A Novel Heterogeneous Clustering Protocol for Lifetime Maximization of Wireless Sensor Network

The network lifetime of Wireless Sensor Network (WSN) is one of the most challenging issues for any network protocol. The nodes in the network are densely deployed and are provided with limited power supply. The routing strategy is treated as an effective solution to improve the lifetime of the network. The cluster based routing techniques are used in the WSN to enhance the network lifespan and to minimize the energy consumption of the network. In this paper, an energy efficient heterogeneous clustering protocol for the enhancement of the network lifetime is proposed. The proposed protocol uses the sensor energy for the clustering process in a well-organized manner to maximize the lifetime of network. The MATLAB simulator is used for implementing the clustering model of proposed protocol and for measuring the effectiveness of the proposed technique the comparison is performed with the various existing approaches such as Stability Election Protocol, Distributed Energy Efficient Clustering and Adaptive Threshold Energy Efficient cross layer based Routing.

     

A Low-Power Wide-Dynamic-Range Analog VLSI Cochlea

Low-power wide-dynamic-range systems are extremely hard to build. The biological cochlea is one of the most awesome examples of such a system: It can sense sounds over 12 orders of magnitude in intensity, with an estimated power dissipation of only a few tens of microwatts. In this paper, we describe an analog electronic cochlea that processes sounds over 6 orders of magnitude in intensity, and that dissipates 0.5 mW. This 117-stage, 100 Hz to 10 KHz cochlea has the widest dynamic range of any artificial cochlea built to date. The wide dynamic range is attained through the use of a wide-linear-range transconductance amplifier, of a low-noise filter topology, of dynamic gain control (AGC) at each cochlear stage, and of an architecture that we refer to as overlapping cochlear cascades. The operation of the cochlea is made robust through the use of automatic offset-compensation circuitry. A BiCMOS circuit approach helps us to attain nearly scale-invariant behavior and good matching at all frequencies. The synthesis and analysis of our artificial cochlea yields insight into why the human cochlea uses an active traveling-wave mechanism to sense sounds, instead of using bandpass filters. The low power, wide dynamic range, and biological realism make our cochlea well suited as a front end for cochlear implants.     

Cost analysis of a multi-component parallel redundant complex system with overloading effect and waiting under critical human error

The cost analysis of a multi-component parallel redundant complex system is considered, incorporating the concept of overloading effect and waiting time for repair under critical human error. Failure and waiting times follow an exponential time distribution, whereas repair time follows a general distribution. Using the supplementary variable technique, Laplace transforms of the probabilities of the complex system being in various states have been computed. Some graphs have been plotted to highlight the main results.     

Effect of puffing on oil characteristics ofAmaranth (Rajgeera) seeds

Puffing or popping is a common method of processingAmaranthus cruentus (Syn.Amaranthus paniculatus L. or Rajgeera) grain. Investigations into the effect of this processing treatment have shown the percent unsaturation in the oil to decrease from 75.5% to 62.3%. The maximum effect is on linoleic acid, the quantity of which decreased sharply from 46.8% to 27.0%. Squalene also increased by 15.5%, due to puffing of amaranth seeds.     

Rate-distortion optimized tree-structured compression algorithms for piecewise polynomial images.

This paper presents novel coding algorithms based on tree-structured segmentation, which achieve the correct asymptotic rate-distortion (R-D) behavior for a simple class of signals, known as piecewise polynomials, by using an R-D based prune and join scheme. For the one-dimensional case, our scheme is based on binary-tree segmentation of the signal. This scheme approximates the signal segments using polynomial models and utilizes an R-D optimal bit allocation strategy among the different signal segments. The scheme further encodes similar neighbors jointly to achieve the correct exponentially decaying R-D behavior (D(R) - c(o)2(-c1R)), thus improving over classic wavelet schemes. We also prove that the computational complexity of the scheme is of O(N log N). We then show the extension of this scheme to the two-dimensional case using a quadtree. This quadtree-coding scheme also achieves an exponentially decaying R-D behavior, for the polygonal image model composed of a white polygon-shaped object against a uniform black background, with low computational cost of O(N log N). Again, the key is an R-D optimized prune and join strategy. Finally, we conclude with numerical results, which show that the proposed quadtree-coding scheme outperforms JPEG2000 by about 1 dB for real images, like cameraman, at low rates of around 0.15 bpp.     

Parametric Optimization of Complementary Split-Ring Resonator Dimensions for Planar Antenna Size Miniaturization

Wireless Personal Communications -     

Reliability of large periphery GaN-on-Si HFETs

GaN devices exhibit excellent potential for use in many RF applications. However, commercial acceptance of the technology has been hindered by the scarcity and non-statistical nature of reliability results. In this work we present a full device level reliability study of GaN-on-Si HFETs. Reliability results on this technology include three-temperature DC data that show an activation energy of 1.7 eV and an average failure time >10⁷ h at 150 °C. Additionally, long duration DC lifetest (30 000 device hours) and RF lifetest (4000 device hours) results demonstrate a repeatable low drift process. Environmental tests such as autoclave and ESD demonstrate the ruggedness of the material system and technology. Finally, initial failure analysis is discussed.     

Distributed dynamic fault-tolerant channel allocation for cellularnetworks

Efficient allocation of communication channels is critical for the performance of cellular systems. The centralized channel allocation algorithms proposed in literature are neither robust nor scalable. Several of these algorithms are unable to dynamically adjust to spatial and temporal fluctuations in channel demand (load). We present a distributed dynamic channel allocation (DCA) algorithm in which heavily loaded regions acquire a large number of communication channels, while their lightly loaded neighbors get assigned fewer channels. As the spatial distribution of channel demand changes with time, the spatial distribution of allocated channels adjusts accordingly. The algorithm described in this paper requires minimal involvement of the mobile nodes, thus conserving their limited energy supply. The algorithm is proved to be deadlock free, starvation free, and fair. It prevents cochannel interference and can tolerate the failure of mobile as well as static nodes without any significant degradation in service. Simulation experiments demonstrate that the performance of the proposed distributed dynamic algorithm is comparable to, and for some metrics, better than that of efficient centralized dynamic algorithms where the central switch has complete and latest information about channel availability. The major advantages of the proposed algorithm over its dynamic centralized counterparts are its scalability, flexibility, and low computation and communication overheads     

Fair queueing with service envelopes (FQSE): a cousin-fair hierarchical scheduler for subscriber access networks

In this paper, we propose and investigate the characteristics of a fair queueing with service envelopes (FQSE) algorithm-a hierarchical fair-share scheduling algorithm for access networks based on a remote scheduling system such as Ethernet passive optical networks (EPON) or cable TV network. FQSE is designed to overcome the limiting factors of a typical remote scheduling system such as large control-plane delay, limited control-plane bandwidth, and significant queue switch-over overhead. The algorithm is based on a concept of service envelope-a function representing the fair allocation of resources based on a global network condition called satisfiability parameter (SP). We define properties of cousin-fairness and sibling-fairness and show the FQSE to be cousin-fair. FQSE is unique in that it is the only hierarchical algorithm that is simultaneously cousin-fair. Furthermore, we show the necessary techniques to adapt FQSE to variable-sized packet-based networks. We analyze FQSE performance in EPON serving 1024 independent queues and demonstrate FQSE's ability to provide guaranteed bandwidth to each queue and to share the excess bandwidth fairly.     

ORuML: Optimized Routing in wireless networks using Machine Learning

Routing is a process of selecting a path in a network for delivering a packet from source node to destination node. Successful delivery of a message is a challenge, and therefore, this paper proposes an algorithm for a wireless network called Optimized Routing in wireless networks using Machine Learning (ORuML), which uses machine learning algorithm namely, K‐nearest neighbor (KNN), Support Vector Machine (SVM), and Multinomial Logistic Regression (MLR), to predict the network type of the source and destination nodes. The ML model is trained by using characteristic features of a node collected in real time such as battery power utilization, available internal storage, IP address, and range of a node. Intuitively, the MLR should outperform KNN and SVM in terms of accuracy and Area under ROC Curve (AUC). The proposed algorithm determines whether the source and destination nodes are co‐located and also, determines the best neighboring hop for efficient routing.