scholarly journals A Joint Optimization Strategy of Coverage Planning and Energy Scheduling for Wireless Rechargeable Sensor Networks

Processes ◽  
2020 ◽  
Vol 8 (10) ◽  
pp. 1324
Author(s):  
Cheng Gong ◽  
Chao Guo ◽  
Haitao Xu ◽  
Chengcheng Zhou ◽  
Xiaotao Yuan
Keyword(s):  
Sensor Networks ◽  
Communication Networks ◽  
Energy Supply ◽  
Large Scale ◽  
Joint Optimization ◽  
Second Phase ◽  
Optimization Strategy ◽  
Two Phase ◽  
Game Equilibrium ◽  
Wireless Rechargeable Sensor Networks

Wireless Sensor Networks (WSNs) have the characteristics of large-scale deployment, flexible networking, and many applications. They are important parts of wireless communication networks. However, due to limited energy supply, the development of WSNs is greatly restricted. Wireless rechargeable sensor networks (WRSNs) transform the distributed energy around the environment into usable electricity through energy collection technology. In this work, a two-phase scheme is proposed to improve the energy management efficiency for WRSNs. In the first phase, we designed an annulus virtual force based particle swarm optimization (AVFPSO) algorithm for area coverage. It adopts the multi-parameter joint optimization method to improve the efficiency of the algorithm. In the second phase, a queuing game-based energy supply (QGES) algorithm was designed. It converts energy supply and consumption into network service. By solving the game equilibrium of the model, the optimal energy distribution strategy can be obtained. The simulation results show that our scheme improves the efficiency of coverage and energy supply, and then extends the lifetime of WSN.

scholarly journals Joint Optimization Strategy of Coverage Planning and Energy Scheduling for Wireless Rechargeable Sensor Networks

2020 ◽  
Author(s):  
Cheng Gong ◽  
Chao Guo ◽  
Haitao Xu ◽  
Chengcheng Zhou ◽  
Xiaotao Yuan
Keyword(s):  
Sensor Networks ◽  
Communication Networks ◽  
Energy Supply ◽  
Large Scale ◽  
Optimization Method ◽  
Joint Optimization ◽  
Second Phase ◽  
Optimization Strategy ◽  
Game Equilibrium ◽  
Wireless Rechargeable Sensor Networks

Wireless Sensor Networks (WSNs) has the characteristics of large-scale deployment, flexible networking, and wide application. It is an important part of the wireless communication networks. However, due to limited energy supply, the development of WSN is greatly restricted. Wireless Rechargeable Sensor Networks (WRSNs) transform the distributed energy around the environment into usable electricity through energy collection technology. In this work, a joint optimization strategy is proposed to improve the energy management efficiency for WRSNs. The joint optimization strategy is divided into two phases. In the first phase, we design an Annulus Virtual Force based Particle Swarm Optimization (AVFPSO) algorithm for area coverage planing. It adopts the multi-parameter joint optimization method to improve the efficiency of the algorithm. In the second phase, a Queuing Game-based Energy Supply (QGES) algorithm is designed for energy scheduling. It converts energy supply and consumption into network service. By solving the game equilibrium of the model, the optimal energy distribution strategy can be obtained. The simulation results show that our scheme improves the efficiency of coverage and energy, and extends the lifetime of WSN.

scholarly journals A Study on Applicability of the Scrum Framework for Large Software Projects

2021 ◽  
Author(s):  
Jaweria Sultana
Keyword(s):  
Literature Review ◽  
Systematic Literature Review ◽  
Large Scale ◽  
Primary Objective ◽  
Work Rate ◽  
Communication Overhead ◽  
Second Phase ◽  
Software Projects ◽  
Two Phase ◽  
Good Communication

The primary objective of this research is to investigate the adaptability of the Scrum framework for large scale projects. A two phase approach has been undertaken towards the goal. The first phase involves conducting a systematic literature review to identify and elaborate scaling practices used in the current industry. The review also identifies the challenges faced by the developers when the Scrum framework is used for the development of large projects. The second phase involves the construction of a simulation model to analyze the dynamic behavior of the Scrum framework for large projects. The systematic literature review revealed that the major challenge while scaling Scrum is ensuring good communication among project members. The communication overhead was incorporated in the system dynamic model of the Scrum framework. The simulation results showed that there is a reduction in work rate when number of personnel is increased due to the increasing communication overhead.

Towards Rapid Redesign: Pattern-Based Design Diagnostics for Large-Scale and Complex Redesign Problems

2005 ◽  
Author(s):  
Li Chen ◽  
Ashish Macwan
Keyword(s):  
Large Scale ◽  
Functional Dependence ◽  
Agile Manufacturing ◽  
Design Model ◽  
Second Phase ◽  
Phase Decomposition ◽  
Two Phase ◽  
Dependency Matrix ◽  
Solution Approach ◽  
Coupling Structure

This paper presents our continued research efforts towards developing a decomposition-based solution approach for rapid computational redesign to support agile manufacturing of evolutionary products. By analogy to the practices used for physical machines, the proposed approach involves two general steps: diagnosis and repair. This paper focuses on the diagnosis step. for which a two-phase decomposition method is developed. The first phase, called design dependency analysis, systematizes and reorganizes the intrinsic coupling structure of the existing design model by analyzing and reordering the design dependency matrix (DDM) used to represent the functional dependence and couplings inherent in the design model. The second phase, called redesign partitioning analysis, uses this result to generate alternative redesign pattern solutions through a three-stage procedure. Each pattern solution delimits the portions of the design model that need to be re-computed. An example problem concerning the redesign of an automobile powertrain is used for method illustration. Our seed paper has presented a method for selecting the optimal redesign pattern solution from the alternatives generated through redesign partitioning analysis, and a sequel paper will discuss how to generate a corresponding re-computation strategy and redesign plan (redesign shortcut roadmap).

3D MС Simulation of Grain Growth Kinetics and the Zener Limit in Polycrystals

2014 ◽  
Vol 598 ◽  
pp. 8-12
Author(s):  
K.R. Phaneesh ◽  
Anirudh Bhat ◽  
Gautam Mukherjee ◽  
Kishore T. Kashyap
Keyword(s):  
Monte Carlo ◽  
Grain Growth ◽  
Growth Kinetics ◽  
Large Scale ◽  
Volume Fraction ◽  
Growth Exponent ◽  
Cube Root ◽  
Second Phase ◽  
Two Phase ◽  
Second Phase Particles

Large scale Potts model Monte Carlo simulation was carried on 3-dimensional square lattices of 1003 and 2003 sizes using the Metropolis algorithm to study grain growth behavior. Simulations were carried out to investigate both growth kinetics as well as the Zener limit in two-phase polycrystals inhibited in growth by second phase particles of single-voxel size. Initially the matrices were run to 10,000 Monte Carlo steps (MCS) to check the growth kinetics in both single phase and two-phase poly-crystals. Grain growth exponent values obtained as a result have shown to be highest (~ 0.4) for mono-phase materials while the value decreases with addition of second phase particles. Subsequently the matrices were run to stagnation in the presence of second phase particles of volume fractions ranging from 0.001to 0.1. Results obtained have shown a cube root dependence of the limiting grain size over the particle volume fraction thus reinforcing earlier 3D simulation efforts. It was observed that there was not much difference in the values of either growth kinetics or the Zener limit between 1003 and 2003 sized matrices, although the results improved mildly with size.

scholarly journals Two-Phase Time Synchronization-Free Localization Algorithm for Underwater Sensor Networks

2017 ◽  
Author(s):  
Junhai Luo ◽  
Liying Fan
Keyword(s):  
Sensor Networks ◽  
Time Synchronization ◽  
Sensor Nodes ◽  
Second Phase ◽  
Underwater Sensor Networks ◽  
Localization Algorithm ◽  
Two Phase ◽  
Phase Time ◽  
Anchor Nodes ◽  
Range Free

Underwater Sensor Networks (UWSNs) can enable a broad range of applications such as resource monitoring, disaster prevention, and navigation-assisted. It is especially relevant for sensor nodes location in UWSNs. Global Positioning System (GPS) is not suitable for using in UWSNs because of the underwater propagation problems. Hence some localization algorithms based on the precise time synchronization between sensor nodes have been proposed which are not feasible for UWSNs. In this paper, we propose a localization algorithm called Two-Phase Time Synchronization-Free Localization Algorithm (TP-TSFLA). TP-TSFLA contains two phases, namely, range-based estimation phase and range-free evaluation phase. In the first phase, we address a time synchronization-free localization scheme base on the Particle Swarm Optimization (PSO) algorithm to decrease the localization error. In the second phase, we propose a Circle-based Range-Free Localization Algorithm (CRFLA) to locate the unlocalized sensor nodes which cannot obtain the location information through the first phase. In the second phase, sensor nodes which are localized in the first phase act as the new anchor nodes to help realize localization. Hence in this algorithm, we use a small number of mobile beacons to help achieve location without any other anchor nodes. Besides, to improve the precision of the range-free method, an extension of CRFLA by designing a coordinate adjustment scheme is updated. The simulation results show that TP-TSFLA can achieve a relative high localization ratio without time synchronization.

Minimizing the number of wireless charging PAD for unmanned aerial vehicle–based wireless rechargeable sensor networks

2021 ◽  
Vol 17 (12) ◽  
pp. 155014772110559
Author(s):  
Yingjue Chen ◽  
Yingnan Gu ◽  
Panfeng Li ◽  
Feng Lin
Keyword(s):  
Sensor Networks ◽  
Unmanned Aerial Vehicles ◽  
Unmanned Aerial Vehicle ◽  
Large Scale ◽  
Base Station ◽  
Sensor Nodes ◽  
Wireless Charging ◽  
Aerial Vehicles ◽  
Wireless Rechargeable Sensor Networks ◽  
Aerial Vehicle

In wireless rechargeable sensor networks, most researchers address energy scarcity by introducing one or multiple ground mobile vehicles to recharge energy-hungry sensor nodes. The charging efficiency is limited by the moving speed of ground chargers and rough environments, especially in large-scale or challenging scenarios. To address the limitations, researchers consider replacing ground mobile chargers with lightweight unmanned aerial vehicles to support large-scale scenarios because of the unmanned aerial vehicle moving at a higher speed without geographical limitation. Moreover, multiple automatic landing wireless charging PADs are deployed to recharge unmanned aerial vehicles automatically. In this work, we investigate the problem of introducing the minimal number of PADs in unmanned aerial vehicle–based wireless rechargeable sensor networks. We propose a novel PAD deployment scheme named clustering-with-double-constraints and disks-shift-combining that can adapt to arbitrary locations of the base station, arbitrary geographic distributions of sensor nodes, and arbitrary sizes of network areas. In the proposed scheme, we first obtain an initial PAD deployment solution by clustering nodes in geographic locations. Then, we propose a center shift combining algorithm to optimize this solution by shifting the location of PADs and attempting to merge the adjacent PADs. The simulation results show that compared to existing algorithms, our scheme can charge the network with fewer PADs.

scholarly journals A Type of Annulus-Based Energy Balanced Data Collection Method in Wireless Rechargeable Sensor Networks

Sensors ◽  
2018 ◽  
Vol 18 (9) ◽  
pp. 3150 ◽  
Author(s):  
Chao Sha ◽  
Qin Liu ◽  
Si-Yi Song ◽  
Ru-Chuan Wang
Keyword(s):  
Energy Consumption ◽  
Sensor Networks ◽  
Data Collection ◽  
Large Scale ◽  
Energy Hole ◽  
Node Scheduling ◽  
Wireless Rechargeable Sensor Networks ◽  
Energy Consumption Optimization ◽  
Balance Energy ◽  
Simulation Results

With the increasing number of ubiquitous terminals and the continuous expansion of network scale, the problem of unbalanced energy consumption in sensor networks has become increasingly prominent in recent years. However, a node scheduling strategy or an energy consumption optimization algorithm may be not enough to meet the requirements of large-scale application. To address this problem a type of Annulus-based Energy Balanced Data Collection (AEBDC) method is proposed in this paper. The circular network is divided into several annular sectors of different sizes. Nodes in the same annulus-sector form a cluster. Based on this model, a multi-hop data forwarding strategy with the help of the candidate cluster headers is proposed to balance energy consumption during transmission and to avoid buffer overflow. Meanwhile, in each annulus, there is a Wireless Charging Vehicle (WCV) that is responsible for periodically recharging the cluster headers as well as the candidate cluster headers. By minimizing the recharging cost, the energy efficiency is enhanced. Simulation results show that AEBDC can not only alleviate the “energy hole problem” in sensor networks, but also effectively prolong the network lifetime.

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