Efficient Management of Fragmented Replica in Data Grids

2012 ◽  
Vol 4 (2) ◽  
pp. 63-70 ◽  
Author(s):  
Chao-Chin Wu ◽  
Lien-Fu Lai ◽  
Jia-Xian Lai
Keyword(s):  
Optimal Solution ◽  
Selection Algorithm ◽  
Data Grids ◽  
Server Selection ◽  
Efficient Management ◽  
Replica Selection ◽  
Retrieval Efficiency ◽  
Simulation Results ◽  
Replication Technique ◽  
Selection Algorithms

Rather than replicating a file completely, Chang et al. proposed a fragmented replication technique to cope with the problem that only partial content of the replica are required in a local application. Furthermore, they also proposed two server selection algorithms for replica retrieval. However, their algorithms do not always find an optimal solution. To address the problem, in this paper, the authors propose a replica selection algorithm to improve the fragmented replica retrieval efficiency in this paper. It is a heuristic considering not only the transmission time but also the number of available servers for each block. Simulation results show that the proposed algorithm can improve the retrieval efficiency up to 12%.

scholarly journals An Improved Normalized Mutual Information Variable Selection Algorithm for Neural Network-Based Soft Sensors

Sensors ◽  
2019 ◽  
Vol 19 (24) ◽  
pp. 5368 ◽  
Author(s):  
Kai Sun ◽  
Pengxin Tian ◽  
Huanning Qi ◽  
Fengying Ma ◽  
Genke Yang
Keyword(s):  
Mutual Information ◽  
Variable Selection ◽  
Optimal Solution ◽  
Selection Algorithm ◽  
Soft Sensors ◽  
Model Accuracy ◽  
Normalized Mutual Information ◽  
Entropy Information ◽  
Local Optimal Solution ◽  
Selection Algorithms

In this paper, normalized mutual information feature selection (NMIFS) and tabu search (TS) are integrated to develop a new variable selection algorithm for soft sensors. NMIFS is applied to select influential variables contributing to the output variable and avoids selecting redundant variables by calculating mutual information (MI). A TS based strategy is designed to prevent NMIFS from falling into a local optimal solution. The proposed algorithm performs the variable selection by combining the entropy information and MI and validating error information of artificial neural networks (ANNs); therefore, it has advantages over previous MI-based variable selection algorithms. Several simulation datasets with different scales, correlations and noise parameters are implemented to demonstrate the performance of the proposed algorithm. A set of actual production data from a power plant is also used to check the performance of these algorithms. The experiments showed that the developed variable selection algorithm presents better model accuracy with fewer selected variables, compared with other state-of-the-art methods. The application of this algorithm to soft sensors can achieve reliable results.

Wireless Sensor Network Link Selection Algorithm with Bayesian Technique

2014 ◽  
Vol 1078 ◽  
pp. 329-332
Author(s):  
Lai Jun Luo ◽  
Hai Ping Ren
Keyword(s):  
Wireless Sensor Networks ◽  
Wireless Sensor Network ◽  
Success Rate ◽  
Bayesian Approach ◽  
Wireless Sensor ◽  
Small Samples ◽  
Selection Algorithm ◽  
Network Link ◽  
Simulation Results ◽  
Selection Algorithms

In wireless sensor networks, traditional link selection algorithm needs lots of data packages as testing samples, but the nodes of WSN are battery-powered, so the energy is extremely limited. To overcome this shortcoming, the aim of this paper is to propose three new link selection algorithms based the concept of Bayesian approach. Simulation results demonstrate that the three algorithms based on Bayesian approach have a higher success rate than empirical-algorithm by about 10 percent in selecting the highest quality link with the case of small samples. Among them, BSLA-EB has a good adaptability and it can get better experimental results.

An Enhancement of Feature Selection Algorithm for EDM: A Review

2018 ◽  
Vol 8 (5) ◽  
pp. 29
Author(s):  
Manpreet Kaur ◽  
Chamkaur Singh
Keyword(s):  
Feature Selection ◽  
Educational Data Mining ◽  
Problem Formulation ◽  
Research Area ◽  
Education Quality ◽  
Educational Institutions ◽  
Selection Algorithm ◽  
Positive Role ◽  
Data Set ◽  
Selection Algorithms

Educational Data Mining (EDM) is an emerging research area help the educational institutions to improve the performance of their students. Feature Selection (FS) algorithms remove irrelevant data from the educational dataset and hence increases the performance of classifiers used in EDM techniques. This paper present an analysis of the performance of feature selection algorithms on student data set. .In this papers the different problems that are defined in problem formulation. All these problems are resolved in future. Furthermore the paper is an attempt of playing a positive role in the improvement of education quality, as well as guides new researchers in making academic intervention.

scholarly journals Optimal Decision-Making to Charge Electric Vehicles in Heterogeneous Networks: Stackelberg Game Approach

Energies ◽  
2019 ◽  
Vol 12 (2) ◽  
pp. 325 ◽  
Author(s):  
Shijun Chen ◽  
Huwei Chen ◽  
Shanhe Jiang
Keyword(s):  
Electric Vehicles ◽  
Heterogeneous Networks ◽  
Demand Uncertainty ◽  
Stackelberg Game ◽  
Optimal Solution ◽  
Stackelberg Equilibrium ◽  
Optimal Decision ◽  
Charging Station ◽  
Simulation Results ◽  
Grid Operators

Electric vehicles (EVs) are designed to improve the efficiency of energy and prevent the environment from being polluted, when they are widely and reasonably used in the transport system. However, due to the feature of EV’s batteries, the charging problem plays an important role in the application of EVs. Fortunately, with the help of advanced technologies, charging stations powered by smart grid operators (SGOs) can easily and conveniently solve the problems and supply charging service to EV users. In this paper, we consider that EVs will be charged by charging station operators (CSOs) in heterogeneous networks (Hetnet), through which they can exchange the information with each other. Considering the trading relationship among EV users, CSOs, and SGOs, we design their own utility functions in Hetnet, where the demand uncertainty is taken into account. In order to maximize the profits, we formulate this charging problem as a four-stage Stackelberg game, through which the optimal strategy is studied and analyzed. In the Stackelberg game model, we theoretically prove and discuss the existence and uniqueness of the Stackelberg equilibrium (SE). Using the proposed iterative algorithm, the optimal solution can be obtained in the optimization problem. The performance of the strategy is shown in the simulation results. It is shown that the simulation results confirm the efficiency of the model in Hetnet.

Research and Improvement about LEACH Routing Protocol for Wireless Sensor Networks

2012 ◽  
Vol 241-244 ◽  
pp. 1028-1032
Author(s):  
Li Wang ◽  
Qi Lin Zhu
Keyword(s):  
Routing Protocol ◽  
Routing Algorithm ◽  
Cluster Head ◽  
Wireless Sensor ◽  
Cluster Head Selection ◽  
Selection Algorithm ◽  
Energy Factor ◽  
Random Cluster ◽  
Simulation Results ◽  
Node Energy

In recent years, as the development of wireless sensor network, people do some deep researches on cluster-based protocol, most around the prolongation of the lifetime of WSN and decline of energy consumed by the sensors. This paper analyses of classical clustering routing protocol based on LEACH, aiming at the node energy foot presents energy improved clustering routing algorithm, the random cluster head selection algorithm of threshold to be changed, lowering the threshold, in the original threshold increases the node's remaining energy factor, reduces the communication load of cluster nodes, and simulation. The simulation results show that the LEACH-E improved algorithm, energy saving, reducing balance node energy consumption, effectively prolongs the network lifetime.

scholarly journals Latency optimization for D2D-enabled parallel mobile edge computing in cellular networks

2021 ◽  
Vol 2021 (1) ◽  
Author(s):  
Yan Cai ◽  
Liang Ran ◽  
Jun Zhang ◽  
Hongbo Zhu
Keyword(s):  
Cellular Networks ◽  
Optimal Solution ◽  
Vital Role ◽  
Base Stations ◽  
Low Latency ◽  
Mobile Edge Computing ◽  
System Delay ◽  
Simulation Results ◽  
And Task ◽  
Parallel Communication

AbstractEdge offloading, including offloading to edge base stations (BS) via cellular links and to idle mobile users (MUs) via device-to-device (D2D) links, has played a vital role in achieving ultra-low latency characteristics in 5G wireless networks. This paper studies an offloading method of parallel communication and computation to minimize the delay in multi-user systems. Three different scenarios are explored, i.e., full offloading, partial offloading, and D2D-enabled partial offloading. In the full offloading scenario, we find a serving order for the MUs. Then, we jointly optimize the serving order and task segment in the partial offloading scenario. For the D2D-enabled partial offloading scenario, we decompose the problem into two subproblems and then find the sub-optimal solution based on the results of the two subproblems. Finally, the simulation results demonstrate that the offloading method of parallel communication and computing can significantly reduce the system delay, and the D2D-enabled partial offloading can further reduce the latency.

Fast satellite selection algorithm for GNSS multisystems based on the Sherman-Morrison formula

2021 ◽  
Author(s):  
Junpeng SHI ◽  
Kezhao LI ◽  
Lin CHAI ◽  
Lingfeng LIANG ◽  
Chengdong TIAN ◽  
...  
Keyword(s):  
Optimal Estimation ◽  
Observation Data ◽  
Selection Algorithm ◽  
Maximum Volume ◽  
Adaptive Function ◽  
Satellite Selection ◽  
Geometric Dilution Of Precision ◽  
Value Decomposition ◽  
Selection Algorithms ◽  
Usage Efficiency

Abstract The usage efficiency of GNSS multisystem observation data can be greatly improved by applying rational satellite selection algorithms. Such algorithms can also improve the real-time reliability and accuracy of navigation. By combining the Sherman-Morrison formula and singular value decomposition (SVD), a smaller geometric dilution of precision (GDOP) value method with increasing number of visible satellites is proposed. Moreover, by combining this smaller GDOP value method with the maximum volume of tetrahedron method, a new rapid satellite selection algorithm based on the Sherman-Morrison formula for GNSS multisystems is proposed. The basic idea of the algorithm is as follows: first, the maximum volume of tetrahedron method is used to obtain four initial reference satellites; then, the visible satellites are co-selected by using the smaller GDOP value method to reduce the GDOP value and improve the accuracy of the overall algorithm. By setting a reasonable precise threshold, the satellite selection algorithm can be autonomously run without intervention. The experimental results based on measured data indicate that (1) the GDOP values in most epochs over the whole period obtained with the satellite selection algorithm based on the Sherman-Morrison formula are less than 2. Furthermore, compared with the optimal estimation results of the GDOP for all visible satellites, the results of this algorithm can meet the requirements of high-precision navigation and positioning when the corresponding number of selected satellites reaches 13. Moreover, as the number of selected satellites continues to increase, the calculation time increases, but the decrease in the GDOP value is not obvious. (2) The algorithm includes an adaptive function based on the end indicator of the satellite selection calculation and the reasonable threshold. When the reasonable precise threshold is set to 0.01, the selected number of satellites in most epochs is less than 13. Furthermore, when the number of selected satellites reaches 13, the GDOP value is less than 2, and the corresponding probability is 93.54%. These findings verify that the proposed satellite selection algorithm based on the Sherman-Morrison formula provides autonomous functionality and high-accuracy results.

Sign in / Sign up

Export Citation Format

Share Document