46184949
Adaptive Deadlock-Free Wormhole Routing in Faulty Hypercubes
206892687
Recycled path routing in mobile ad hoc networks
In mobile ad hoc networks, many routing algorithms rely on some form of flooding to accomplish the route discovery process. Flooding, however, consumes many valuable network resources such as time, bandwidth, and power. Most current routing schemes expire valid routes after a time period to account for nodal movement. This paper proposes a new route discovery method, called recycled path routing (RPR), which directs broadcasts toward the destination node even in the absence of location information. The recycled path routing scheme reduces the search space for the destination node by implementing an expired route cache that is utilized by each node in the network. Routes are added to the expired route cache as they expire from the active route cache and remain there until some time interval has passed or a new route has been discovered. Since these expired routes can provide valuable insight into finding new routes, RPR uses them to direct broadcasts toward the destination node. RPR can save a significant quantity of valuable network resources because only nodes near the optimal path will rebroadcast route requests.
34087964
Wormhole Routing in Faulty Mesh Networks
3150650
Fault-Tolerant All-to-All Broadcasting in Hypercubes
29785948
Fast Replacement Route Discovery in Location-Aided Mobile Ad hoc Networks
20757485
Rigorous Modeling of Disk Performance for Real-Time Applications
Performance modeling of magnetic disks allows the prediction of the disk service time which is useful for on-line decision support for soft real-time applications. In this paper, we propose a new performance model of disk access time to estimate the bounded disk service time. Our proposed model focuses on modeling the head positioning time to fully utilize the disk I/O bandwidth by exploiting the geometric layout of the disk. The experimental results show that our proposed model can estimate the disk service time with less than 10% error on average.
17579236
Adaptive topology control for wireless Ad hoc networks
Topology control in ad-hoc networks is the problem of adjusting the transmission power at network nodes in order to achieve the optimal topology that maximizes network performance. Recently, using effective topology control to optimize energy usage in the network has come into focus in the research community [1, 2]. The common thesis arrived at by existing works is that the transmission range used by mobile nodes should be the minimum required to keep the network connected. We refer to such a topology as the minimally connected topology in the rest of the paper. We argue in this work that the minimally connected topology does not always provide the optimal performance in typical ad-hoc networks. We show that in contrast, for typical ad-hoc networks with a few hundred nodes distributed over a few square miles area, the optimal topology is a function of the traffic load.
34356748
Model-Based Human Motion Capture from Monocular Video Sequences
Generating motion and capturing motion of an articulated body for computer animation is an expensive and time-consuming task. Conventionally, animators manually generate intermediate frames between key frames, but this task is very labor-intensive. This paper presents a model-based singularity-free automatic-initialization approach to capturing human motion from widely-available, static background monocular video sequences. A 3D human body model is built and projected on a 2D projection plane to find the best fit with the foreground image silhouette. We convert the human motion capture problem into two types of parameter optimization problems: static optimization and dynamic optimization. First, we determine each model body configuration using static optimizations for every input image. Then, to obtain better description of motion, the results from all static optimizations are fed into a dynamic optimization process where the entire sequence of motion is considered for the user-specified motion. The user-specified motion is defined by the user and the final form of the motion they want. A cost function for static optimization is used to estimate the degree of overlapping between the foreground input image silhouette and a projected 3D model body silhouette. The overlapping is computed using computational geometry by converting a set of pixels from the image domain to a polygon in the real projection plane domain. A cost function for dynamic optimization is the user-specified motion based on the static optimization results as well as image fitting. Our method is used to capture various human motions: walking, pushing, kicking, and handshaking.
15182689
Chameleon: a resource scheduler in a data grid environment
Grid computing is moving into two ways. The Computational Grid focuses on reducing execution time of applications that require a great number of computer processing cycles. The Data Grid provides the way to solve large scale data management problems. Data intensive applications such as High Energy Physics and Bioinformatics require both Computational and Data Grid features. Job scheduling in Grid has been mostly discussed from the perspective of computational Grid. However, scheduling on Data Grid is just a recent focus of Grid computing activities. In Data Grid environment, effective scheduling mechanism considering both computational and data storage resources must be provided for large scale data intensive applications. In this paper, we describe new scheduling model that considers both amount of computational resources and data availability in Data Grid environment. We implemented a scheduler, called Chameleon, based on the proposed application scheduling model. Chameleon shows performance improvements in data intensive applications that require both large number of processors and data replication mechanisms. The results achieved from Chameleon are presented.
18395094
Quantitative analysis of transmission power control in wireless ad-hoc networks
In this paper, we address the issue of transmission power control in wireless ad-hoc networks. In general, it is assumed that the minimum transmission power required to keep the network connected achieves the optimal throughput performance in an ad-hoc network. In contrast, we show that using the minimal transmission range might not always result in optimal throughput performance. Using both throughput and throughput per unit energy as the optimization criteria, we demonstrate that the optimal transmission power is generically a function of the number of stations, the network size, and the traffic load. In particular, we observe that the optimal power is a function of the network load for typical network scenarios. To analyze these observations, we present an analytical model for throughput as function of the transmission power. The throughput model supports the results of our observations, i.e. for specific load conditions throughput is proportional to transmission power in typical ad-hoe networks. We conclude that the transmission power should be adaptive to the specific conditions in an ad-hoc network in order to maximize throughput performance.