Reliable Mobicast via Face-Aware Routing

This paper presents a novel protocol for a spatiotemporal variant of multicast called mobicast, designed to support message delivery in sensor and mobile ad hoc networks. The spatiotemporal character of mobicast relates to the obligation to deliver a message to all the nodes that will be present at time t in some geographic zone Z, where both the location and shape of the delivery zone are a function of time over some interval (tstart, tend). The protocol, called Face-Aware Routing (FAR), exploits ideas adapted from existing applications of face routing to achieve reliable mobicast delivery. The key features of the protocol are a routing strategy, which uses information confined solely to a node’s immediate spatial neighborhood, and a forwarding schedule, which employs only local topological information. Statistical results showing that, in uniformly distributed random disk graphs, the spatial neighborhood size is usually less than 20 suggest that FAR is likely to exhibit a low average memory cost. An estimation formula for the average size of the spatial neighborhood in random network is another analytical result reported in this paper. This paper also includes a novel and low cost distributed algorithm for spatial neighborhood discovery

FAR: Face-Aware Routing for Mobicast in Large-Scale Sensor Networks

This paper presents FAR, a Face-Aware Routing protocol for mobicast, a spatiotemporal variant of multicast tailored for sensor networks with environmental mobility. FAR features face-routing and timed-forwarding for delivering a message to a mobile delivery zone. Both analytical and statistical results show that, FAR achieves reliable and just-in-time mes-sage delivery with only moderate communication and memory overhead. This paper also presents a novel distributed algorithm for spatial neighborhood discovery for FAR boot-strapping. The spatiotemporal performance and reliability of FAR are demonstrated via ns-2 simulations

Minimum Power Configuration in Wireless Sensor Networks

This paper proposes the minimum power configuration (MPC) approach to energy conservation in wireless sensor networks. In sharp contrast to earlier research that treats topology control, power-aware routing, and sleep management in isolation, MPC integrates them as a joint optimization prob-lem in which the power configurationof a network consists of a set of active nodes and the transmission powers of the nodes. We show through analysis that the minimum power configu-ration of a network is inherently dependent on the data rates of sources. We propose several approximation algorithms with provable performance bounds compared to the optimal solu-tion, and a practical Minimum Power Configuration Protocol (MPCP) that can dynamically (re)configure a network to mini-mize the energy consumption based on current data rates. Sim-ulations based on realistic radio models of the Mica2 motes show that MPCP can conserve significantly more energy than existing minimum power routing and topology control protocols

Minimum Power Configuration for Wireless Communication in Sensor Networks

This paper proposes the Minimum Power Configuration (MPC) approach to power management in wireless sensor networks. In contrast to earlier research that treats different radio states (transmission/reception/idle) in isolation, MPC integrates them in a joint optimization problem that depends on both the set of active nodes and the transmission power. We propose four approximation algorithms with provable performance bounds and two practical routing protocols. Simulations based on realistic radio models show that the MPC approach can conserve more energy than existing minimum power routing and topology control protocols. Furthermore, it can flexibly adapt to network workload and radio platforms

Radial Velocities of Stars in the Galactic Center

We present results from K band slit scan observations of a ~20''x20'' region of the Galactic center (GC) in two separate epochs more than five years apart. The high resolution (R>=14,000) observations allow the most accurate radial velocity and acceleration measurements of the stars in the central parsec of the Galaxy. Detected stars can be divided into three groups based on the CO absorption band heads at ~2.2935 microns and the He I lines at ~2.0581 microns and ~2.112, 2.113 microns: cool, narrow-line hot and broad-line hot. The radial velocities of the cool, late-type stars have approximately a symmetrical distribution with its center at ~-7.8(+/-10.3) km/s and a standard deviation ~113.7(+/-10.3) km/s. Although our statistics are dominated by the brightest stars, we estimate a central black hole mass of 3.9(+/-1.1) million solar masses, consistent with current estimates from complete orbits of individual stars. Our surface density profile and the velocity dispersion of the late type stars support the existence of a low density region at the Galactic center suggested by earlier observations. Many hot, early-type stars show radial velocity changes higher than maximum values allowed by pure circular orbital motions around a central massive object, suggesting that the motions of these stars greatly deviate from circular orbital motions around the Galactic center. The correlation between the radial velocities of the early type He I stars and their declination offsets from Sagittarius A* suggests that a systematic rotation is present for the early-type population. No figure rotation around the Galactic center for the late type stars is supported by the new observations.Comment: 61 pages, 18 figures, 7 tables; accepted for publication in Astrophysical Journa

A Car-Following Model Based on Quantified Homeostatic Risk Perception

This study attempts to elucidate individual car-following behavior using risk homeostasis theory (RHT). On the basis of this theory and the stimulus-response concept, we develop a desired safety margin (DSM) model. Safety margin, defined as the level of perceived risk in car-following processes, is proposed and considered to be a stimulus parameter. Acceleration is assessed in accordance with the difference between the perceived safety margin (perceived level of risk) and desired safety margin (acceptable level of risk) of a driver in a car-following situation. Sixty-three cases selected from Next Generation Simulation (NGSIM) are used to calibrate the parameters of the proposed model for general car-following behavior. Other eight cases with two following cars taken from NGSIM are used to validate the model. A car-following case with stop-and-go processes is also used to demonstrate the performance of the proposed model. The simulation results are then compared with the calculations derived using the Gazis-Herman-Rothery (GHR) model. As a result, the DSM and GHR models yield similar results and the proposed model is effective for simulation of car following. By adjusting model parameters, the proposed model can simulate different driving behaviors. The proposed model gives a new way to explain car-following process by RHT