Routing Correlated Data with Fusion Cost in Wireless Sensor Networks

In this paper, we propose a routing algorithm called minimum fusion Steiner tree (MFST) for energy efficient data gathering with aggregation (fusion) in wireless sensor networks. Different from existing schemes, MFST not only optimizes over the data transmission cost, but also incorporates the cost for data fusion, which can be significant for emerging sensor networks with vectorial data and/or security requirements. By employing a randomized algorithm that allows fusion points to be chosen according to the nodes' data amounts, MFST achieves an approximation ratio of 5/4log(k + 1), where k denotes the number of source nodes, to the optimal solution for extremely general system setups, provided that fusion cost and data aggregation are nondecreasing against the total input data. Consequently, in contrast to algorithms that only excel in full or nonaggregation scenarios without considering fusion cost, MFST can thrive in a wide range of applications     

Improved Thermal Performance of AlGaN/GaN HEMTs by an Optimized Flip-Chip Design

AlGaN/GaN high electron mobility transistors (HEMT) on sapphire substrates have been studied for their potential application in RF power applications; however, the low thermal conductivity of the sapphire substrate is a major drawback. Aiming at RF system-in-a-package, the authors propose a flip-chip-integration approach, where the generated heat is dissipated to an AlN carrier substrate. Different flip-chip-bump designs are compared, using thermal simulations, electrical measurements, micro-Raman spectroscopy, and infrared thermography. The authors show that a novel bump design, where bumps are placed directly onto both source and drain ohmic contacts, improves the thermal performance of the HEMT     

Recent Developments in Semipolar InGaN Laser Diodes

Semiconductors - Group III-nitride semiconductors (GaN, AlN, and InN) are attractive materials for a wide range of electronic and photonic applications. The most widely employed growth plane for...     

Aperture Field Estimation in E Plane and H-Plane T-Junctions Using Field Theoretic Analysis

Wireless Personal Communications - This paper presents method of moment based analysis of E Plane and H-Plane T-junctions to find the field distributions on different transverse and longitudinal...     

Exploiting information theory for adaptive mobility and resource management in future cellular networks

We utilize tools from information theory to develop adaptive algorithms for two key problems in cellular networks: location tracking and resource management. The use of information theory is motivated by the fundamental observation that overheads in many aspects of mobile computing can be traced to the randomness or uncertainty in an individual user's movement behavior. We present a model-independent information-theoretic approach for estimating and managing this uncertainty, and relate it to the entropy or information content of the user's movement process. Information-theoretic mobility management algorithms are very simple, yet reduce overhead by /spl sim/80 percent in simulated scenarios by optimally adapting to each individual's movement. These algorithms also allow for flexible tradeoff between location update and paging costs. Simulation results demonstrate how an information-theory-motivated resource provisioning strategy can meet QoS bounds with very small wastage of resources, thus dramatically reducing the overall blocking rate.     

A Finite Element Computational Method for Gas Hydrate. Part II: Application

A finite element model has been applied to the dissociation of gas hydrates in porous media by hot water injection. In the first step, it was applied to calculate the temperature and saturation profiles for a two-phase convective heat transfer case. The second step involved hydrate thawing calculations with release of water and gas. Realistic results were obtained in predicting the temperature, pressure, and water saturation profiles in the hydrate medium with respect to time, when subjected to hot water injection at high pressure in a wellbore. Furthermore, the thaw front progression calculated by this scheme exhibits stable and satisfactory behavior with respect to time.     

Throughput analysis in censoring-based cooperative cognitive radio network with energy harvesting

An energy harvesting (EH) and cooperative cognitive radio (CR) network (CRN) is studied in this paper where CR users transmit data through a primary user (PU) channel if the channel remains idle, else an optimal number CRs helps in transmission of PU. To achieve the optimum number of CRs (ONCR) involved in cooperation, a novel scheme based on a combination of channel censoring and total error is proposed. The performance of the proposed scheme is investigated under RF harvesting scenario. The EH is dependent on sensing decision and a CR source harvests energy from PU's RF signal. The harvested energy (HE) is split into two parts: One part is used by the CR network (CRN) for its own transmission, and the other part is used for supporting PU. The effect of the energy allocation factor on total throughput is also investigated. New expressions for optimal number of CRs and throughput are developed. The effect of network parameters such as sensing time, censoring threshold, and energy allocation parameter (EAP) on throughput is investigated. Impact of distance between nodes is also studied.     

Gecko‐Inspired Dry Adhesive for Robotic Applications

Most geckos can rapidly attach and detach from almost any kind of surface. This ability is attributed to the hierarchical structure of their feet (involving toe pads, setal arrays, and spatulae), and how they are moved (articulated) to generate strong adhesion and friction forces on gripping that rapidly relax on releasing. Inspired by the gecko's bioadhesive system, various structured surfaces have been fabricated suitable for robotic applications. In this study, x–y–z asymmetric, micrometer‐sized rectangular flaps composed of polydimethylsiloxane (PDMS) were fabricated using massively parallel micro‐electromechanical systems (MEMS) techniques with the intention of creating directionally responsive, high‐to‐low frictional‐adhesion toe pads exhibiting properties similar to those found in geckos. Using a surface forces apparatus (SFA), the friction and adhesion forces of both vertical (symmetric) and angled/tilted (x–y–z asymmetric) microflaps under various loading, unloading and shearing conditIons were investigated. It was found that the anisotropic structure of tilted microflaps gives very different adhesion and tribological forces when articulated along different x–y–z directions: high friction and adhesion forces when articulated in the y–z plane along the tilt (+y) direction, which is also the direction of motion, and weak friction and adhesion forces when articulated against the tilt (–y) direction. These results demonstrate that asymmetric angled structures, as occur in geckos, are required to enable the gecko to optimize the requirements of high friction and adhesion on gripping, and low frictional‐adhesion on releasing. These properties are intimately coupled to a (also optimum) articulation mechanism. We discuss how both of these features can be simultaneously optimized in the design of robotic systems that can mimic the gecko adhesive system.     

Wavelet and subband transforms: fundamentals and communicationapplications

Subband and wavelet transforms have been a subject of great interest, especially in the fields of signal processing and applied mathematics. This article presents a tutorial on this subject, emphasizing the fundamentals and the reason for its success, importance, and potential. Subband and wavelet transform applications in communications are also reviewed. These application areas include interference excision, spread spectrum codes based on subband transform bases, CDMA, and discrete multitone transceivers     

A selective location update strategy for PCS users

A new location update strategy for personal communication services (PCS) networks and its implementation using a genetic algorithm are proposed. Most of the practical cellular mobile systems partition a geographical region into location areas (LAs) and users are made to update on entering a new LA. The main drawback of this scheme is that it does not consider the individual user mobility and call arrival patterns. Combining these factors with the LAbased approach, we propose an optimal update strategy which determines whether or not a user should update in each LA, and minimizes the average location management cost derived from a userspecific mobility model and call generation pattern. The location management cost optimization problem is also elegantly solved using a genetic algorithm. Detailed simulation experiments are conducted to capture the effects of mobility and callarrival patterns on the location update strategy. The conclusion from this work is that skipping location updates in certain LAs leads to the minimization of the overall location management cost for a user with a specific mobility pattern and even with moderately high call arrival rate.