scholarly journals Cluster Design and Optimization of SWIPT-Based MEC Networks with UAV Assistance

2021 ◽  
Vol 2021 ◽  
pp. 1-14
Author(s):  
Xuefei E ◽  
Zhonggui Ma ◽  
JunFeng Huang
Keyword(s):  
Resource Allocation ◽  
Dimensional Space ◽  
Low Cost ◽  
Bat Algorithm ◽  
Design And Optimization ◽  
Resource Requirements ◽  
Calculation Task ◽  
Degree Of Stability ◽  
Resource Allocation Strategy ◽  
Disaster Tolerance

In recent years, service isolation and service miniaturization have become very popular. The large services are dismantled into multiple low-cost and simple small services to improve the scalability and disaster tolerance of the entire services. A service network composed of unmanned aerial vehicles (UAVs) and MEC servers is proposed in this paper, which aims at decoupling multiple services of the SWIPT-MEC network. In this network, UAVs take charge of energy transmission and calculation task scheduling and MEC servers are focused on task calculation. To meet the resource requirements of the ground nodes (GNs) in the network, we designed a distributed iterative algorithm to solve the resource allocation decision problem of GNs and used the modified expert bat algorithm to complete the UAV’s trajectory planning in a two-dimensional space. The results show that the algorithm can formulate a more fair resource allocation strategy, and its performance is improved by 7% compared with the traditional bat algorithm. In addition, the algorithm in this paper can also adapt to changes in task length and has a certain degree of stability.

Moth Flame Optimization Algorithm Range-Based for Node Localization Challenge in Decentralized Wireless Sensor Network

2019 ◽  
Vol 10 (1) ◽  
pp. 82-109 ◽  
Author(s):  
Mihoubi Miloud ◽  
Rahmoun Abdellatif ◽  
Pascal Lorenz
Keyword(s):  
Swarm Intelligence ◽  
Optimization Algorithm ◽  
Dimensional Space ◽  
Fitness Function ◽  
Low Cost ◽  
Bat Algorithm ◽  
Wireless Sensor ◽  
Flower Pollination Algorithm ◽  
Node Localization ◽  
Moth Flame Optimization Algorithm

Recently developments in wireless sensor networks (WSNs) have raised numerous challenges, node localization is one of these issues. The main goal in of node localization is to find accurate position of sensors with low cost. Moreover, very few works in the literature addressed this issue. Recent approaches for localization issues rely on swarm intelligence techniques for optimization in a multi-dimensional space. In this article, we propose an algorithm for node localization, namely Moth Flame Optimization Algorithm (MFOA). Nodes are located using Euclidean distance, thus set as a fitness function in the optimization algorithm. Deploying this algorithm on a large WSN with hundreds of sensors shows pretty good performance in terms of node localization. Computer simulations show that MFOA converge rapidly to an optimal node position. Moreover, compared to other swarm intelligence techniques such as Bat algorithm (BAT), particle swarm optimization (PSO), Differential Evolution (DE) and Flower Pollination Algorithm (FPA), MFOA is shown to perform much better in node localization task.

scholarly journals Resource Allocation in Cloud Computing for Energy Efficiency

2019 ◽  
Vol 8 (6) ◽  
pp. 1170-1174
Keyword(s):  
Resource Allocation ◽  
Cloud Computing ◽  
Power Consumption ◽  
High Performance ◽  
High Reliability ◽  
Low Cost ◽  
Work Load ◽  
Cloud Infrastructure ◽  
Multiple Resources ◽  
Resource Requirements

Cloud computing is a paradigm in which we have virtualized computer systems that deliver services, processing, storage, network, and other fundamental computing resources. Cloud computing enables low cost, device location independence, high reliability, scalability and sustainability. This paper describes the present state of cloud computing research by examining literature, identifying current study trends. We have analyzed the resource allocation method and concluded. It typically designs for high performance that supports the peak resource requirements. After several analyses the power consumption of data center and cloud systems as increased almost several times. There is a lack of research that addresses challenges of managing multiple resources with objective of allocating enough resources for each work load to optimizing power consumption. These papers survey various types of resource allocation algorithms that improve the cloud Infrastructure.

Resource Allocation in Cloud using Multi Bidding Model with User Centric Behavior Analysis

2020 ◽  
Vol 13 (5) ◽  
pp. 1008-1019
Author(s):  
N. Vijayaraj ◽  
T. Senthil Murugan
Keyword(s):  
Resource Allocation ◽  
Behavior Analysis ◽  
User Behavior ◽  
Low Cost ◽  
Cloud Services ◽  
Online Auction ◽  
Analysis Model ◽  
Efficient Resource ◽  
User Centric ◽  
Cloud Resources

Background: Number of resource allocation and bidding schemes had been enormously arrived for on demand supply scheme of cloud services. But accessing and presenting the Cloud services depending on the reputation would not produce fair result in cloud computing. Since the cloud users not only looking for the efficient services but in major they look towards the cost. So here there is a way of introducing the bidding option system that includes efficient user centric behavior analysis model to render the cloud services and resource allocation with low cost. Objective: The allocation of resources is not flexible and dynamic for the users in the recent days. This gave me the key idea and generated as a problem statement for my proposed work. Methods: An online auction framework that ensures multi bidding mechanism which utilizes user centric behavioral analysis to produce the efficient and reliable usage of cloud resources according to the user choice. Results: we implement Efficient Resource Allocation using Multi Bidding Model with User Centric Behavior Analysis. Thus the algorithm is implemented and system is designed in such a way to provide better allocation of cloud resources which ensures bidding and user behavior. Conclusion: Thus the algorithm Efficient Resource Allocation using Multi Bidding Model with User Centric Behavior Analysis is implemented & system is designed in such a way to provide better allocation of cloud resources which ensures bidding, user behavior. The user bid data is trained accordingly such that to produce efficient resource utilization. Further the work can be taken towards data analytics and prediction of user behavior while allocating the cloud resources.

scholarly journals Sensor Networks for Structures Health Monitoring: Placement, Implementations, and Challenges—A Review

Vibration ◽  
2021 ◽  
Vol 4 (3) ◽  
pp. 551-584
Author(s):  
Samir Mustapha ◽  
Ye Lu ◽  
Ching-Tai Ng ◽  
Pawel Malinowski
Keyword(s):  
Sensor Networks ◽  
Health Monitoring ◽  
Data Transmission ◽  
System Integration ◽  
Structural Integrity ◽  
Low Cost ◽  
Data Communication ◽  
Total Cost ◽  
Design And Optimization ◽  
Successful Case

The development of structural health monitoring (SHM) systems and their integration in actual structures has become a necessity as it can provide a robust and low-cost solution for monitoring the structural integrity of and the ability to predict the remaining life of structures. In this review, we aim at focusing on one of the important issues of SHM, the design, and implementation of sensor networks. Location and number of sensors, in any SHM system, are of high importance as they impact the system integration, system performance, and accuracy of assessment, as well as the total cost. Hence we are interested in shedding the light on the sensor networks as an essential component of SHM systems. The review discusses several important parameters including design and optimization of sensor networks, development of academic and commercial solutions, powering of sensors, data communication, data transmission, and analytics. Finally, we presented some successful case studies including the challenges and limitations associated with the sensor networks.

MPPT-based on Bat algorithm for photovoltaic systems working under partial shading conditions

2021 ◽  
pp. 1-9
Author(s):  
Mohammed Asim ◽  
Piyush Agrawal ◽  
Mohd Tariq ◽  
Basem Alamri
Keyword(s):  
Low Cost ◽  
Bat Algorithm ◽  
Photovoltaic System ◽  
Maximum Power Point ◽  
Partial Shading ◽  
Point Tracking ◽  
Power Point Tracking ◽  
Full Power ◽  
Power Point ◽  
Global Peak

Under partial shading conditions (PSC), most traditional maximum power point tracking (MPPT) techniques may not adopt GP (global peak). These strategies also often take a considerable amount of time to reach a full power point (MPP). Such obstacles can be eliminated by the use of metaheuristic strategies. This paper shows, in partial shading conditions, the MPPT technique for the photovoltaic system using the Bat Algorithm (BA). Simulations have been performed in the MATLAB ®/Simulink setting to verify the efficacy of the proposed method. In MPPT applications, the results of the simulations emphasize the precision of the proposed technique. The algorithm is also simple and efficient, on a low-cost microcontroller, it could be implemented. Hardwar in loop (HIL) validation is performed, with a Typhoon HIL 402 setup.

scholarly journals Improved Bat Algorithm for UAV Path Planning in Three-Dimensional Space

IEEE Access ◽  
2021 ◽  
Vol 9 ◽  
pp. 20100-20116
Author(s):  
Xianjin Zhou ◽  
Fei Gao ◽  
Xi Fang ◽  
Zehong Lan
Keyword(s):  
Path Planning ◽  
Dimensional Space ◽  
Three Dimensional ◽  
Bat Algorithm ◽  
Three Dimensional Space
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