In this paper, elliptic curves Diffie Hellman-Rivest Shamir Adleman algorithm (ECDH-RSA) is a novel encryption method was proposed, which based on ECDH and RSA algorithm to secure transmitted data in heterogeneous wireless sensor networks (HWSNs). The proposed encryption is built under cheesboard clustering routing method (CCRM). The CCRM used to regulate energy consumption of the nodes. To achieve good scalability and performance by using limited powerful max-end sensors besides a large powerful of min-end sensors. ECDH is used for the sharing of public and private keys because of its ability to provide small key size high protection. The proposed authentication key is generated by merging it with the reference number of the node, and distance to its cluster head (CH). Decreasing the energy intake of CHs, RSA encryption allows CH to compile the tha data which encrypted with no need to decrypt it. The results of the simulation show that the approach could maximize the life of the network by nearly (47%, and 35.7%) compare by secure low-energy adaptive clustering hierarchy (Sec-LEACH and SL-LEACH) approches respectively.

In this work, we have used fuzzy homotopy analysis method to find the fuzzy series solution (fuzzy semi-analytical solution) of the first order fuzzy Riccati differential equation. The fuzzy approximate-analytical solutions that we obtained during this paper are accurate solutions and very close to the fuzzy exact-analytical solutions. Some numerical results are given to illustrate the method. The obtained numerical results are compared with the exact solutions.

<span style="font-family: Arial, sans-serif; font-size: 9pt;">In this paper, we propose a new clustering method called fuzzy stable election protocol (FSEP), which is capable to overcome the bottleneck problem and addressing the uneven energy consumption problem in heterogeneous WSNs. We also propose an energy-efficient routing method called particle swarm optimization routing method (PSORM) to find the optimal routing path for the heterogeneous WSNs. PSORM seeks to investigate the problems of balancing energy consumption and maximization of network lifetime. To demonstrate the effectiveness of FSEP-PSORM in terms of lessening end-to-end delay, balancing energy consumption, and maximization of heterogeneous network lifetime, we compare our method with three approaches namely, chessboard clustering approach, PEGASIS, and LEACH. Simulation results show that the network lifetime achieved by FSEP-PSORM could be increased by nearly 38%, 45%, and 60% more than that obtained by PEGASIS, LEACH and stable election protocol clustering (SEP), respectively.</span>

Abstract

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