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<p class="0abstract"><strong>—</strong>In the communication networks, guidance has become an important factor, with a significant impact on network performance, where the network orientation area has been and continues to be an ongoing development, intensive research for many years aimed at optimizing the network. This paper performs three modifications for a multipath routing protocol to solve the problem of routing in a DCell network simulation and apply online solutions on the network, the goal is to improve the transition efficiency of data. The modifications used to avoid data transmission failures which are delay problem<strong>, </strong>link failure problem, and power off (rack problem). The implementation of multipath routing protocol on the DCell network in actual simulation using the NS-3 program, which represents the rule that the DCell network was built and simulated. Finally, the modifications succeeded and return good results decreasing the delay time and solving the data transaction problems.</p>

Wireless Sensor Network (WSN) is a high potential technology used in many fields (agriculture, earth, environmental monitoring, resources union, health, security, military, and transport, IoT technology). The band width of each cluster head is specific, thus, the number of sensors connected to each cluster head is restricted to a maximum limit and exceeding it will weaken the connection service between each sensor and its corresponding cluster head. This will achieve the research objective which refers to reaching the state where the proposed system energy is stable and not consuming further more cost. The main challenge is how to distribute the cluster heads regularly on a specified area, that’s why a solution was supposed in this research implies finding the best distribution of the cluster heads using a genetic algorithm. Where using an optimization algorithm, keeping in mind the cluster heads positions restrictions, is an important scientific contribution in the research field of interest. The novel idea in this paper is the crossover of two-dimensional integer encoded individuals that replacing an opposite region in the parents to produce the children of new generation. The mutation occurs with probability of 0.001, it changes the type of 0.05 sensors found in handled individual. After producing more than 1000 generations, the achieved results showed lower value of fitness function with stable behavior. This indicates the correct path of computations and the accuracy of the obtained results. The genetic algorithm operated well and directed the process towards improving the genes to be the best possible at the last generation. The behavior of the objective function started to be regular gradually throughout the produced generations until reaching the best product in the last generation where it is shown that all the sensors are connected to the nearest cluster head. As a conclusion, the genetic algorithm developed the sensors’ distribution in the WSN model, which confirms the validity of applying of genetic algorithms and the accuracy of the results.

Recently developed low-power networked systems, wireless communications, and wireless sensors have all contributed to the rise of Wireless Sensor Networks (WSNs) as a potentially useful tool in the medical field. Securing Wireless Body Area Networks (WBANs) is essential for their widespread use in healthcare environments because the data they send frequently includes private and confidential patient health information. The study's goal is to create a system for detecting intrusions in WBAN. To best identify attacks in such systems, we present a novel “Attention-based Bi-directional Long Short-Term Memory with Graph Construction” (ABL-GC) here. The suggested approach ensures that the intrusion detection system uses only the features essential to detect a given attack, reducing the processing complexity.