During the past decades, in the era of wireless communications and embedded system, the concept of the Internet of Things (IoT) was first presented by Kevin Ashton in the year 1999 [1]. Along with the tremendous growth in the number of sensing devices connected to the Internet, we were a witness of emerging IoT into healthcare, transportation system, smart cities, agriculture, and other enterprises. The IoT benefits cooperation of diverse computing systems such as sensors and smart devices to cloud computers. On the other side, the internet and mobile communication facilitate the spatiotemporal connection between distant people with common experience and values. More recently, technological evolution is introduced by intelligent sensor devices installed in the physical and virtual realm of IoT to act as or on behalf of human beings: the virtual robots [2]. This creates the possibility for physical objects present in a self-organized manner without a central administration and leads to meaningful human-machine interaction in IoT scenario [3].
<p class="MsoNormal" style="text-align: left; margin: 0cm 0cm 0pt; layout-grid-mode: char;" align="left"><span class="text"><span style="font-family: ";Arial";,";sans-serif";; font-size: 9pt;">In this paper a new low power and high performance adder cell using a new design style called “Bridge” is proposed. The bridge design style enjoys a high degree of regularity, higher density than conventional CMOS design style as well as lower power consumption, by using some transistors, named bridge transistors. Simulation results illustrate the superiority of the resulting proposed adder against conventional CMOS 1-bit full-adder in terms of power, delay and PDP. We have performed simulations using HSPICE in a 90 nanometer (nm) standard CMOS technology at room temperature; with supply voltage variation from 0.65v to 1.5v with 0.05v steps.</span></span><span style="font-family: ";Arial";,";sans-serif";; font-size: 9pt;"></span></p>
This paper presents an iterative mathematical decision model for organizations to evaluate whether to invest in establishing information technology (IT) infrastructure on-premises or outsourcing IT services on a multicloud environment. This is because a single cloud cannot cover all types of users' functional/nonfunctional requirements, in addition to several drawbacks such as resource limitation, vendor lock-in, and prone to failure. On the other hand, multicloud brings several merits such as vendor lock-in avoidance, system fault tolerance, cost reduction, and better quality of service. The biggest challenge is in selecting an optimal web service composition in the ever increasing multicloud market in which each provider has its own pricing schemes and delivers variation in the service security level. In this regard, we embed a module in the cloud broker to log service downtime and different attacks to measure the security risk. If security tenets, namely, security service level agreement, such as availability, integrity, and confidentiality for mission-critical applications, are targeted by cybersecurity attacks, it causes disruption in business continuity, leading to financial losses or even business failure. To address this issue, our decision model extends the cost model by using the cost present value concept and the risk model by using the advanced mean failure cost concept, which are derived from the embedded module to quantify cloud competencies. Then, the cloud economic problem is transformed into a bioptimization problem, which minimizes cost and security risks simultaneously. To deal with the combinatorial problem, we extended a genetic algorithm to find a Pareto set of optimal solutions. To reach a concrete result and to illustrate the effectiveness of the decision model, we conducted different scenarios and a small-to-medium business IT development for a 5-year investment as a case study. The result of different implementation shows that multicloud is a promising and reliable solution against IT on-premises deployment.
IoT describes a new world of billions of objects that intelligently communicate and interact with each other. One of the important areas in this field is a new paradigm-Social Internet of Things (SIoT), a new concept of combining social networks with IoT. SIoT is an imitation of social networks between humans and objects. Objects like humans are considered intelligent and social. They create their social network to achieve their common goals, such as improving functionality, performance, and efficiency and satisfying their required services. Our article’s primary purpose is to present a comprehensive review article from the SIoT system to analyze and evaluate the recent works done in this area. Therefore, our study concentrated on the main components of the SIoT (Architecture, Relation Management, Trust Management, web services, and information), features, parameters, and challenges. To gather enough information for better analysis, we have reviewed the articles published between 2011 and December 2019. The strengths and weaknesses of each article are examined, and effective evaluation parameters, approaches, and the most used simulation tools in this field are discussed. For this purpose, we provide a scientific taxonomy for the final SIoT structure based on the academic contributions we have studied. Ultimately we observed that the evaluation parameters are different in each element of the SIoT ecosystem, for example for Relation Management, scalability 29% and navigability 22% are the most concentrated metrics, in Trust Management, accuracy 25%, and resiliency 25% is more important, in the web service process, time 23% and scalability 16% are the most mentioned and finally in information processing, throughput and time 25% are the most investigated factor. Also, Java-based tools like Eclipse has the most percentage in simulation tools in reviewed literature with 28%, and SWIM has 13% of usage for simulation.
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