نشریه مهندسی برق
سال پنجاه و سوم شماره 4 (پیاپی 106، زمستان 1402)

Fog computing is a new paradigm which enables offloading IOT data (tasks) to the network devices. The aim of this approach is reducing the response time for delay-sensitive applications and improving the quality of service for users. This paper presents a task offloading scheme with taking advantages of the Software-Defind Networks. In this research a mixed integer linear programming (MILP) optimization model is presented with the aim of minimizing delay and mobility cost of things, which considers local computing, fog nodes participation, applications distribution and resource limitations. Whereas the presented mathematical model is Np-hard, a meta-heuristic algorithm based on the ant colony optimization is proposed by considering constraints of the mathematical model. The results obtained from evaluation of the proposed method is compared with the optimal value obtained from the mathematical model, random method and a heuristic algorithm presented in related works. The results of evaluation show that the delay and the total offloading cost in the proposed method are 22% and 28.75% higher than the optimal values, respectively. Also, the proposed method is capable to reduce the delay by 20% and reduce the migration cost of computing results by 40% compared to the heuristic method in state-of-the-art.

In this paper, a new method based on model predictive control with a finite control set is proposed for the cascaded H-bridge converter-based active rectifier to control the converter under switch fault conditions. The purpose of the fault-tolerant method is to guarantee the continuous operation of the converter after switch(es) open-circuit failure. After the occurrence of an open circuit fault in the switches, by using the system model, the presented model predictive approach enables the operation of the converter despite the presence of a faulty cell. The proposed method sets the dc voltages of dc-link capacitors at the reference value under balanced and unbalanced dc loads and keeps the current drawn from the grid at a good quality. The performance of the proposed method has been evaluated through simulations based on the seven-level cascaded H-bridge converter in the MATLAB/SIMULINK environment.

In this study, the mantle cloaking method is utilized to eliminate strong mutual coupling between two compact co-frequency patch antenna arrays with orthogonal polarizations. The patches are reduced in size by 33% through the addition of two slots on the resonant edges, allowing a reduction in distance between elements and enabling beam steering. To mitigate the destructive effects of mutual coupling between elements, a thin metasurface cloak is placed on the top and bottom surfaces of the patches. The metasurface cloak exhibits capacitive reactance at the desired operating frequency and eliminates the inductive reactance caused by induced currents from adjacent patches, making the elements of the two arrays invisible to each other. Full-wave simulation is used to evaluate the performance of this cloak structure in terms of array radiation characteristics. Results show that adding the cloak increased array efficiency by 35% compared to the uncloaked case, with isolation between elements improving by over 24 dB at the operating frequency. Radiation patterns in the cloaked case demonstrate a 98.5% similarity to those of isolated arrays. The antenna gains in the cloaked case slightly decreased by 0.1 dB and 0.2 dB for arrays I and II, respectively, and the sidelobe levels increased by 0.5 dB and 0.2 dB compared to isolated arrays. These findings confirm that this metasurface cloak design successfully restores radiation characteristics of tightly coupled arrays similar to those of isolated arrays.

Directional sensor networks (DSNs) consist of directional sensor nodes which can switch to several directions to extend their sensing ability to cover the interested area. One important problem in these networks is providing adequate coverage to fulfill the issued sensing tasks. This paper addresses the problem of selection and orientation of directional sensors for providing full area coverage in directional sensor networks. Using the notion of homology in Algebraic topology, we model the coverage of DSNs by simplicial complexes and formulate the problem of selection and orientation of directional sensors as a binary linear programming. Then, an algorithm based on irregular cellular learning automata for orientation of sensors is proposed to solve the problem in a reasonable time. The proposed algorithm works based on the size of the existing holes in the covered area. The proposed algorithm has adopted a homological approach to find holes in the sensor network. The simulation results show about 2% increase in the amount of coverage and also a significant decrease in the number of conditions and variables of the proposed optimization problem.

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.

A challenging aspect of video error concealment (VEC) is reducing blockiness around the missing region. In this paper, we have devised a novel method for calculating the boundary matching distortion based on the edge direction surrounding the lost area to deal with this problem. After detecting the corresponding slice’s erroneous Macroblock (MB), it is divided into four 8×8 pixels sub-blocks. Then, the gradient of outer boundary pixels is derived and determines each side’s smoothness, which is further used for drawing the hypothetical line. Furthermore, this paper proposes a novel optimization-based model that can accurately measure boundary matching error for loss recovery. We observe better results for our proposed technique than other related VEC algorithms in terms of PSNR and SSIM. The proposed algorithm improves the average PSNR by 1.09 dB and increases the average SSIM by 0.0135 at the packet loss rate of 10%. In addition, for a PLR of 20%, the PSNR is increased by 1.28 dB, and the SSIM enhancement is 0.019. This algorithm is slightly more computationally complex than the compared methods, but it is still acceptable. Thus, by adding a few computations to the video decoder, the proposed method maintains the quality of the video, especially in the rough, damaged regions of a decoded frame.

In recent years, due to the interconnectedness and stress on power distribution and natural gas networks, enhancing the level of resilience against severe natural events such as storms has become crucial and vital. The presence of energy storage systems in microgrids has transformed them into reliable resilience sources in electric energy distribution systems. In this regard, studying the improvement of resilience in distribution networks in the presence of microgrids holds special importance. The objective of this article is to achieve the maximum utilization of available network storage to supply critical and non-critical electrical loads while minimizing the loss of load prior to the occurrence of severe events. To this end, a multi-objective optimization algorithm, namely Ant Colony Optimization, has been employed for proactive scheduling and achieving optimal decisions within consecutive time periods. Simulation results demonstrate that increasing the number of microgrids and expanding energy storage systems in the network not only improves network loadability but also reduces the amount of lost load by 15.27%, thereby increasing the level of resilience.