Multilevel heterogeneous network model for wireless sensor networks

The lifetime of a network can be increased by increasing the network energy. The network energy can be increased either increasing the number of sensors or increasing the initial energy of some sensors without increasing their numbers. Increasing network energy by deploying extra sensors is about ten times costlier than that using some sensors of high energy. Increasing the initial energy of some sensors leads to heterogeneous nodes in the network. In this paper, we propose a multilevel heterogeneous network model that is characterized by two types of parameters: primary parameter and secondary parameters. The primary parameter decides the level of heterogeneity by assuming the values of secondary parameters. This model can describe a network up to nth level of heterogeneity (n is a finite number). We evaluate the network performance by applying the HEED, a clustering protocol, on this model, naming it as MLHEED (Multi Level HEED) protocol. For n level of heterogeneity, this protocol is denoted by MLHEED-n. The numbers of nodes of each type in any level of heterogeneity are determined by the secondary model parameter. The MLHEED protocol (for all level heterogeneity) considers two variables, i.e., residual energy and node density, for deciding the cluster heads. We also consider fuzzy implementation of the MLHEED in which four variables are used to decide the cluster heads: residual energy, node density, average energy, and distance between base station and the sensor nodes. In this work, we illustrate the network model up to seven levels (\(1\le n\le 7\)). Experimentally, as the level of heterogeneity increases, the rate of energy dissipation decreases and hence the nodes stay alive for longer time. The MLHEED-m, \(m=2,3,4,5,6,7\), increase the network lifetime by \(73.05, 143.40, 213.17, 267.90, 348.60, 419.10\,\%\), respectively, by increasing the network energy as \(40, 57, 68.5, 78, 84, 92.5\,\%\) with respect to the original HEED protocol. In case of fuzzy implementation, the MLHEEDFL-m, \(m=2,3,4,5,6,7,\) increases the network lifetime by \(282.7, 378.5, 435.78, 498.50, 582.63, 629.79\,\%\), respectively, corresponding to the same increase in the network energy as that of the MLHEED (all levels) with respect to the original HEED. The fuzzy implementation of the HEED, MLHEEDFL-1, increases the network lifetime by \(176.6\,\%\) with respect to the original HEED with no increase in the network energy.     

Heterogeneous HEED Protocol for Wireless Sensor Networks

One of the important protocols for increasing the network lifetime in wireless sensor networks (WSNs) is hybrid energy efficient distributed (HEED) protocol. This protocol considers two parameters for deciding the cluster heads, i.e., residual energy and node density and has been designed for the homogeneous WSNs. In this paper, we consider the implementation of HEED for a heterogeneous network. Depending upon the type of nodes, it defines one-level, two-level, and three-level heterogeneity and accordingly the implementation of HEED is referred to as hetHEED-1, hetHEED-2, and hetHEED-3, respectively. We also consider one more parameter, i.e., distance and apply fuzzy logic to determine the cluster heads and accordingly the hetHEED-1, hetHEED-2, and hetHEED-3 are named as HEED-FL, hetHEED-FL-2, hetHEED-FL-3, respectively. The simulation results show that as the level of heterogeneity increases in the network, the nodes remain alive for longer time and the rate of energy dissipation decreases. And also, increasing the heterogeneity level helps sending more packets to the base station and increases the network lifetime. The increase in the network energy increases the network lifetime manifold. In fact, using fuzzy logic, the network lifetime increases by 114.85 % that of the original HEED without any increase in the network energy. Thus, the hetHEED-FL-3 provides the longest lifetime (387.94 % increase) in lifetime at the cost of 19 % increase in network energy), sends maximum number of packets to the base station, and has minimum rate of energy dissipation.     

PVO based reversible data hiding technique for roughly textured images

Multidimensional Systems and Signal Processing - Recently, several reversible data hiding (RDH) techniques based on pixel value ordering (PVO) have been proposed that precisely embed the secret...     

Evaluating Authentication Schemes for Real-Time Data in Wireless Sensor Network

There have been discussed many user authentication schemes for wireless sensor networks. This paper intends to review the existing authentication techniques for their pros and cons. The techniques are primarily classified on the basis of factors used therein that include one-factor, two-factor, and three-factor schemes. Twelve architecture models on which various authentication schemes are based. The pros and cons of models are also discussed. The security and functionality feature is also used as criteria for evaluation metrics. In this paper, we have also considered various one-factor, two-factor and three-factor authentication scheme. The communication, computation cost, security feature and the security tool are the most important criteria for comparing the authentication techniques. This whole analysis can be used by other researchers to design their own authentication schemes considering the stated criteria.

     

Low bandwidth data hiding for multimedia systems based on bit redundancy

Multimedia Tools and Applications - In recent years, low bandwidth data hiding schemes for multimedia systems are being seen as a promising new technology for multimedia information protection and...     

Energy efficient rendezvous points based routing technique using multiple mobile sink in heterogeneous wireless sensor networks

Wireless Networks - In recent decades, Sensor nodes (SNs) are used in numerous uses of heterogeneous wireless sensor networks (HWSNs) to obtain a variety of sensing data sources. Sink mobility...     

An Improved Histogram-Shifting-Imitated reversible data hiding based on HVS characteristics

In this paper, we propose a reversible data hiding scheme to hide a secret message into a cover image by considering the characteristics of Human Visual System (HVS) in order to improve the visual imperceptibility. The human eyes are more sensitive to the changes in the low intensity pixels than the higher intensity ones. Therefore, we divide the intensity levels (0–255) into four groups: the first group contains 0–79 intensity level; second, third, and fourth group contain, respectively, 80–151, 152–215, and 216–255 intensity levels. We further divide first group into segments of size 2 elements, second, third, and fourth group into 3, 4, and 5 elements sized segments, respectively. After constructing the segments, we scan the image in raster order to identify the peak points for each segment, which are used to embed the secret data. The secret data is also divided into the four segments according to the identified peak points per group. The first segment data is converted into base2 representation, second, third and fourth segment secret data into 3, 4, and 5 base representation, respectively. The first segment of secret data is embedded into the peak points belonging to first group, second, third and fourth group secret data is embedded into the peak points of second, third and fourth group, respectively. Thus, our scheme makes least changes into the pixels belonging to the first group which have least intensity values and most to the fourth group pixels which have highest intensity values. Experimentally, our scheme provides better quality stego image and hides more secret data than the other state of the art schemes. We also build a location map for all the peak points to ensure the reversibility of the proposed scheme.     

An optimal high capacity reversible data hiding scheme using move to front coding for LZW codes

Reversible Data hiding techniques reduce transmission cost as secret data is embedded into a cover image without increasing its size in such a way that at the receiving end, both secret data and the cover image can be extracted and recovered, respectively, to their original form. To further reduce the transmission cost, the secret data can be embedded in the compression codes by some popular reversible data hiding schemes. One of the popular and important reversible data hiding method is high- performance data-hiding Lempel–Ziv–Welch (HPDH-LZW) scheme which hides the secret data in LZW codes. In this paper, the HPDH-LZW scheme is modified in order to increase its hiding capacity and compression ratio. First, the proposed work modifies the Move to Front (MTF) encoding technique to hide the secret data and also to increase the similarity among the element of the cover media. Then, LZW encoding technique is applied on the resultant cover data to obtain LZW codes, which are used to hide further secret data. Experimental results show that the proposed scheme has significantly increased the data hiding capacity and have good embedding and extraction speed in comparison to other state of the art schemes.

     

Energy-optimized cluster head selection based on enhanced remora optimization algorithm in underwater wireless sensor network

With the technological advancements, wireless sensor network (WSN) has played an impeccable role in monitoring the underwater applications. Underwater WSN (UWSN) is supported by WSN but subjected to data dissemination in an acoustic medium. Due to challenging conditions in underwater scenario, the limited battery resources of these sensor nodes stem to a crucial research problem that needs to address the energy-efficient routing in UWSN. In this research work, we intend to propose an energy-optimized cluster head (CH) selection based on enhanced remora optimization algorithm (ECERO) in UWSN. Since CH devours the maximum energy among the nodes, we perform selection of CH based on EROA while considering energy, Euclidean distance from sink, node density, network's average energy, acoustic path loss model and lastly, the adaptive quantity of CHs in the network. Further, to reduce the load on CH node, we introduce the concept of sleep scheduling among the closely located cluster nodes. The proposed work improves the performance of recently proposed EOCSR algorithm by great magnitude which claims to mitigate hot-spot problem, but EOCSR still suffers from the same due to relaying a large magnitude of data.