Energies Of Nodes Research Articles

An Energy Efficient Cluster Head Selection in WSN Based on Enhanced Chicken Swarm Optimization

Clustering of data are ab effective energy saving method for wireless sensor networks (WSN). However, they incur additional costs in data collections from sensor nodes and sending them to base station (BS) after aggregations. Cluster heads (CHs) in hierarchical cluster-based WSNs use more energy. Therefore, choosing a suitable CHs is essential to conserve energy for sensor nodes and prolong the life of the WSN. Provide energy-saving cluster head selection techniques in this work. where enhanced fuzzy means clustering is used to perform the first cluster construction. Enhanced Chick Swarm optimization (ECSO) selects CHs which is evaluated strictly for varying WSN scenarios and counts of CHs and nodes for values of remaining energies of sensor nodes, sink distances, and distances within clusters. To demonstrate that the proposed technique is superior, the results are compared with those of several other currently used algorithms.

A Security Key Management Method using Grid Routing for EDDK in WSNs

Wireless sensor networks (WSNs) utilize event data collected through sensor nodes, which can be employed in different environments. Sensor nodes used in WSNs have limited energy and can be easily compromised by attackers since they are placed in the external environment. Therefore, energy efficiency and security are core requirements in WSNs, and various schemes have been proposed to solve them. The energy-efficient distributed deterministic key management scheme (EDDK) is a security scheme that uses distributed pairwise keys. The EDDK encrypts the packet using the pairwise key of the neighboring node, and transmits the encrypted packet securely to the base station (BS). In addition, the pairwise key shared with neighboring nodes is updated to defend against network attacks such as Denial of Service. However, the energies of the sensor nodes decrease rapidly in environments where key updates occur frequently. Further, since EDDK does not encrypt the sequence number, the attacker can manipulate this sequence number. If such attacks are continually attempted, key updates occur frequently. This paper proposes a scheme that removes the local cluster key from the EDDK and instead uses a grid routing protocol. The proposed scheme reduces the number of key updates by removing the local cluster key. In addition, the proposed scheme constructs the routing as a grid and selects the sensor node nearest to the BS as the master node. the master node of the grid routing scheme transmits routing control messages to the corresponding sensor nodes. In this way, the proposed method improves the sensor network energy efficiency. Experimental results show that the energy efficiency of the sensor network is improved by about 7.8097% compared with EDDK. Additionally, since the proposed scheme removes the local cluster key, sequence number manipulation attacks can be avoided. As a result, the security rate of the proposed scheme is more than double compared with EDDK.

Energy-efficient routing protocol based on tree link topology in wireless sensor networks

Wireless sensor networks have been widely used in target monitoring application. It is often assumed in a typical target coverage algorithm that the environment is known, and each target is covered by only one node. However, these algorithms are not scalable. In fact, one target may need to be covered by more than one node, which is the K-coverage problem. Aiming at the application of target monitoring in wireless sensor network, a K-coverage model— kernal matrix based genetic algorithm (KMGA) based on the genetic algorithm—is proposed. The KMGA model ensures that each target is covered by multiple sensors simultaneously. First, multiple Covers are generated as much as possible through genetic algorithm, and then, while coverage requirements are ensured, coverage between Covers is switched based on remaining energies of nodes so as to extend the network life. Experimental data show that the proposed KMGA model can effectively extend the network lifetime and ensure coverage rate.

Saving Energy by an Alliance: An Adaptive Clustering Scheme for Wireless Sensor Networks

Generally, the applications of Wireless Sensor Networks (WSNs) need a deployment of a large population of sensor nodes. Therefore, the design of such networks requires scalable organizational and management strategies. To ensure network scalability and energy saving, sensor nodes could be grouped into clusters. WSNs' research community has given a high importance to clustering techniques in these networks during the last years. However, most of the existing clustering schemes focus on making sensor nodes periodically taking turns in fulfilling the burdening task of cluster heads. These solutions do not consider the consumed energy by the clustering mechanism itself which leads to waste the energies of sensor nodes. To cope with this problem, we propose an energy aware clustering scheme for WSNs based on a self-stabilizing algorithm. We term our scheme SEAC (Saving Energy by an Alliance-based Clustering). Sensor nodes execute a distributed algorithm which determines the set of nodes that form an alliance based on an energy condition. The alliance's sensor nodes are the cluster heads. SEAC does not perform re-clustering at each round. New cluster heads are selected when the energy condition is not verified. The frequency of re-clustering is decreased, which diminishes the communication overhead. Simulation results show that SEAC improves the network lifetime and consumes less energy with respect to existing approaches.

Analysis of QOS and Energy Consumption in IEEE 802. 15. 4/ZigBee Wireless Sensor Network

the last few years, Wireless sensor networks have gained worldwide attention from both the research communities and the actual users. It comprises of a large number of extremely small autonomous computing, communication, and sensing devices, with limited energy and computing capabilities which co-operates to accomplish a large sensing task. Wireless sensor network raise some problems like limited energy resources replacement task. Therefore good functions of such networks depend on energies of nodes. In this paper two analytical models which predict the QOS in terms of throughput, jitter, average end-to-end delay and energy consumption have been introduced. These two different formats of nodes are organized as cluster and grid based network and for simulation analysis QualNet 6.1 simulator is used. KeywordsIEEE 802.15.4, Cluster based, Grid based, ZigBee, QualNet 6.1 simulator 1. INTRODUCTIONWireless sensor networks (WSNs) are the most important technologies. It has gained world-wide attention in recent few years. These sensors are small, with limited transmission range, and computing resources. These sensor nodes are battery operated and need to operate without battery replacement for several years. There are two things which are to be reviewed i.e. how to achieve balancing energy drainage across all the nodes and how to achieve high routing efficiency under multihop transmission circumstance. Therefore, for designing such type of networks researchers must focus on both the energy consumption and routing efficiency.

Optimized hierarchical routing technique for wireless sensors networks

Wireless sensor networks are battery-powered ad hoc networks in which sensor nodes that are scattered over a region connect to each other and form multi-hop networks. Since these networks consist of sensors that are battery operated, care has to be taken so that these sensors use energy efficiently. This paper proposes an optimized hierarchical routing technique which aims to reduce the energy consumption and prolong network lifetime. In this technique, the selection of optimal cluster head (CHs) locations is based on artificial fish swarm algorithm that applies various behaviors such as preying, swarming, and following to the formulated clusters and then uses a fitness function to compare the outputs of these behaviors to select the best CHs locations. To prove the efficiency of the proposed technique, its performance is analyzed and compared to two other well-known energy efficient routing techniques: low-energy adaptive clustering hierarchy (LEACH) technique and particle swarm optimized (PSO) routing technique. Simulation results show the stability and efficiency of the proposed technique. Simulation results show that the proposed method outperforms both LEACH and PSO in terms of energy consumption, number of alive nodes, first node die, network lifetime, and total data packets received by the base station. This may be due to considering residual energies of nodes and their distance from base station , and alternating the CH role among cluster's members. Alternating the CH role balances energy consumption and saves more energy in nodes.

ScEP: A Scalable and Energy Aware Protocol to Increase Network Lifetime in Wireless Sensor Networks

Wireless Sensor Networks are known by cooperative endeavour of large deployment of sensors with limited battery power. One of the main challenges about these networks is how to minimize the energy consumption of sensor nodes which will lead to extended network life time. In this paper, we proposed an efficient protocol based on Map-Reduce computing model and a new clustering algorithm. In the proposed protocol, the cluster heads are determined based on the remaining energies of sensor nodes and their distance to base station. Experimental results with a prototype implementation of ScEP demonstrate considerable improvement in enhancing both network lifetime and residual energies of sensor nodes compared to when the two main related work, MRKCP and LEACH is used.

(111)surface states of SnTe

The characterization and applications of topological insulators depend critically on their protected surface states, which, however, can be obscured by the presence of trivial dangling bond states. Our first principle calculations show that this is the case for the pristine $(111)$ surface of SnTe. Yet, the predicted surface states unfold when the dangling bond states are passivated in proper chemisorption. We further extract the anisotropic Fermi velocities, penetration lengths and anisotropic spin textures of the unfolded $\bar\Gamma$- and $\bar M$-surface states, which are consistent with the theory in http://dx.doi.org/10.1103/PhysRevB.86.081303 Phys. Rev. B 86, 081303 (R). More importantly, this chemisorption scheme provides an external control of the relative energies of different Dirac nodes, which is particularly desirable in multi-valley transport.

Signal power random fading based interference-aware routing for wireless sensor networks

Power loss and interference coexist in wireless transmissions where random uncertainty is aggravated due to the mobility of sensor nodes. A probability interference model was proposed, based on the physical model and random fading of the received signal power, to depict the uncertainty of wireless interference. In addition, an interference-aware routing metric was designed, in which interference, routing convergence and residual energies of nodes were integrated. Furthermore, an interference-aware probabilistic routing algorithm was proposed for mobile wireless sensor networks, and its correctness and time and space complexities were proved. The NS-2 simulation experiments showed that the proposed algorithm can achieve higher packet delivery ratio than Greedy Perimeter Stateless Routing in various cases like the pause time and maximum moving speed. Simultaneously, the energy consumption of a packet and average delay were taken into consideration to better meet the needs of mobile scenarios with higher reliability.

Enhancing Coverage Ratio Using Mobility in Heterogeneous Wireless Sensor Network

In the lifespan of the sensor network, coverage, localization, reliability and lifetime (when the final sensor dies) are the major design challenges for which the work is still going on. Especially in heterogeneous wireless sensor network, it is very difficult to estimate the coverage and lifetime of the network. There have been many existing classical protocols in heterogeneous network where the heterogeneity was taken either in sensing radius or in the energies of nodes. An idea to increase the coverage ratio as well as the lifetime of the senor network is suggested in this paper by introducing mobility in heterogeneous WSN, where the heterogeneity is considered in energy of nodes. We have chosen the deployment in heterogeneous wireless sensor network with loco-mobility capability nodes which has different energies. The simulation results show that in our algorithm, maximum area is covered, and in addition, some nodes are in off state to conserve the energy. We consider the nodes to cover large area while being reliable in sensing by saving energy. Our proposed algorithm's target is to schedule the sensor nodes in such a way that they can monitor a region efficiently. We compare our scheme with already existing protocol named as stable election protocol, analyzing the network lifetime for different number of nodes in various areas and also the coverage throughout the lifetime.

Effects of Lanthanoid Cations on the First Electronic Transition of Liquid Water Studied Using Attenuated Total Reflection Far-Ultraviolet Spectroscopy: Ligand Field Splitting of Lanthanoid Hydrates in Aqueous Solutions

The effects of the lanthanoid cations (Ln(3+)) on the first electronic transition (à ← X̃) of liquid water were studied from the attenuated total reflection far-ultraviolet (ATR-FUV) spectra of trivalent Ln(3+) electrolyte solutions (1 M), except Pm(3+). The à ← X̃ transition energies of the Ln(3+) electrolyte solutions show a distinct tetrad in their dependence on the number of 4f electrons of the Ln(3+) cations. For the half occupation period of the 4f electrons, the à ← X̃ transition energies decrease from La(3+) (4f(0), 8.0375 eV) to Nd(3+) (4f(3), 8.0277 eV) and increase from Sm(3+) (4f(5), 8.0279 eV) to Gd(3+) (4f(7), 8.0374 eV). For the complete occupation period, there are two local minima at Dy(3+) (4f(9), 8.0349 eV) and Yb(3+) (4f(13), 8.0355 eV). The à ← X̃ transition energies of the tetrad nodes (La(3+), Gd(3+), Ho(3+) (4f(10)), and Lu(3+) (4f(14))) increase slightly, as the nuclear charge increases in accordance with the hydration energies of the Ln(3+) cations. The energy difference (ΔE) between the à ← X̃ transition energies and the line between La(3+) and Lu(3+) is largest at Nd(3+) (80.5 cm(-1)) for the half occupation period and at Dy(3+) (26.1 cm(-1)) and Yb(3+) (24.5 cm(-1)) for the complete occupation period. The order of magnitude of ΔE is comparable to the ligand field splitting (LFS) of the ground state multiplets of Ln(3+) complexes. The observed tetrad trend of the à ← X̃ transition energies of the Ln(3+) electrolyte solutions across the 4f period reflects the hydration energies of the Ln(3+) cations and the LFS induced by water ligands.

Decay of correlations in a topological glass

In this paper we continue the study of a topological glassy system. The state space of the model is given by all triangulations of a sphere with N nodes, half of which are red and half are blue. Red nodes want to have five neighbors while blue ones want seven. Energies of nodes with other numbers of neighbors are supposed to be positive. The dynamics is that of flipping the diagonal between two adjacent triangles, with a temperature-dependent probability. We consider the system at very low temperatures. We concentrate on several new aspects of this model: Starting from a detailed description of the stationary state, we conclude that pairs of defects (nodes with the “wrong” degree) move with very high mobility along one-dimensional paths. As they wander around, they encounter single defects, which they then move “sideways” with a geometrically defined probability. This induces a diffusive motion of the single defects. If they meet, they annihilate, lowering the energy of the system. We both estimate the decay of energy to equilibrium, as well as the correlations. In particular, we find a decay like t −0.4.

Normalized wavelet packets quantifiers for condition monitoring

Normalized wavelet packets quantifiers are proposed and studied as a new tool for condition monitoring. The new quantifiers construct a complete quantitative time–frequency analysis: the Wavelet packets relative energy measures the normalized energy of the wavelet packets node; the Total wavelet packets entropy measures how the normalized energies of the wavelet packets nodes are distributed in the frequency domain; the Wavelet packets node entropy describes the uncertainty of the normalized coefficients of the wavelet packets node. Unlike the feature extraction methods directly using the amplitude of wavelet coefficients, the new quantifiers are derived from probability distributions and are more robust in diagnostic applications. By applying these quantifiers to Acoustic Emission signals from faulty bearings of rotating machines, our study shows that both localized defects and advanced contamination faults can be successfully detected and diagnosed if the appropriate quantifier is chosen. The Bayesian classifier is used to quantitatively analyse and evaluate the performance of the proposed quantifiers. We also show that reducing the Daubechies wavelet order or the length of the segment will deteriorate the performance of the quantifiers. A two-dimensional diagnostic scheme can also help to improve the diagnostic performance but the improvements are only significant when using lower wavelet orders.

A Topological Glass

We propose and study a model with glassy behavior. The state space of the model is given by all triangulations of a sphere with n nodes, half of which are red and half are blue. Red nodes want to have 5 neighbors while blue ones want 7. Energies of nodes with other numbers of neighbors are supposed to be positive. The dynamics is that of flipping the diagonal of two adjacent triangles, with a temperature dependent probability. We show that this system has an approach to a steady state which is exponentially slow, and show that the stationary state is unordered. We also study the local energy landscape and show that it has the hierarchical structure known from spin glasses. Finally, we show that the evolution can be described as that of a rarefied gas with spontaneous generation of particles and annihilating collisions.