International Journal of Wireless and Ad Hoc Communication

Trigonometric functions are essential part of digital communication systems such as receivers, synthesizers, and phase locked loop. Implementation of trigonometric functions requires many arithmetic units; multipliers and adders circuits which reduces the speed of operation and consumes much power. In this paper we introduce two approximation methods to represents sine, and cosine functions to achieve fast operation and low power consumption. The simulations indicate a matching between the ideal trigonometric functions and the approximation method with 0.001 error which considered as trivial amount.

In order to alleviate traffic congestion, traffic control systems are an important tool. These systems strive to boost the efficiency of road systems to optimize traffic flow on individual road segments. The benefits of real-time traffic control systems might be increased by integrating new telecommunication and autonomous car technology. There is six real-time traffic advancing sustainable development examined in this study: variable message signs and ramp meters, traffic diversion, and the integration of driverless vehicles into other traffic management systems, with four key criteria: economics, community and social, ecologic and traffic security, as well as 13 sub-criteria using MCDM. To do this, we offer unique additions to the WASPAS technique.

The use of alternative energy sources rather than fossil fuels will be unavoidable in the nearish term due to rising levels of toxic residues that threaten natural life and human health. Furthermore, the use of fossil fuels puts subsequent generations in danger from environmental damage and climate change. Battery electric vehicles (BEVs), an environmentally friendly kind of vehicle, are important in light of transportation's significant contribution to the carbon footprint. In light of the recent fast growth of the BEV industry, it has become more important to consider all available BEV options from the perspective of the end-user. Each BEV's fundamental characteristics may be examined in order to make this evaluation. For the correct BEV buying choice, MCDM strategies are useful. As a result, eleven battery-electric vehicles (BEVs) are considered in this study. A variety of multi-criteria methodologies are used to rate these cars on the basis of their technical specifications, such as acceleration, pricing, battery life, and range. It is then used entropy weight and TOPSIS approaches to gather findings from different MCDM strategies. The entropy method is used to compute the weights of the criteria. Then the TOPSIS is used to rank the options.  The 3 key considerations for BEV choosing are "price," "permitted load," and "energy usage," with Tesla Model S emphasized as the preferred route. 

Cloud computing provides various types of services to users. The goal of virtual machine placement (VMP) is to map the best physical machine to a virtual machine. With the help of Virtual Machine Placement, we can reduce cost, maximize resource utilization, reduced energy consumption of data centers in cloud environments. The focus of Virtual Machine Placement is to saving of power, quality of service. In this paper, we have reviewed various placements techniques used in cloud computing. At last, we have also studied various challenges for virtual machine placement in cloud computing. The main motive of various types of Virtual Machine Placement algorithms have to reduced energy consumption and minimize cost by maximizing utilization of various resources in the cloud platform. For further study, the researcher should focus on these challenges for the best virtual machine placement in a cloud environment. In this paper, we critically examine the techniques, challenges, and research gaps in virtual placements in cotext with Cloud Computing. Cloud computing, placement of virtual machines becomes major problems. For finding the solution to the problem we can use the various virtual machine placement algorithms. The main motive is to reduce consumption of energy, maximum resource utilization, minimizing cost factors used for virtual to the physical machine mapping in the cloud environment. For selecting the best algorithm various optimization methods are used. With these different optimization methods, we can analyze different algorithms. There is a great scope of improvement in existing systems of virtual placements to make them more energy-efficient, more reliable, and fault-tolerant. Redundancy in cloud downloading can be made more intelligent and minimized for duplicate data while downloading and uploading.