Duo to limited energy of the sensor nodes which forming the wireless sensor network (WSN), and almost deployed in harsh environment, therefore it is very important to minimize the consumption of the sensor node’s energy. For this reasons designing an energy efficient clustering and scheduling of sensor nodes considered the most efficient methods for extending the WSN’s lifetime. In this paper, we have proposed Genetic algorithm based methods for clustering and scheduling. The proposed methods have two stages; in the first stage GA is used for cluster formation where the chromosome is represented by using the sensor node’s position. While in the second stage GA is used for selecting a minimum number of nodes while maintaining the full coverage and the connectivity of the selected nodes. The simulation result shows that the proposed algorithm (AGA) is more efficient than the existent algorithms in terms of number of first node die per round, number of a live nodes, and energy consumption.

Routing is a technique used for choosing the best network’s path and forwarding the data over the selected path. This paper investigates the enhanced routing algorithms for wire/wireless networks through making a deep study of the most new routing algorithms in those networks, then analyzing these algorithms to examine the efficiency and effectiveness of the analyzed algorithms. Moreover, the paper deals with OSPF for the wired network and AODV for the wireless network. The emphasis of this research paper is concentrated on the survey in routing algorithms that used in wired and wireless networks such as OSPF and AODV because such algorithms are the best suitable kinds for the two types of Networks. The next subsection describes the basic features of these protocols. This paper also focuses on the common points in wire/wireless routing algorithms and using machine learning techniques for enhancements and improvements.

In computer operating systems books, they explain and solve deadlock problems by declaring in advance the maximum needs of resources and their instances for each process, the total number of resources' instances, and the allocation of the resources' instances for each process. In this paper, we introduce an effective software tool to prove that it is not necessary to declare in advance the allocation of resources' instances for each process since we suggested and implement in the tool some equations to calculate and discover a suitable allocation of resources' instances to be distributed among competing processes in such a way that the computer system will never enter a deadlock state. In fact, the only necessary and sufficient conditions to solve deadlock problems are the total number of resources and their instances besides the maximum needs of resources and their instances for each process. The theory and details are explained with some examples in the contents.

The rapid evolution of wireless networking technologies opens the door to the evolution of the Wireless Sensor Networks (WSNs) and their applications in different fields. The WSN consists of small energy sensor nodes used in a harsh environment. The energy needed to communicate between the sensors networks can be identified as one of the major challenges. It is essential to avoid massive loss, or loss of packets, as well as rapid energy depletion and grid injustice, which lead to lower node efficiency and higher packet delivery delays. For this purpose, it was very important to track the usage of energy by nodes in order to improve general network efficiency by the use of intelligent methods to reduce the energy used to extend the life of the WSN and take successful routing decisions. For these reasons, designing an energy-efficient system that utilizes intelligent approaches is considered as the most powerful way to prolong the lifetime of the WSN. The proposed system is divided into four phases (sensor deployment phase, clustering phase, intra-cluster phase, and inter-cluster phase). Each of these phases uses a different intelligent algorithm with some enhancements. The performance of the proposed system was analyzed and evaluations were elaborated with well-known existing routing protocols. To assess the proficiency of the proposed system and evaluate the endurance of the network, efficiency parameters such as network lifetime, energy consumption, and packet delivery to the Sink (Base station) were exploited. The experimental outcomes justify that the proposed system surpasses the existing mechanisms by 50%.