scholarly journals Optimal 3D Deployment and Trajectory Selection of UAVs for Maximum Network Utility and Disaster Management

2021 ◽  
Author(s):  
Sanjoy Debnath ◽  
Wasim Arif ◽  
Debarati Sen ◽  
Srimanta Baishya
Keyword(s):  
Differential Evolution ◽  
Optimal Trajectory ◽  
Seismic Survey ◽  
Network Coverage ◽  
User Coverage ◽  
User Data ◽  
Optimal Resource ◽  
Optimal Deployment ◽  
Rate Requirement

Abstract Advancement in Unmanned Aerial Vehicles (UAV) technology supervised us to use them in many situations like seismic survey of an area, border and restricted area surveillance, disaster rescue, agriculture monitoring, and many others. The deployment of UAVs for expansion and extension of wireless network coverage for surveillance and rescue during and post disaster situations is fenced with promising challenges. The dense user coverage, quality of service (QoS), user data rate requirement, limited short flying time, and optimal trajectory path are some of the pertinent issues that UAVs are encountering. In this work we develop some algorithms for fast deployment of UAVs for application in disaster scenarios and optimal trajectory of each UAV in some specified area. The main aim of the work is to reduce the time complexity for optimal deployment of UAVs in order to optimize diverse parametric constraints. We propose a highly time efficient algorithm for UAV deployment through Lloyd and FCM as the initial localization of position in conjunction with the evolutionary algorithm namely Differential Evolution (DE) and Hybrid Differential Evolution with Learning (HDEL) for finding the optimal location of UAVs. We also develop an algorithm for finding out the optimal trajectory to reach the intended location for effective deployment of UAVs to ensure optimal resource allocation and user coverage. Comprehensive simulation of various performance measuring metrics is obtained and the result shows that the proposed algorithms are well efficient as compared to some of the standard algorithms used in deployment of UAVs.

scholarly journals Complete resource pooling of a load-balancing policy for a network of battery swapping stations

2021 ◽  
Author(s):  
Fiona Sloothaak ◽  
James Cruise ◽  
Seva Shneer ◽  
Maria Vlasiou ◽  
Bert Zwart
Keyword(s):  
Carbon Emission ◽  
Queueing Network ◽  
Service Levels ◽  
Resource Pooling ◽  
Transportation Sector ◽  
Single Station ◽  
Optimal Resource ◽  
Promising Solution ◽  
Reduce Carbon Emission

AbstractTo reduce carbon emission in the transportation sector, there is currently a steady move taking place to an electrified transportation system. This brings about various issues for which a promising solution involves the construction and operation of a battery swapping infrastructure rather than in-vehicle charging of batteries. In this paper, we study a closed Markovian queueing network that allows for spare batteries under a dynamic arrival policy. We propose a provisioning rule for the capacity levels and show that these lead to near-optimal resource utilization, while guaranteeing good quality-of-service levels for electric vehicle users. Key in the derivations is to prove a state-space collapse result, which in turn implies that performance levels are as good as if there would have been a single station with an aggregated number of resources, thus achieving complete resource pooling.

The Importance of Skin Disease as Assessed by “Willingness-To-Pay”

2003 ◽  
Vol 7 (5) ◽  
pp. 369-371 ◽  
Author(s):  
Lauren Parks ◽  
Rajesh Balkrishnan ◽  
Line Hamel-Gariépy ◽  
Steven R. Feldman
Keyword(s):  
Willingness To Pay ◽  
Skin Disease ◽  
Skin Diseases ◽  
Medical Conditions ◽  
Monthly Basis ◽  
Related Quality ◽  
Health Related ◽  
Optimal Resource ◽  
The Impact

Background: To achieve optimal resource allocation in health care, it is necessary to value competing resource uses according to the benefit derived from those uses. Skin disease makes as great an impact as other serious medical conditions when assessed by effects on health-related quality of life. Objective: To confirm the high impact of skin disease by comparing patients' willingness to pay (WTP) to be cured or relieved from symptoms of skin and nonskin conditions. Methods: We searched the published literature on WTP to compare the impact of dermatologic conditions with the impact of other medical conditions. A total of 46 articles were identified of which 10 included information on willingness to pay for cure reported on a monthly basis. Results: WTP for skin diseases fell in the range of $125–260/month and was comparable or higher than all but one of the other identified conditions. Conclusion: Willingness to pay for relief from skin diseases is comparable to that for relief of other serious medical conditions. Skin diseases are associated with a significant adverse impact on patients' lives.

scholarly journals FPGA–implementation of PID-controller by differential evolution optimization

2018 ◽  
Vol 8 (1) ◽  
pp. 395-402
Author(s):  
Mika Hanhila ◽  
Timo Mantere ◽  
Jarmo T. Alander
Keyword(s):  
Differential Evolution ◽  
Pid Controller ◽  
Differential Evolution Algorithm ◽  
Fpga Implementation ◽  
Solution Convergence ◽  
Fitness Value ◽  
Mutation Operation ◽  
Self Adaptation ◽  
Evolution Algorithm

Abstract We will describe an FPGA implementation of PID-controller that uses differential evolution to optimize the coefficients of the PID controller, which has been implemented in VHDL. The original differential evolution algorithm was improved by ranking based mutation operation and self-adaptation of mutation and crossover parameters. Ranking-based mutation operation improves the quality of solution, convergence rate and success of optimization. Due to the self-adaptive control parameters, the user does not have to estimate the mutation and crossover rates. Optimization have been performed by calculating for each generation fitness value by means of trial parameters. The final optimal parameters are selected based on the minimum fitness.

scholarly journals How Unique is "E-stonia"? A Cross-Country Comparison of E-Services Usage in Europe

2019 ◽  
Author(s):  
Fabian Stephany
Keyword(s):  
Role Model ◽  
Young Population ◽  
Baltic State ◽  
Digital Government ◽  
Individual Privacy ◽  
The Social ◽  
User Data ◽  
Cross Country ◽  
The Government

User data fuel the digital economy, while individual privacy is at stake. Governments react differently to this challenge. Estonia, a small Baltic state, has become a role model for the renewal of the social contract in times of big data (hence, often ironically referred to as "E-stonia"). While e-governance usage has been growing in many parts of Europe during the last ten years, some regions are lagging behind. The Estonian example suggests that online governance is most accepted in a small state, with a young population, trustworthy institutions and the need of technological renewal. This work examines the development of e-governance usage (citizens interacting digitally with the government) during the last decade in Europe from a comprehensive cross-country perspective: Size, age and trust are relevant for the usage of digital government services in Europe. However, the quality of past communication infrastructure is not related to e-governance popularity.

scholarly journals Adaptive Unified Differential Evolution for Clustering

2018 ◽  
Vol 12 (1) ◽  
pp. 53
Author(s):  
Maulida Ayu Fitriani ◽  
Aina Musdholifah ◽  
Sri Hartati
Keyword(s):  
Differential Evolution ◽  
Fitness Function ◽  
Single Mutation ◽  
Clustering Methods ◽  
Mutation Strategy ◽  
Clustering Quality ◽  
Silhouette Index ◽  
Mutation Strategies ◽  
Time Required

Various clustering methods to obtain optimal information continues to evolve one of its development is Evolutionary Algorithm (EA). Adaptive Unified Differential Evolution (AuDE), is the development of Differential Evolution (DE) which is one of the EA techniques. AuDE has self adaptive scale factor control parameters (F) and crossover-rate (Cr).. It also has a single mutation strategy that represents the most commonly used standard mutation strategies from previous studies.The AuDE clustering method was tested using 4 datasets. Silhouette Index and CS Measure is a fitness function used as a measure of the quality of clustering results. The quality of the AuDE clustering results is then compared against the quality of clustering results using the DE method.The results show that the AuDE mutation strategy can expand the cluster central search produced by ED so that better clustering quality can be obtained. The comparison of the quality of AuDE and DE using Silhoutte Index is 1:0.816, whereas the use of CS Measure shows a comparison of 0.565:1. The execution time required AuDE shows better but Number significant results, aimed at the comparison of Silhoutte Index usage of 0.99:1 , Whereas on the use of CS Measure obtained the comparison of 0.184:1.

scholarly journals Differential Evolution in Wireless Communications: A Review

2019 ◽  
Vol 15 (11) ◽  
pp. 29
Author(s):  
Hilary I Okagbue ◽  
Muminu O Adamu ◽  
Timothy A Anake
Keyword(s):  
Wireless Communications ◽  
Differential Evolution ◽  
Computational Method ◽  
Biological Processes ◽  
Search Region ◽  
Coverage Area ◽  
Related Field ◽  
Research Areas ◽  
Scientific Fields

<p class="0abstract">Differential Evolution (DE) is an evolutionary computational method inspired by the biological processes of evolution and mutation. DE has been applied in numerous scientific fields. The paper presents a literature review of DE and its application in wireless communication. The detailed history, characteristics, strengths, variants and weaknesses of DE were presented. Seven broad areas were identified as different domains of application of DE in wireless communications. It was observed that coverage area maximisation and energy consumption minimisation are the two major areas where DE is applied. Others areas are quality of service, updating mechanism where candidate positions learn from a large diversified search region, security and related field applications. Problems in wireless communications are often modelled as multiobjective optimisation which can easily be tackled by the use of DE or hybrid of DE with other algorithms. Different research areas can be explored and DE will continue to be utilized in this context.</p>

scholarly journals Design and Analysis of Sustainable and Seasonal Profit Scaling Model in Cloud Environment

2019 ◽  
Vol 2019 ◽  
pp. 1-14
Author(s):  
Monika Kumari ◽  
G. Sahoo
Keyword(s):  
Genetic Algorithm ◽  
Differential Evolution ◽  
Resource Provisioning ◽  
Vertical Scaling ◽  
Predator Prey ◽  
Average Completion Time ◽  
Predator Prey Model ◽  
De Algorithm ◽  
Optimal Resource ◽  
And Performance

Cloud is a widely used platform for intensive computing, bulk storage, and networking. In the world of cloud computing, scaling is a preferred tool for resource management and performance determination. Scaling is generally of two types: horizontal and vertical. The horizontal scale connects users’ agreement with the hardware and software entities and is implemented physically as per the requirement and demand of the datacenter for its further expansion. Vertical scaling can essentially resize server without any change in code and can increase the capacity of existing hardware or software by adding resources. The present study aims at describing two approaches for scaling, one is a predator-prey method and second is genetic algorithm (GA) along with differential evolution (DE). The predator-prey method is a mathematical model used to implement vertical scaling of task for optimal resource provisioning and genetic algorithm (GA) along with differential evolution(DE) based metaheuristic approach that is used for resource scaling. In this respect, the predator-prey model introduces two algorithms, namely, sustainable and seasonal scaling algorithm (SSSA) and maximum profit scaling algorithm (MPSA). The SSSA tries to find the approximation of resource scaling and the mechanism for maximizing sustainable as well as seasonal scaling. On the other hand, the MPSA calculates the optimal cost per reservation and maximum sustainable profit. The experimental results reflect that the proposed logistic scaling-based predator-prey method (SSSA-MPSA) provides a comparable result with GA-DE algorithm in terms of execution time, average completion time, and cost of expenses incurred by the datacenter.

Introduction to this special section: Acquisition and sensing

2019 ◽  
Vol 38 (9) ◽  
pp. 670-670
Author(s):  
Margarita Corzo ◽  
Tim Brice ◽  
Ray Abma
Keyword(s):  
Special Section ◽  
Seismic Survey ◽  
Ocean Bottom ◽  
Total Cost ◽  
Small Boat ◽  
Air Gun ◽  
Seismic Acquisition ◽  
The Cost ◽  
Seismic Images

Seismic acquisition has undergone a revolution over the last few decades. The volume of data acquired has increased exponentially, and the quality of seismic images obtained has improved tremendously. While the total cost of acquiring a seismic survey has increased, the cost per trace has dropped precipitously. Land surveys have evolved from sparse 2D lines acquired with a few dozen receivers to densely sampled 3D multiazimuth surveys. Marine surveys that once may have consisted of a small boat pulling a single cable have evolved to large streamer vessels pulling multiple cables and air-gun arrays and to ocean-bottom detectors that require significant fleets to place the detectors, shoot the sources, and provide support. These surveys collect data that are wide azimuth and typically fairly well sampled.

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