Wireless sensor networks consisting of tens or hundreds of sensors that are based on intended use in a distributed environment and their main purpose is to record information. In numerous applications, sharing information in short period of time is gravely important. Also, sharning information would spend most of system’ s energy and considering the limitaions of energy resource in system, controlling the energy usage in network is a challenge. So, the most important problems in wireless sensor network are energy consumption and latency on the network. To optimize energy consumption and transmission Delay, separately and hand-to-hand, meta-heuristic algorithms in wireless sensor network can be used. Based on results, hand-to-hand optimization of these two parameters can increase longevity and performance of the network. The results show that by repeating optimization algorithm, suggested Metaheuristic algorithm’ s results are more similar to results of Shortest path algorithm, in comare to results of Particle Swarm optimization (PSO) algorithm.

In this paper, recommended spiral passive micromixer was designed and simulated. spiral design has the potential to create and strengthen the centrifugal force and the secondary flow. A series of simulations were carried out to evaluate the effects of channel width, channel depth, the gap between loops, and flowrate on the micromixer performance. These features impact the contact area of the two fluids and ultimately lead to an increment in the quality of the mixture. In this study, for the flow rate of 25 μl/min and molecular diffusion coefficient of 1×10-10 m2/s, mixing efficiency of more than 90% is achieved after 30 (approximately one-third of the total channel length). Finally, the optimized design fabricated using proposed 3D printing method.

Application of the network equivalent concept for external system representation for power system transient analysis is well known. However, the challenge to utilize an equivalent network, approximated by a rational function, is to guarantee the passivity of the corresponding model. In this regard, special techniques are required to enforce the passivity of the equivalent model through a post processing approach that minimizes its impact on the original model characteristics. In this paper, the passivity is enforced by expressing the problem in terms of a convex optimization problem that guarantees the global optimal solution. The convex optimization problem is efficiently solved by recently developed numerical interior–point methods. This passivity enforcement is also global which indicates that the passivity enforcement in one region does not lead to passivity violation in other regions.

Given the importance of reducing data latency in discrete wireless networks in critical situations, we present the combined routing protocol with a storage and forwarding approach in Throw-Box-based network topology concerning aspects such as proper relay prediction and effective buffer management. To reduce the data transfer time in the relay node selection criteria, we consider the effect of different factors: node records, end-to-end latency, the nodes' available buffer space, and information such as average speed and node movement direction. We also use artificial intelligence to perform optimal routing using the Simulated Annealing algorithm. Important common performance criteria such as average latency, delivery ratio, number of lost messages, and network overhead were used to evaluate the performance of the proposed model. The results showed that our proposed routing method has less reception Delay than other routing methods and maintains maximum transmission.

Trust establishment is one of the significant resources to enhance the scalability and reliability of resources on cloud environments. To establish a novel trust model on SaaS (Software as a Service) cloud resources and to optimize the resource utilization of multiple user requests, an integrated software trust estimator with multi-user resource competence (IST-MRC) optimization mechanism is proposed in this paper. IST-MRC optimization mechanism combines its trustworthy properties with optimal resource allocation, on the requisition of the software apps, without any traffic occurrence in the cloud environment. Initially, a behavior trust estimator is developed in the IST-MRC mechanism to measure the trust value of the software service zone. The trust value is estimated, based on Software Availability Rate, Hit Rate, and User Feedback regarding the specific software apps. Next, the resources are optimized to multiple users using competence optimization. The competence optimization in the IST-MRC mechanism computes the processor speed, bandwidth, and latency to handle the varied traffic conditions on multiple user requests. Experiments are conducted to measure and evaluate factors, such as Successful Request Handles, Resource Utilization Efficiency, Latency Time, and Trust Success Ratio on the multiple users.

There is a growing interest in the optimal design of the phase locked loops, because these circuits are widely used in communication and electronic circuits. Undoubtedly the most important objectives in designing PLLs (phase locked loops) are low power consumption and low Delay. In this paper, the process of designing and the optimization of PFD (one of the main part in PLLs) are proposed by using particle swarm optimization (PSO) algorithm. In the proposed method, instead of carrying out the frequent experiments and simulations based on trial and error to achieve the desired parameters of the phase frequency detector, effective variables are sent to the PSO algorithm and optimization process is done by this algorithm. The results show a remarkable ability of this heuristic method to find transistors sizing for optimal power consumption and Delay.