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Abstract-Cloud computing is the latest answer of technology to meet the computational requirements of users. The notable point in complicated computational works is energy consumption. The integration is one of the elements in the cloud system which can reduce the energy consumption and coordinate the software products. In this article, some solutions have been considered for determining the upper bound threshold of utilization for doing migration in order to reduce the power consumption. Also, it has been tried to use a solution to diagnose the overloaded host and eliminate it from the host as it can amend the efficiency as well as improve the host performance. All these will eventually reduce the power consumption. The results of evaluation show that the presented model has better efficiency in reducing the power consumption as well as decreasing the number of the migrations in comparison with the other models.Index Terms-Cloud computing, overloaded host, power consumption, migration. I. INTRODUCTIONmodel, similar to any other technology, has been created according to its own specific advantages while it involves some disadvantages. One of cloud computing disadvantages is producing a huge amount of CO2 due to the presence of very large data centers and high power consumption. The studies [2] regarding power consumption of server farms in 2005 show that the electric consumption by the wide world of servers (including cooling servers and their equipment) cost US $ 7.2. This study also shows that electricity consumption in that year, compared with consumption in 2000, has been doubled. However, the technology improvements have presented suitable hardware [3] including low-power processors, solid state drives and energy efficient monitors. A series of software solutions are optimally improving the energy efficiency. These two guidelines (hardware and software) should be evaluated as competitive supplements in order to incredibly increase their effects on the amount of energy consumption. The software solutions alongside software methods can improve the cloud computing Manuscript received September 12, 2014; revised November 17, 2014. Mona Arjmandi, Nik Mohammad Balouchzahi, Mahmood Fathy, and Ahmad Akbari are with the Iran University of Science and Technology, Tehran, Balouchzahi@iust.ac.ir, mahfathy@iust.ac.ir, Akbarii@iust.ac.ir).Kaamran Raahemifar is with the Ryerson University, Toronto, Canada (e-mail: Kraahemi@ee.rayerson.ca).efficiencies from the power consumption point of view. In this article one of the software factors, integration of virtual machines, will be evaluated. This factor reduces the server's power consumption. In this solution the low-load and overload servers will be diagnosed through a proper method and after migration of virtual machines, the low-load servers will be turned off. Moreover, those groups of the virtual machines which belong to the overload servers that ought to migrate are determined via the selective policy of the virtual machines. In the next step the selected machines wil...

In this paper, four PSO based distributed algorithms are presented to attain k-coverage in the target filed. In the first algorithm named K-Coverage Particle Swarm Optimization (KPSO), each static sensor which discovers an event in its sensing range, implements Particle Swarm Optimization (PSO) algorithm in a distributed manner on its mobile sensors. The calculation time is considered as a big bottleneck in PSO, so a second algorithm named K-Coverage Virtual Force directed Particle Swarm Optimization (KVFPSO) is presented, comprised of Virtual Force and KPSO algorithms. In the first and second proposed algorithms, the best experiences of the particles were used to determine their speed. It is possible that these responses might not be the final result and cause extra movements. Another algorithm named KVFPSO-Learning Automata (KVFPSO-LA) is introduced based on which the speed of particles is corrected by using the existing knowledge and the feedback from the actual implementation of the algorithm. To improve performance of the algorithm, Improved KVFPSO-LA is introduced, in which static sensors are equipped with learning automata. Simulation results show that the proposed protocols perform well with respect to balanced energy consumption among nodes, thus maximizing network life-time

Near Field Communication (NFC) is a new technology which can provide communication between mobile devices in short range. Data would be communicate in three modes: (1) between two mobile systems (MS), (2) MS2 NFC tags (3) reader2MS. One of the must public application in this technology is micropayment system, so by developing NFC technology it would be used in E-commerce and e-everything. In combination of E-Commerce and NFC technology MS would be used as smart card. It is clear that by developing one technology we should consider security and protection system for that. Therefore NFC security and protecting MS from attacks and eavesdropping is so important and critical. In this article at the first we will briefly review about this technology and the architecture, in the next step we will explain about NFC threats therefore we can analyze the attack. After that we will describe some scenarios for protecting against the NFC threats. Then we will explain NFC security standards. In this part we will mention to SSH and SCH, we will show that in secure channel we should use a symmetric algorithm. In this standard AES is has been recommended but we will show that two fish algorithm is more complex than in AES on the other hand we will simulate our proposed approach and we will show that the power consumption and processing time are decreased.

Coronavirus is spreading an outbreak in the world and the medical staffs have been coming under further strain with increasing in patients referring to the hospital. Real-time health monitoring systems play a critical role in prevention, control the pandemic disease, and enhance the entire health care service delivery in real-time, and influence on visiting the hospital visiting the hospital. In this paper, a hierarchical architecture for the Internet of Things is improved using resource and task management techniques for reducing emergency response time and enhanced the patients’ quality of experiences considering energy consumption, network delay, cost of execution in the cloud and network usage. In this proposed scenario, the task is divided into subtasks and processes depending on their functions with different execution times. This method also has led to improving the fog architecture. This proposed method is modeled are evaluated in terms of the specified parameters, using the iFogsim toolkit. The results showed an improvement of 80 percent in their parameters such as cost of execution, total network usage, and average delays, compared to the cloud and other common architecture.

Mac protocol plays an important role in spectrum opportunities

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