A survey and analysis of multipath routing protocols in wireless multimedia sensor networks

The main objective of this research is to conduct a performance analysis of various multipath routing protocols in wireless multimedia sensor networks for the efficient transmission of the image, audio and video data. To provide efficient routing for the large sized multimedia content, various multipath routing protocols such as energy-aware routing, QoS based routing and geographical routing methods are analyzed. In this analysis, the efficient routing techniques including geographical routing techniques such as GPSR, DGR, PW-DGR presented for wireless multimedia sensor networks are studied and the performance of each technique is evaluated to determine the efficient multipath routing technique. Comparisons are made for evaluated protocols and it is proved that the PW-DGR provides better routing performance for the multimedia data. The findings of the research also show that the PW-DGR method efficiently overcomes the routing problems such as energy bottleneck problem, energy-hole, reduced network lifetime and high delay in packet transmission.     

Weighted Hyperbolic DV-Hop Positioning Node Localization Algorithm in WSNs

The localization of nodes plays a fundamental role in Wireless Sensor and Actors Networks (WSAN) identifying geographically where an event occurred, which facilitates timely response to this action. This article presents a performance evaluation of multi-hop localization range-free algorithms used in WSAN, such as Distance Vector Hop (DV-Hop), Improved DV-Hop (IDV-Hop), and the Weighted DV-Hop (WDV-Hop). In addition, we propose a new localization algorithm, merging WDV-Hop, with the weighted hyperbolic localization algorithm (WH), which includes weights to the correlation matrix of the estimated distances between the node of interest (NOI) and the reference nodes (RN) in order to improve accuracy and precision. As performance metrics, the accuracy, precision, and computational complexity are evaluated. The algorithms are evaluated in three scenarios where all nodes are randomly distributed in a given area, varying the number of RNs, the density of nodes in the network, and radio coverage of the nodes. The results show that in networks with 100 nodes, WDV-Hop outperforms the DV-Hop and IDV-Hop even if the number of RNs is reduced to 10. Moreover, our proposal shows an improvement in terms of accuracy and precision at the cost of increased computational complexity, specifically in the algorithm execution time, but without affecting the hardware cost or power consumption.     

Hop-Limit Path Mapping Algorithm for Virtual Network Embedding

Virtual network (VN) mapping which deals with the allocation of network resources from the shared physical substrate to individual VNs is one of the key challenges for the application of realizing network virtualization. While a variety of state-of-the-art algorithms have attempted to address this issue from different aspects, the challenge still remains for mapping virtual link with hop count constraint. This paper presents a fast approximation path mapping algorithm to address this issue by formulating such virtual link mapping problem as a path-flow mathematical programming model, which aims to minimize the maximum link load factor. Through the use of the primal–dual method, a fully polynomial time approximation algorithm is proposed to solve this model. The experimental results show that the proposed algorithm can effectively solve the problem of path mapping with hop limit.     

Global Optimization of Wireless Seismic Sensor Network Based on the Kriging Model and Improved Particle Swarm Optimization Algorithm

This study established the Kriging model to simplify the mathematical model for calculations and to improve the operational efficiency of global optimization in seismic exploration engineering. Accordingly, wireless seismic sensor network (WSSN) was used as an example in this research, and the generated seismic data flow rate and the flow rate of seismic data transmission are the simulation sample points. Thereafter, the Kriging model was constructed and the function was fitted. An improved particle swarm optimization (PSO) was also utilized for the global optimization of the Kriging model of WSSN to determine the optimized network lifetime. Results show that the Kriging model and the improved PSO algorithm significantly enhanced the lift performance and computer operational efficiency of WSSN.     

Ag/Ni Metallization Bilayer: A Functional Layer for Highly Efficient Polycrystalline SnSe Thermoelectric Modules

The structural and electrical characteristics of Ag/Ni bilayer metallization on polycrystalline thermoelectric SnSe were investigated. Two difficulties with thermoelectric SnSe metallization were identified for Ag and Ni single layers: Sn diffusion into the Ag metallization layer and unexpected cracks in the Ni metallization layer. The proposed Ag/Ni bilayer was prepared by hot-pressing, demonstrating successful metallization on the SnSe surface without interfacial cracks or elemental penetration into the metallization layer. Structural analysis revealed that the Ni layer reacts with SnSe, forming several crystalline phases during metallization that are beneficial for reducing contact resistance. Detailed investigation of the Ni/SnSe interface layer confirms columnar Ni-Sn intermetallic phases [(Ni₃Sn and Ni₃Sn₂) and Ni_5.63SnSe₂] that suppress Sn diffusion into the Ag layer. Electrical specific-contact resistivity (5.32 × 10^?4 Ω cm²) of the Ag/Ni bilayer requires further modification for development of high-efficiency polycrystalline SnSe thermoelectric modules.     

Thermal Stress Assessment for Transient Liquid-Phase Bonded Si Chips in High-Power Modules Using Experimental and Numerical Methods

The potential of transient liquid-phase (TLP) bonding for chip packaging applications has been evaluated, focusing on three interlayer arrangements (Ag-Sn-Ag, Ni-Sn-Ni, and Ag-Sn-Ni). Shear tests on TLP-bonded components provided the interlayer-dependent mechanical strength as well as failure mode and position. Critical local stresses, i.e., failure criteria, within the intermetallic compound (IMC) layer were derived by replicating the shear test conditions with finite-element methods. The missing coefficient of thermal expansion for Ag₃Sn IMC was obtained by producing small IMC bulk samples and subjecting them to dilatometric measurements. The experimental results were implemented into a finite-element model of a representative power module architecture to provide first predictions on thermally induced residual stresses that could be classified into fail/safe, as successfully validated by TLP chip bonding experiments. A numerical parameter study then assessed thermal stresses, including failure prediction and design optimization for TLP-bonded Si chips, considering the influence of process temperature, service conditions, TLP interlayer system, and metallization layers within the TLP joint. The presented procedure serves as a guideline to choose an appropriate TLP interlayer system for predefined boundary conditions, or vice versa.     

Solid-State Reaction Mechanism and Deliquescence Phenomenon of K<Subscript>0.5</Subscript>Na<Subscript>0.5</Subscript>Nb<Subscript>0.7</Subscript>Al<Subscript>0.3</Subscript>O<Subscript>3</Subscript> Ceramic

Development of (K,Na)NbO₃-based ceramics has attracted much attention in recent decades. In this work, K_0.5Na_0.5Nb_0.7Al_0.3O₃ ceramic was prepared using conventional solid-state processing. A deliquescence phenomenon was observed when the specimen was exposed to moist atmosphere. The reaction mechanism and cause of deliquescence were investigated using x-ray diffraction analysis, scanning electron microscopy, energy-dispersive spectrometry, electron microprobe analysis, inductively coupled plasma mass spectrometry, and thermogravimetric/differential scanning calorimetric analysis. The results revealed interactions mainly amongst the raw materials K₂CO₃, Na₂CO₃, and Nb₂O₅ as well as K₂CO₃, Na₂CO₃, and Al₂O₃, which can influence the sintering behavior of the mixture. (K,Na)NbO₃ and (K,Na)AlO₂ were present in the sintered K_0.5Na_0.5Nb_0.7Al_0.3O₃ ceramic, with the latter leading to deliquescence. During the sintering process, Al₂O₃ reacts with alkali oxides (Na₂O and K₂O), which are the decomposition products of carbonates, to form (K,Na)AlO₂. In addition, Al₂O₃ is more likely to react with K₂O compared with Na₂O.     

Computationally highly efficient mixture of adaptive filters

We introduce a new combination approach for the mixture of adaptive filters based on the set-membership filtering (SMF) framework. We perform SMF to combine the outputs of several parallel running adaptive algorithms and propose unconstrained, affinely constrained and convexly constrained combination weight configurations. Here, we achieve better trade-off in terms of the transient and steady-state convergence performance while providing significant computational reduction. Hence, through the introduced approaches, we can greatly enhance the convergence performance of the constituent filters with a slight increase in the computational load. In this sense, our approaches are suitable for big data applications where the data should be processed in streams with highly efficient algorithms. In the numerical examples, we demonstrate the superior performance of the proposed approaches over the state of the art using the well-known datasets in the machine learning literature.     

Linear-time prediction mode reduction method for intracoding in H.264/AVC

We present a linear-time elimination method to adaptively reduce the nine intraprediction modes in H.264/AVC to two, three, five, or nine modes while preserving a satisfactory reconstructed video quality. Resemblance between prediction modes and appearing frequency for each prediction mode are first determined in an off-line way from the training video sequences. Prediction modes are modeled as vertices and resemblance between two prediction modes as the weight of the connecting edge in a complete graph. Then, find the Hamilton cycle with the minimum sum of weights. When encoding each intrablock, prediction modes corresponding to the adjacent vertices along the Hamilton cycle are examined for similarity. The prediction mode which appears less frequently in a pair of similar prediction modes is declared as redundant and eliminated. When compared with Laroche et al.’s method which aims to reduce the bitrate, experimental results demonstrate that the proposed elimination method can substantially reduce the execution time while preserving the peak signal-to-noise ratio and bitrate performance.     

A joint-optimization NSAF algorithm based on the first-order Markov model

Recently, the normalized subband adaptive filter (NSAF) algorithm has attracted much attention for handling colored input signals. Based on the first-order Markov model of the optimal weight vector, this paper provides some insights for the convergence of the standard NSAF. Following these insights, both the step size and the regularization parameter in the NSAF are jointly optimized by minimizing the mean-square deviation. The resulting joint-optimization step size and regularization parameter algorithm achieves a good tradeoff between fast convergence rate and low steady-state error. Simulation results in the context of acoustic echo cancelation demonstrate good features of the proposed algorithm.