presence of node movements and topology changes. This paper presents the On-Demand Multicast Routing Protocol (ODMRP) for wireless mobile ad hoc networks. ODMRP is a mesh-based, rather than a conventional tree-based, multicast scheme and uses a forwarding group concept; only a subset of nodes forwards the multicast packets via scoped flooding. It applies on-demand procedures to dynamically build routes and maintain multicast group membership. ODMRP is well suited for ad hoc wireless networks with mobile hosts where bandwidth is limited, topology changes frequently, and power is constrained. We evaluate ODMRP performance with other multicast protocols proposed for ad hoc networks via extensive and detailed simulation.
776311
American sign language recognition in game development for deaf children
CopyCat is an American Sign Language (ASL) game, which uses gesture recognition technology to help young deaf children practice ASL skills. We describe a brief history of the game, an overview of recent user studies, and the results of recent work on the problem of continuous, user-independent sign language recognition in classroom settings. Our database of signing samples was collected from user studies of deaf children playing aWizard of Oz version of the game at the Atlanta Area School for the Deaf (AASD). Our data set is characterized by disfluencies inherent in continuous signing, varied user characteristics including clothing and skin tones, and illumination changes in the classroom. The dataset consisted of 541 phrase samples and 1,959 individual sign samples of five children signing game phrases from a 22 word vocabulary. Our recognition approach uses color histogram adaptation for robust hand segmentation and tracking. The children wear small colored gloves with wireless accelerometers mounted on the back of their wrists. The hand shape information is combined with accelerometer data and used to train hidden Markov models for recognition. We evaluated our approach by using leave-one-out validation; this technique iterates through each child, training on data from four children and testing on the remaining child's data. We achieved average word accuracies per child ranging from 91.75% to 73.73% for the user-independent models.