Energy Minimization for Real-Time Data Gathering in Wireless Sensor Networks

This paper studies the challenging problem of energy minimization for data gathering over a multiple-sources single-sink communication substrate in wireless sensor networks by exploring the energy-latency tradeoffs using rate adaptation techniques. We consider a real-time scenario for mission-critical applications, where the data gathering must be performed within a specified latency constraint. We first propose an offline numerical optimization algorithm with performance analysis for a special case with a complete binary data gathering tree. Then, by discretizing the transmission time, we present a simple, distributed on-line protocol that relies only on the local information available at each sensor node. Extensive simulations were conducted for both long and short-range communication scenarios using two different source placement models. We used the baseline of transmitting all packets at the highest speed and shutting down the radios afterwards. Our simulation results show that compared with this baseline, up to 90% energy savings can be achieved by our techniques (both off-line and on-line), under different settings of several key system parameters     

ISHair: Importance Sampling for Hair Scattering

We present an importance sampling method for the bidirectional scattering distribution function (bsdf) of hair. Our method is based on the multi‐lobe hair scattering model presented by Sadeghi et al. [ [SPJT10] ]. We reduce noise by drawing samples from a distribution that approximates the bsdf well. Our algorithm is efficient and easy to implement, since the sampling process requires only the evaluation of a few analytic functions, with no significant memory overhead or need for precomputation. We tested our method in a research raytracer and a production renderer based on micropolygon rasterization. We show significant improvements for rendering direct illumination using multiple importance sampling and for rendering indirect illumination using path tracing.     

Focus-engineered coherent anti-Stokes Raman scattering microscopy: a numerical investigation

The coherent anti-Stokes Raman scattering (CARS) signal is calculated as a function of focal-field distributions with engineered phase jumps. We show that the focal fields in CARS microscopy can be shaped such that the signal from the bulk is suppressed in the forward detection mode. We present the field distributions that display enhanced sensitivity to vibrationally resonant object interfaces in the lateral dimension. The use of focus-engineered CARS provides a simple means to detect chemical edges against the strong background signals from the bulk.     

On the Complexity of Distributed Self-Configuration in Wireless Networks

We consider three distributed configuration tasks that arise in the setup and operation of multi-hop wireless networks: partition into coordinating cliques, Hamiltonian cycle formation and conflict-free channel allocation. We show that the probabilities of accomplishing these tasks undergo zero-one phase transitions with respect to the transmission range of individual nodes. We model these tasks as distributed constraint satisfaction problems (DCSPs) and show that, even though they are NP-hard in general, these problems can be solved efficiently on average when the network is operated sufficiently far from the transition region. Phase transition analysis is shown to be a useful mechanism for quantifying the critical range of energy and bandwidth resources needed for the scalable performance of self-configuring wireless networks.     

Sensor network algorithms and applications

A sensor network is a collection of nodes with processing, communication and sensing capabilities deployed in an area of interest to perform a monitoring task. There has now been about a decade of very active research in the area of sensor networks, with significant accomplishments made in terms of both designing novel algorithms and building exciting new sensing applications. This Theme Issue provides a broad sampling of the central challenges and the contributions that have been made towards addressing these challenges in the field, and illustrates the pervasive and central role of sensor networks in monitoring human activities and the environment.     

Sequence-Based Localization in Wireless Sensor Networks

We introduce a novel sequence-based localization technique for wireless sensor networks. We show that the localization space can be divided into distinct regions that can each be uniquely identified by sequences that represent the ranking of distances from the reference nodes to that region. For n reference nodes in the localization space, combinatorially, O(n") sequences are possible, but we show that, due to geometric constraints, the actual number of feasible location sequences is much lower: only O(n ⁴). Using these location sequences, we develop a localization technique that is robust to random errors due to the multipath and shadowing effects of wireless channels. Through extensive systematic simulations and a representative set of real mote experiments, we show that our lightweight localization technique provides comparable or better accuracy than other state-of-the-art radio signal strength-based localization techniques over a range of wireless channel and node deployment conditions.     

Modeling path duration distributions in MANETs and their impact on reactive routing protocols

We develop a detailed approach to study how mobility impacts the performance of reactive mobile ad hoc network routing protocols. In particular, we examine how the statistics of path durations including probability density functions vary with the parameters such as the mobility model, relative speed, number of hops, and radio range. We find that at low speeds, certain mobility models may induce multimodal distributions that reflect the characteristics of the spatial map, mobility constraints and the communicating traffic pattern. However, this paper suggests that at moderate and high velocities the exponential distribution with appropriate parameterizations is a good approximation of the path duration distribution for a range of mobility models. Analytically, we show that the reciprocal of the average path duration has a strong linear relationship with the throughput and overhead of dynamic source routing (DSR), which is also confirmed by simulation results. In addition, we show how the mathematical expression obtained for the path duration distribution can also be used to prove that the nonpropagating cache hit ratio in DSR is independent of velocity for the freeway mobility model. These two case studies illustrate how various aspects of protocol performance can be analyzed with respect to a number of significant parameters including the statistics of link and path durations.     

Optimal Sequential Paging in Cellular Wireless Networks

In a high-capacity cellular network with limited spectral resources, it is desirable to minimize the radio bandwidth costs associated with paging when locating mobile users. Sequential paging, in which cells in the coverage area are partitioned into groups and paged in a non-increasing order of user location probabilities, permits a reduction in the average radio costs of paging at the expense of greater delay in locating the users. We present a polynomial time algorithm for minimizing paging cost under the average delay constraint, a problem that has previously been considered intractable. We show the conditions under which cluster paging, a simple heuristic technique proposed for use with dynamic location update schemes, is optimal. We also present analytical results on the average delay and paging cost obtained with sequential paging, including tight bounds.