scholarly journals Optimal Coverage Multi-Path Scheduling Scheme with Multiple Mobile Sinks for WSNs

2020 ◽  
Vol 62 (2) ◽  
pp. 695-711 ◽  
Author(s):  
Jin Wang ◽  
Yu Gao ◽  
Chang Zhou ◽  
R. Simon Sherratt ◽  
Lei Wang
Keyword(s):  
Mobile Sinks ◽  
Scheduling Scheme ◽  
Path Scheduling

scholarly journals A novel testability-oriented data path scheduling scheme in high-level synthesis

2007 ◽  
Vol 12 (S1) ◽  
pp. 134-138 ◽  
Author(s):  
Benmao Cheng ◽  
Hong Wang ◽  
Shiyuan Yang ◽  
Daoheng Niu ◽  
Yang Jin
Keyword(s):  
High Level Synthesis ◽  
Data Path ◽  
Scheduling Scheme ◽  
High Level ◽  
Path Scheduling

ESMO: An Energy-Efficient Mobile Node Scheduling Scheme for Sound Sensing

2010 ◽  
Vol E93-B (11) ◽  
pp. 2912-2924
Author(s):  
Tian HAO ◽  
Masayuki IWAI ◽  
Yoshito TOBE ◽  
Kaoru SEZAKI
Keyword(s):  
Energy Efficient ◽  
Mobile Node ◽  
Scheduling Scheme ◽  
Node Scheduling

Spatial-temporal data collection process models using mobile sinks

2019 ◽  
Vol 942 (12) ◽  
pp. 22-28
Author(s):  
A.V. Materuhin ◽  
V.V. Shakhov ◽  
O.D. Sokolova
Keyword(s):  
Energy Consumption ◽  
Operation Time ◽  
Point Of View ◽  
Process Models ◽  
Temporal Data ◽  
Network Nodes ◽  
Mobile Sinks ◽  
Autonomous Operation ◽  
Data Collection Process ◽  
Spatio Temporal

Optimization of energy consumption in geosensor networks is a very important factor in ensuring stability, since geosensors used for environmental monitoring have limited possibilities for recharging batteries. The article is a concise presentation of the research results in the area of increasing the energy consumption efficiency for the process of collecting spatio-temporal data with wireless geosensor networks. It is shown that in the currently used configurations of geosensor networks there is a predominant direction of the transmitted traffic, which leads to the fact that through the routing nodes that are close to the sinks, a much more traffic passes than through other network nodes. Thus, an imbalance of energy consumption arises in the network, which leads to a decrease in the autonomous operation time of the entire wireless geosensor networks. It is proposed to use the possible mobility of sinks as an optimization resource. A mathematical model for the analysis of the lifetime of a wireless geosensor network using mobile sinks is proposed. The model is analyzed from the point of view of optimization energy consumption by sensors. The proposed approach allows increasing the lifetime of wireless geosensor networks by optimizing the relocation of mobile sinks.

scholarly journals Day-Ahead and Intra-Day Optimal Scheduling of Integrated Energy System Considering Uncertainty of Source & Load Power Forecasting

Energies ◽  
2021 ◽  
Vol 14 (9) ◽  
pp. 2539
Author(s):  
Zhengjie Li ◽  
Zhisheng Zhang
Keyword(s):  
Wind Power ◽  
Demand Response ◽  
Solar Power ◽  
Load Forecasting ◽  
Energy System ◽  
Optimal Scheduling ◽  
Scheduling Scheme ◽  
Load Power ◽  
Integrated Energy System ◽  
Operation Cost

At present, due to the errors of wind power, solar power and various types of load forecasting, the optimal scheduling results of the integrated energy system (IES) will be inaccurate, which will affect the economic and reliable operation of the integrated energy system. In order to solve this problem, a day-ahead and intra-day optimal scheduling model of integrated energy system considering forecasting uncertainty is proposed in this paper, which takes the minimum operation cost of the system as the target, and different processing strategies are adopted for the model. In the day-ahead time scale, according to day-ahead load forecasting, an integrated demand response (IDR) strategy is formulated to adjust the load curve, and an optimal scheduling scheme is obtained. In the intra-day time scale, the predicted value of wind power, solar power and load power are represented by fuzzy parameters to participate in the optimal scheduling of the system, and the output of units is adjusted based on the day-ahead scheduling scheme according to the day-ahead forecasting results. The simulation of specific examples shows that the integrated demand response can effectively adjust the load demand and improve the economy and reliability of the system operation. At the same time, the operation cost of the system is related to the reliability of the accurate prediction of wind power, solar power and load power. Through this model, the optimal scheduling scheme can be determined under an acceptable prediction accuracy and confidence level.

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