scholarly journals Rate Maximization for Suspicious Multicast Communication Networks with Full-Duplex Proactive Monitoring

2020 ◽  
Vol 2020 ◽  
pp. 1-6
Author(s):  
Dongsheng Liu ◽  
Sai Zhao ◽  
Quanzhong Li ◽  
Jiayin Qin
Keyword(s):  
Communication Network ◽  
Communication Networks ◽  
Optimal Solution ◽  
Full Duplex ◽  
Multicast Communication ◽  
Multicast Networks ◽  
Rate Maximization ◽  
Local Optimal Solution ◽  
Global Optimal ◽  
Proactive Monitoring

In this paper, we investigate the optimization of the monitoring rate for a suspicious multicast communication network with a legitimate full-duplex (FD) monitor, where the FD monitor is proactive to jam suspicious receivers and eavesdrop from the suspicious transmitter simultaneously. To effectively monitor the suspicious communication over multicast networks, we maximize the monitoring rate under the outage probability constraint of the suspicious multicast communication network and the jamming power constraint at the FD monitor. The formulated optimization problem is nonconvex, and its global optimal solution is hard to obtain. Thus, we propose a constrained concave convex procedure- (CCCP-) based iterative algorithm, which is able to achieve a local optimal solution. Simulation results demonstrate that the proposed proactive eavesdropping scheme with optimal jamming power outperforms the conventional passive eavesdropping scheme.

AO-BBO: A Novel Optimization Algorithm and Its Application in Plant Drug Extraction

2019 ◽  
Vol 19 (2) ◽  
pp. 139-145 ◽  
Author(s):  
Bote Lv ◽  
Juan Chen ◽  
Boyan Liu ◽  
Cuiying Dong
Keyword(s):  
Optimization Algorithm ◽  
Learning Strategy ◽  
Optimal Solution ◽  
Population Diversity ◽  
Global Optimal Solution ◽  
Plant Medicine ◽  
Suitability Index ◽  
Sensing Model ◽  
Local Optimal Solution ◽  
Global Optimal

<P>Introduction: It is well-known that the biogeography-based optimization (BBO) algorithm lacks searching power in some circumstances. </P><P> Material & Methods: In order to address this issue, an adaptive opposition-based biogeography-based optimization algorithm (AO-BBO) is proposed. Based on the BBO algorithm and opposite learning strategy, this algorithm chooses different opposite learning probabilities for each individual according to the habitat suitability index (HSI), so as to avoid elite individuals from returning to local optimal solution. Meanwhile, the proposed method is tested in 9 benchmark functions respectively. </P><P> Result: The results show that the improved AO-BBO algorithm can improve the population diversity better and enhance the search ability of the global optimal solution. The global exploration capability, convergence rate and convergence accuracy have been significantly improved. Eventually, the algorithm is applied to the parameter optimization of soft-sensing model in plant medicine extraction rate. Conclusion: The simulation results show that the model obtained by this method has higher prediction accuracy and generalization ability.</P>

IoT-Based Management of Smart Microgrid

2019 ◽  
pp. 1-13
Author(s):  
Lipi Chhaya
Keyword(s):  
Communication Network ◽  
Internet Of Things ◽  
Smart Grid ◽  
Communication Networks ◽  
Alternative Energy ◽  
Power Grid ◽  
Energy Utilization ◽  
Full Duplex ◽  
Communication Infrastructure ◽  
Hierarchical Communication

The present power grid is going through a substantial and radical transformation process. Unification of existing electrical infrastructure with information and communication network is an unavoidable requirement of smart grid deployment and operation. The key characteristics of smart grid technology are full duplex communication, advanced metering infrastructure, integration of renewable and alternative energy resources, distribution automation and complete monitoring, as well as control of entire power grid. Smart grid communication infrastructure consists of varied and hierarchical communication networks. Application of smart grid can be realized in the various the facets of energy utilization. Internet of things also plays a pivotal role in smart grid infrastructure as it provides a ubiquitous communication network. This chapter describes an implementation of internet of things (IoT)-based wireless energy management system for smart microgrid communication infrastructure.

IoT-Based Management of Smart Microgrid

2022 ◽  
pp. 833-842
Author(s):  
Lipi Chhaya
Keyword(s):  
Communication Network ◽  
Internet Of Things ◽  
Smart Grid ◽  
Communication Networks ◽  
Alternative Energy ◽  
Power Grid ◽  
Energy Utilization ◽  
Full Duplex ◽  
Communication Infrastructure ◽  
Hierarchical Communication

The present power grid is going through a substantial and radical transformation process. Unification of existing electrical infrastructure with information and communication network is an unavoidable requirement of smart grid deployment and operation. The key characteristics of smart grid technology are full duplex communication, advanced metering infrastructure, integration of renewable and alternative energy resources, distribution automation and complete monitoring, as well as control of entire power grid. Smart grid communication infrastructure consists of varied and hierarchical communication networks. Application of smart grid can be realized in the various the facets of energy utilization. Internet of things also plays a pivotal role in smart grid infrastructure as it provides a ubiquitous communication network. This chapter describes an implementation of internet of things (IoT)-based wireless energy management system for smart microgrid communication infrastructure.

The Research on Modified K-Means Algorithm Based on GA&SA

2013 ◽  
Vol 347-350 ◽  
pp. 3242-3246
Author(s):  
Zhe Feng Zhu ◽  
Xiao Bin Hui ◽  
Yi Qian Cao ◽  
Wan Xiang Lian
Keyword(s):  
Local Search ◽  
Clustering Algorithm ◽  
Optimal Solution ◽  
Global Search ◽  
Local Optimization ◽  
Effective Algorithm ◽  
Global Optimal Solution ◽  
Local Optimal Solution ◽  
Global Optimal ◽  
Clustering Center

The traditional K-means clustering algorithm has the disadvantage of weakness in overall search, easily falling into local optimization, highly reliance on initial clustering center. Aiming at the drawback of falling into partial optimization, putting forward a modified K-means algorithm mixing GA and SA, which combined the advantages of global search ability of GA and local search, to avoid K-means algorithm to lost into local optimal solution. The results of simulation show that the performance of above-mentioned algorithm is better in the optimization capacity than before, and easier to get the global optimal solution. It is an effective algorithm.

scholarly journals In-Band Full-Duplex Relaying for SWIPT-Enabled Cognitive Radio Networks

Electronics ◽  
2020 ◽  
Vol 9 (5) ◽  
pp. 835
Author(s):  
Hieu V. Nguyen ◽  
Van-Dinh Nguyen ◽  
Oh-Soon Shin
Keyword(s):  
Cognitive Radio ◽  
Data Transmission ◽  
Optimal Solution ◽  
Low Complexity ◽  
Full Duplex ◽  
Primary System ◽  
Rate Maximization ◽  
Radio Systems ◽  
Sum Rate ◽  
Multiple Transmit

This paper studies sum rate maximization of a cognitive radio network, where a full-duplex relay (FDR) is considered to assist data transmission. An FDR equipped with multiple transmit/receive antennas is introduced to harvest energy from the radio frequency signal of the primary system to reuse the energy for its own data transmission. By exploiting the time-switching relaying protocol, we first formulate an optimization problem for the sum rate of primary and secondary receivers and then propose a low-complexity algorithm to find the optimal solution. Numerical results verify the effectiveness of the proposed technique for wireless information and power transfer in cognitive radio systems.

scholarly journals AGV optimal path planning based on improved ant colony algorithm

2018 ◽  
Vol 232 ◽  
pp. 03052 ◽  
Author(s):  
Chengwei He ◽  
Jian Mao
Keyword(s):  
Path Planning ◽  
Ant Colony Algorithm ◽  
Optimal Path ◽  
Optimal Solution ◽  
Ant Colony ◽  
Undirected Network ◽  
Optimal Path Planning ◽  
Local Optimal Solution ◽  
Global Optimal ◽  
Improved Ant Colony Algorithm

Using the traditional Ant Colony Algorithm for AGV path planning is easy to fall into the local optimal solution and lacking the capability of obstacle avoidance in the complex storage environment. In this paper, by constructing the MAKLINK undirected network routes and the heuristic function is optimized in the Ant Colony Algorithm, then the AGV path reaches the global optimal path and has the ability to avoid obstacles. According to research, the improved Ant Colony Algorithm proposed in this paper is superior to the traditional Ant Colony Algorithm in terms of convergence speed and the distance of optimal path planning.

Topological Optimization of Communication Networks by Modeling and Management of Information Flows

2016 ◽  
Vol 14 (2) ◽  
pp. 2-11
Author(s):  
K. Trichkov ◽  
E. Trichkova
Keyword(s):  
Communication Network ◽  
Fault Tolerance ◽  
Communication Networks ◽  
Optimal Solution ◽  
Topological Optimization ◽  
Type Star ◽  
Information Flows ◽  
Structural Improvement

Abstract This paper has a main goal which is to offer a topology synthesis through modelling and management of information flows. To proposes an optimal solution for changing the existing communication network from type “star” to a dual- or triple-connected topology. To proposes a model for quantifying the quality, the continuity and fault tolerance of services provided to achieve a technologic and structural improvement of the communication network.

Modeling of Well Service and Workover to Optimize Scheduling of Oil Well Maintenance

2016 ◽  
Vol 836 ◽  
pp. 311-316 ◽  
Author(s):  
Sudiyono Kromodihardjo ◽  
Ergo Swasono Kromodihardjo
Keyword(s):  
Optimal Solution ◽  
Simulation Software ◽  
High Rate ◽  
Oil Well ◽  
Well Production ◽  
Breakdown Time ◽  
Well Location ◽  
Local Optimal Solution ◽  
Global Optimal ◽  
Oil Company

Well maintenance (well service and workover) is an operation needed by oil company to guarantee the optimum productionof its oil well.Well maintenance is performed using large equipment called hydraulic workover unit (HWU-Rig) which is available in limited number. Scheduling sequence of the HWU-Rig to do well service must meet the goal of the maintenance that is to minimize the loss of oil well production due to well breakdown. Thus minimizing breakdown time of well with high rate production is a priority. However, scheduling secuence of the HWU-Rig to perform its task for few days ahead become complicated due to the numerous alternatives of secuence to choose. Each alternatives of sequence yields a certain production loss. Arbitrarily scheduling sequence may not yield the goal og minimizing the loss of well production. This research was done by analyzing workover scheduling system and data from Kondur Petroleum such as well location, well production rate, and service time needed to be performed on wells. Algorithm to create schedulling sequence was developed in the research. The algorithm was then implemented in discrete simulation software, and yield the result of absolute global optimal solution, near optimal solution and local optimal solution of the HWU scheduling problem.

scholarly journals Quasi-Affine Transformation Evolutionary with Double Excellent Guidance

2021 ◽  
Vol 2021 ◽  
pp. 1-15
Author(s):  
Tien-Wen Sung ◽  
Baohua Zhao ◽  
Xin Zhang
Keyword(s):  
Population Structure ◽  
Affine Transformation ◽  
Optimal Solution ◽  
Collaborative Optimization ◽  
Optimal Position ◽  
Mutation Strategy ◽  
Local Optimal Solution ◽  
Global Optimal ◽  
The Individual ◽  
Double Population

The Quasi-Affine Transformation Evolutionary (QUATRE) algorithm is a swarm-based collaborative optimization algorithm, which has drawn attention from researchers due to its simple structure, easy implementation, and powerful performance. However, it needs to be improved regarding the exploration, especially in the late stage of evolution, and the problem of easy falling into a local optimal solution. This paper proposes an improved algorithm named Quasi-Affine Transformation Evolutionary with double excellent guidance (QUATRE-DEG). The algorithm uses not only the global optimal solution but also the global suboptimal solution to guide the individual evolution. We establish a model to determine the guiding force by the distance between the global optimal position and the suboptimal position and propose a new mutation strategy through the double population structure. The optimization of population structure and the improvement of operation mechanisms bring more exploration for the algorithm. To optimize the algorithm, the experiments on parameter settings were made to determine the size of the subpopulation and to achieve a balance between exploration and development. The performance of QUATRE-DEG algorithm is evaluated under CEC2013 and CEC2014 test suites. Through comparison and analysis with some ABC variants known for their strong exploration ability and advanced QUATRE variants, the competitiveness of the proposed QUATRE-DEG algorithm is validated.

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