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In wireless sensor networks (WSNs), clustering is one of the most effective routing protocols. Most clustering algorithms include two stages of operations: cluster head selection and cluster formation. Cluster heads are selected from the sensor nodes based on several key parameters like residual energy of the cluster heads candidates, the distance of cluster heads from their cluster members, and the distance between cluster head and the base station. Cluster formation deals with the association of sensor nodes with one of the selected cluster heads. This paper presents an energy-efficient clustering algorithm with linearly decreasing inertia weight particle swarm optimization (PSO) and improved weight factor. The interia weight PSO is based on cluster head selection and the improved weight factor-based cluster formation. The merit of the proposed approach is the robust formulation of a linear weight factor that leads to efficient cluster formation. The efficacy of the proposed algorithm is verified via different scenarios with varying numbers of nodes and different positions of base stations. Results are compared with some of the existing algorithms, and it is found that the proposed approach outperforms other approaches in terms of various evaluation parameters. [ABSTRACT FROM AUTHOR]

Jaya algorithm is one of the recent algorithms developed to solve optimization problems. The basic concept of this algorithm consists in moving the obtained solution, for a given problem, toward the best solution and avoiding the worst one. However, it severely suffers from premature convergence problem and therefore can be easily trapped in local optimums. This study aimed to alleviate these drawbacks and improve the performance of the original Jaya algorithm. Here, three new mutation strategies were implemented in the original Jaya to improve both its global and local search abilities. Chaotic maps were proved to be able to boost the search capabilities of meta-heuristic algorithms. Therefore, after demonstrating its chaotic behavior through the sensitivity to initial conditions, topological transitivity and the density of periodic points, we proposed a new 2D cross chaotic map. The chaotic sequences provided by the proposed chaotic map were embedded into the original Jaya algorithm to generate the initial population and control the search equations. It is worth mentioning that the modifications incorporated in the original algorithm did not affect its two essential characteristics, i.e., simplicity and nonrequirement of additional control parameters. As case studies, sixteen benchmark functions were used to evaluate the performance of the proposed chaotic Jaya algorithm (C-Jaya) regarding solution accuracy and convergence speed. Comparisons with some other meta-heuristic algorithms for low-, middle- and high-dimensional benchmark functions show that the proposed C-Jaya algorithm enhances the performance of original Jaya significantly. Moreover, it offers the fastest global convergence, the highest solution quality and it is the most robust on almost all the test functions among all the algorithms. Nonparametric statistical procedures, i.e., Friedman test, Friedman aligned ranks test and Quade test, conducted to analyze the obtained results, show the superiority of the proposed algorithm. [ABSTRACT FROM AUTHOR]

In this paper, two efficient cryptosystem schemes in the form of permutation-substitution based on chaotic systems are proposed. Firstly, a simple and efficient S-box method is introduced in order to use this S-box designed scheme in secure color image encryption technique. The major advantage of the proposed strategy is the dynamic aspect of keys used by chaotic map to generate strong S-boxes. Secondly, an efficient color encryption scheme based on chaotic maps and S-boxes in the form of permutation-substitution network is developed. Experimental results show the effectiveness of the proposed schemes. The suggested cryptosystems have superior performance and great potential for prominent prevalence in cryptographic applications compared to previous schemes. [ABSTRACT FROM AUTHOR]

In this paper, we propose to cryptanalyse an encryption algorithm which combines a DNA addition and a chaotic map to encrypt a gray scale image. Our contribution consists on, at first, demonstrating that the algorithm, as it is described, is non-invertible, which means that the receiver cannot decrypt the ciphered image even if he posses the secret key. Then, a chosen plaintext attack on the invertible encryption block is described, where, the attacker can illegally decrypt the ciphered image by a temporary access to the encryption machinery. [ABSTRACT FROM AUTHOR]

Recently a new image encryption method based on DNA encoding and chaotic systems has been proposed. In this paper, several weaknesses of this cryptosystem are pointed out. Equivalent mathematical model of the cryptosystem is designed and algebraic analysis is given. Moreover reduction of the key space has been reached by finding equivalent keys. A recovering scheme is finally given with a lower complexity than the actual decryption scheme. [ABSTRACT FROM AUTHOR]