Cloud computing is a type of parallel, configurable, and flexible system, which refers to the provision of applications on virtual data centers. However, reducing the energy consumption and also maintaining high computation capacity have become timely and important challenges. The concept of replication is used to face these challenges. By increasing the number of data replicas, the energy consumption, the performance, and also the cost of creating and maintaining new replicas also are increased. Deciding on the number of required replicas and their location on the cloud system is an NP-hard problem. In this paper, the problem is formulated as an optimization problem and a hybrid metaheuristic algorithm is offered to solve it. The algorithm uses the global search capability of the Particle Swarm Optimization (PSO) algorithm and the local search capability of the Tabu Search (TS) to get high-quality solutions. The efficiency of the method is shown by comparing it with simple PSO, TS, and Ant Colony Optimization (ACO) algorithm on different test cases. The obtained results indicate that the method outperforms all of them in terms of consumed energy and cost. KEYWORDS cloud computing, data replication, particle swarm optimization, replica INTRODUCTIONCloud computing is a deep revolution in providing the information technology-based services based on virtualization technology. 1-4 It considers the ideas of distributed and parallel computing to offer on-demand computing resources for computers or other devices. 5-9 It aims to offer shared services with high reliability, dynamicity, and scalability; although, it is facing many issues because of its complex architecture. [10][11][12] In the cloud data centers, scalability and complexity issues cause cost and energy become two key challenges that need attention and careful study. 13,14 As the carbon footprint and consumed energy of the cloud infrastructures have been increased, investigators tried to find applicable methods for decreasing energy consumption. 15 In the last few years, the main focus of investigators and engineers was on improving the performance in terms of energy, space, and cost. 1

Distraction is one of the main causes of traffic crashes. The effect of cell phones, a major contributor to cognitive distraction, on response time has tested in many simulator studies. Response time is not the only driving skill affected by cell phone conversations, however. Specifically, it is known that cell phone usage contributes to a reduction in hazard anticipation skills at intersections, and there are many other scenarios where cell phone conversations could have a detrimental effect. The objective of this study is to determine whether cognitive distractions associated with cell phone use affect hazard anticipation, not only at intersections but also in other scenarios which contain latent hazards. Twenty-four drivers navigated 18 scenarios on a driving simulator twice, with their eye movements continuously monitored. During one drive, participants performed a hands-free mock cell phone task while driving; on the other drive, they navigated through the virtual world without any additional tasks apart from the primary task of driving. The scenarios were classified into two types: intersection and non-intersection. Using a logistic regression model within the framework of generalized estimation equations, it was determined that the proportion of anticipatory glances toward potential hazards was reduced significantly for all scenarios when drivers were engaged in a mock cell phone task. Perhaps the most disturbing finding is that this was true both at work zones and at marked midblock crosswalks, scenarios which often endanger vulnerable road users. In summary, the study found a negative effect of cognitive distraction on latent hazard anticipation.

Overall, the rate of vehicle-bicycle collisions is continually increasing. In the United States alone, bicyclist fatalities contributed to 2.3 percent of all crash related fatalities in 2015. In most of these cases, crashes occur due to distracted drivers who are unable to correctly anticipate the bicyclists at the hazardous locations on the roadways such as, intersections and curves. The objective of the current study is to contribute to the divisive literature surrounding cell phone use while driving by specifically measuring, the effects of a secondary mock cell phone task on hazard anticipation performance across common vehicle-bicycle conflict situations. Two groups of 20 drivers each, navigated seven unique scenarios on a driving simulator while being monitored by an eye tracker. One group of participants performed a hands free mock cellphone task while driving, while the second group drove without any additional tasks outside of the primary task of driving. Analysis of the proportion of anticipatory glances using a logistic regression model revealed a significant main effect of the mock cellphone task at reducing the proportion of such glances made by the drivers towards potential bicyclist threats on the roadway.

The objective of the current study is to evaluate the use of virtual reality (VR) headsets to measure driving performance. This is desirable because they are several orders of magnitude less expensive than simulators and, if validated, could greatly extend the powers of simulation. Out of several possible measures of performance that could be considered for evaluating VR headsets, the current study specifically examines drivers’ latent hazard anticipation behavior both because it has been linked to crashes and because it has been shown to be significantly poorer in young drivers compared with their experienced counterparts in traditional driving simulators and in open road studies. In a between-subject design, 48 participants were equally and randomly assigned to one of four experimental conditions—two young driver cohorts (18–21 years) and two middle-aged driver cohorts (30–55 years) navigating either a fixed-based driving simulator or a VR headset-based simulator. All participants navigated six unique scenarios while their eyes were continually tracked. The proportion of latent hazards anticipated by participants which constituted the primary dependent measure, was found to be greater for middle-aged drivers than young drivers across both platforms. The difference in the magnitude of performance between the young and middle-aged drivers was similar across the two platforms. The study provides some justification for the use of VR headsets as a way of understanding drivers’ hazard anticipation behavior.

Vehicle–bicycle collisions are increasing alarmingly. A recent study shows that cognitively distracted drivers who are glancing on the forward roadway are also less likely to glance toward areas for potential vehicle–bicyclist conflicts. But this study did not determine whether cognitively distracted drivers who did glance toward the appropriate area were as likely to process the information as drivers who were not cognitively distracted. Evidence that drivers who were cognitively distracted and glanced toward the bicyclist were not as likely to process the information could be inferred either from shorter fixations in the area where a bicyclist could appear or from smaller reductions in the speed of their vehicle to mitigate a potential conflict. This study intends to add to previous results by examining only glance and vehicle behaviors of participants who glance toward the latent hazardous events involving bicyclists. Specifically, the durations of the glances toward the latent hazardous events of participants who are and are not cognitively distracted are compared as well as their velocity while approaching the potential strike zones. Two groups of 20 participants (one distracted, one not distracted) each drove through seven scenarios on a fixed-based driving simulator while their eye movements were continuously tracked using an eye tracker. Analysis of the participants’ longest glance duration toward the latent hazardous events indicated that distracted drivers made shorter glances toward the latent hazardous events when compared with their non-distracted counterparts. However, there was no difference in vehicle velocity between distracted and non-distracted drivers near the potential strike zones.