18364887
An approach to enhancing mobile applications with situation-awareness capabilities
In ubiquitous computing environments, mobile applications reside in devices that move arbitrarily and communicate with each other through wireless means. They are presented with fast changing situations, such as the location variation, service availability change, and resource fluctuation. Under these circumstances, situation-awareness is a desirable feature for mobile applications. Being situation-aware, a mobile application is capable of detecting situation changes and responding to it on-the-fly without bothering the user all the times. This paper presents an approach to enhancing mobile applications with situation-aware capabilities using middleware service.
13186882
Distributed constraint satisfaction, restricted recombination, and genetic protocols
In this paper, we present four genetic protocols for solving randomly generated distributed constraint satisfaction problems. These genetic protocols are based on an evolutionary paradigm known as a society of hill-climbers (SoHC) and are thus referred to as genetic SoHCs (GSoHCs). The difference between the SoHC and the GSoHCs is that each of the GSoHCs use a distributed restricted recombination operator. We compare the SoHC and GSoHC protocols on a test suite of 400 randomly generated distributed constraint satisfaction problems (DisCSPs) that are composed of asymmetric constraints (referred to as DisACSPs). In a second experiment, we compare the best performing GSoHC and the SoHC on an additional 1100 randomly generated DisACSPs in order to compare their performances across the phase transition. Our results show that all of the GSoHCs dramatically outperform the SoHC protocol even at the phase transition where, on average, the most difficult DisACSPs reside.
6831574
Situation-Aware Caching Strategies in Highly Varying Mobile Networks
Some emerging applications in mobile ad hoc networks (MANETs) and mobile sensor networks (MSNs) have varying mobility patterns that entails different routing strategies at different times to maintain high performance. This requires the routing protocol to adapt to different situations for better overall routing performance. We propose a model-based approach to enable such situation-awareness for the Dynamic Source Routing (DSR) protocol in such challenging environments. Our model captures the access behavior of route cache (hit, miss, and false hit) and is simple enough to be used in real-world settings. We also present a feedback-based architecture that uses the model outputs to cope with mobility changes by adjusting caching strategy on-the-fly. We validate our model against ns-2 simulations for a variety of scenarios, including a real-world mobility. Our results show that the model can aptly drive adaptive routing that leads to consistent performance improvement over DSR for the scenarios considered.
14692168
Testbed implementation of delay/fault-tolerant mobile sensor network (DFT-MSN)
In this paper we present a testbed implementation of delay/fault-tolerant mobile sensor network (DFT-MSN) for pervasive information gathering. We develop a simple and efficient data delivery scheme tailored for DFT-MSN, which consists of two key components for data transmission and queue management, respectively. The former makes decision on when and where to transmit data messages based on the delivery probability, which reflects the likelihood that a sensor can deliver data messages to the sink. The latter decides which messages to transmit or drop based on the fault tolerance, which indicates the importance of the messages. We implement the proposed data delivery scheme and establish a DFT-MSN testbed by using Crossbow sensors. A small scale experiment is carried out, which shows the effectiveness and efficiency of DFT-MSN
1078542
Energy-efficient computing for wildlife tracking: design tradeoffs and early experiences with ZebraNet
Over the past decade, mobile computing and wireless communication have become increasingly important drivers of many new computing applications. The field of wireless sensor networks particularly focuses on applications involving autonomous use of compute, sensing, and wireless communication devices for both scientific and commercial purposes. This paper examines the research decisions and design tradeoffs that arise when applying wireless peer-to-peer networking techniques in a mobile sensor network designed to support wildlife tracking for biology research.The ZebraNet system includes custom tracking collars (nodes) carried by animals under study across a large, wild area; the collars operate as a peer-to-peer network to deliver logged data back to researchers. The collars include global positioning system (GPS), Flash memory, wireless transceivers, and a small CPU; essentially each node is a small, wireless computing device. Since there is no cellular service or broadcast communication covering the region where animals are studied, ad hoc, peer-to-peer routing is needed. Although numerous ad hoc protocols exist, additional challenges arise because the researchers themselves are mobile and thus there is no fixed base station towards which to aim data. Overall, our goal is to use the least energy, storage, and other resources necessary to maintain a reliable system with a very high `data homing' success rate. We plan to deploy a 30-node ZebraNet system at the Mpala Research Centre in central Kenya. More broadly, we believe that the domain-centric protocols and energy tradeoffs presented here for ZebraNet will have general applicability in other wireless and sensor applications.
15418757
Fingerprint classification by directional fields
Fingerprint classification provides an important fingerprint index and can reduce fingerprint matching time in a large database. A good classification algorithm can give an accurate index that is able to search a fingerprint database more effectively. We present a fingerprint classification algorithm that is based on directional fields. We compute directional fields of fingerprint images and detect singular points (cores). Then, we extract features that we define from fingerprint images. We also use k-means classifier and 3-nearest neighbor to classify features and distinguish which fingerprint is Arch, Left Loop, Right Loop, or Whorl. Experimental results show a significant improvement in fingerprint classification performance. Moreover, the time required for the classification algorithm is reduced.
1016609
A 2D kinetic triangulation with near-quadratic topological changes
A triangulation of a set <i>S</i> of points in the plane is a subdivision of the convex hull of <i>S</i> into triangles whose vertices are points of <i>S</i>. Given a set <i>S</i> of <i>n</i> points in ℝ<sup>3</sup>, each moving independently, we wish to maintain a triangulation of S. The triangulation needs to be updated periodically as the points in <i>S</i> move, so the goal is to maintain a triangulation with small number of topological events, each being the insertion or deletion of an edge. We propose a kinetic data structure (KDS) that processes n<sup>2</sup> 2<sup>O(√log n•log log n )</sup> topological events, with high probability, if the trajectories of input points are algebraic curves of fixed degree. Each topological event can be processed in <i>O</i>(log <i>n</i>) time. This is the first known KDS for maintaining a triangulation that processes near-quadratic number of topological events, and almost matches the Ω(<i>n</i><sup>2</sup>) lower bound, [1]. The number of topological events can be reduced to nk • 2<sup>O(√log k•log log n )</sup> if only <i>K</i> of the points are moving.