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Journal articles on the topic 'MOBILE SINK STRATEGY'

Author: Grafiati

Published: 11 September 2023

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1

Feiroz Khan, T. H., and D. Siva Kumar. "An obstacle aware mobile sink path strategy in WSN." Indonesian Journal of Electrical Engineering and Computer Science 15, no. 2 (2019): 879. http://dx.doi.org/10.11591/ijeecs.v15.i2.pp879-887.

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<span>In Wireless Sensor Networks, Mobile Sink accomplishes considerable achievement on network lifetime improvement. In sensing environment, more chances to present the obstacle. But, in the mobile sink, how to identify the obstacle and make the obstacle aware path strategy is a challenging task. To overcome this problem, we propose an Obstacle Aware Mobile sink Path Strategy (OAMPS) that detects any obstacles which enter within the network lifetime and design a shortest mobile sink movement path avoiding detected obstacles. In this scheme, the mobile sink collects the sensing data from

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2

Zheng, Li Li, Qiu Ling Tang, and Xian Li. "An Energy-Balanced Path Plan Strategy for Mobile Sensor Networks." Applied Mechanics and Materials 738-739 (March 2015): 65–69. http://dx.doi.org/10.4028/www.scientific.net/amm.738-739.65.

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Several studies have demonstrated that significant energy consumption reduction of nodes and network energy hole elimination can be achieved by introducing a mobile sink. In most related researches, mobile sink's energy is always assumed to be sufficient to collect data sensed by normal nodes. However, mobile sink consumes large amounts of energy in practical applications and it is impossible to own infinite energy. Correspondingly, the moving path plan of the mobile sink, which can be treated as a TSP (Travelling Salesman Problem), plays an important role in reducing and balancing network ene

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3

Basil Ghazi, Ahmed, Omar Adil Mahdi, and Wid Badee Abdulaziz. "Lightweight route adjustment strategy for mobile sink wireless sensor networks." Indonesian Journal of Electrical Engineering and Computer Science 21, no. 1 (2021): 313. http://dx.doi.org/10.11591/ijeecs.v21.i1.pp313-320.

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<span>As a result of numerous applications and low installation costs, wireless sensor networks (WSNs) have expanded excessively. The main concern in the WSN environment is to lower energy consumption amidst nodes while preserving an acceptable level of service quality. Using multi-mobile sinks to reduce the nodes' energy consumption have been considered as an efficient strategy. In such networks, the dynamic network topology created by the sinks mobility makes it a challenging task to deliver the data to the sinks. Thus, in order to provide efficient data dissemination, the sensor nodes

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4

Yang, Ying, Wude Yang, Huarui Wu, and Yisheng Miao. "A mobile sink–integrated framework for the collection of farmland wireless sensor network information based on a virtual potential field." International Journal of Distributed Sensor Networks 17, no. 7 (2021): 155014772110301. http://dx.doi.org/10.1177/15501477211030122.

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To overcome the limitations of traditional data collection methods in large-scale farmland wireless sensor network, in this study, we introduce a mobile sink and propose a virtual potential field-based strategy for mobile sink path planning. Virtual potential field-based strategy constructs a virtual field based on the residual energy, data generation rate, location information and cache urgency of nodes in the monitoring area. The stronger the virtual field, the more attractive it will be to mobile sink, which consequently affects the mobile path of sink node. Rendezvous points are selected i

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5

Mohapatra, Seli, Prafulla Kumar Behera, Prabodh Kumar Sahoo, et al. "Modified Ring Routing Protocol for Mobile Sinks in a Dynamic Sensor Network in Smart Monitoring Applications." Electronics 12, no. 2 (2023): 281. http://dx.doi.org/10.3390/electronics12020281.

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The stationary hierarchical network faces considerable challenges from hotspots and faster network breakdowns, especially in smart monitoring applications. As a solution to this issue, mobile sinks were recommended since they are associated with huge and balanced ways to transfer data and energy across the network. Again, due to the mobile sink node advertisement around the network latency and the energy utilization overheads introduced across the network, ring routing reduces the control overhead while preserving the benefits of the mobile sink, thereby optimizing the energy and improving the

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6

Bagais, Najla, Etimad Fadel, and Amal Al-Mansour. "An Efficient Path Planning Strategy in Mobile Sink Wireless Sensor Networks." Computers, Materials & Continua 73, no. 1 (2022): 1237–67. http://dx.doi.org/10.32604/cmc.2022.026070.

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7

Yin Tan, Lyk, Hock Guan Goh, Soung-Yue Liew, and Shen Khang Teoh. "An Energy-Efficient Mobile-Sink Path-Finding Strategy for UAV WSNs." Computers, Materials & Continua 67, no. 3 (2021): 3419–132. http://dx.doi.org/10.32604/cmc.2021.015402.

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8

Kancharla, Alekhya. "Load Balancing in Mobile Sink Path Strategy for Wireless Sensor Network." International Journal for Research in Applied Science and Engineering Technology 6, no. 6 (2018): 486–91. http://dx.doi.org/10.22214/ijraset.2018.6075.

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9

Yang, Guisong, Zhiwei Peng, and Xingyu He. "Data Collection Based on Opportunistic Node Connections in Wireless Sensor Networks." Sensors 18, no. 11 (2018): 3697. http://dx.doi.org/10.3390/s18113697.

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The working–sleeping cycle strategy used for sensor nodes with limited power supply in wireless sensor networks can effectively save their energy, but also causes opportunistic node connections due to the intermittent communication mode, which can affect the reliability of data transmission. To address this problem, a data collection scheme based on opportunistic node connections is proposed to achieve efficient data collection in a network with a mobile sink. In this scheme, the mobile sink first broadcasts a tag message to start a data collection period, and all nodes that receive this messa

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10

Liu, Yi, Yi Zhu, and Shu Yan. "The Research of Sink Mobile Strategy based on Gravitational Field in WSN." Research Journal of Applied Sciences, Engineering and Technology 5, no. 15 (2013): 3992–95. http://dx.doi.org/10.19026/rjaset.5.4466.

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11

Patil, Sunita S., and T. Senthil Kumaran. "Priority-based SenCar deployment strategy for mobile sink data gathering in WSN." International Journal of Internet Protocol Technology 15, no. 3/4 (2022): 161. http://dx.doi.org/10.1504/ijipt.2022.125967.

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12

Patil, Sunita S., and T. Senthil Kumaran. "Priority-based SenCar deployment strategy for mobile sink data gathering in WSN." International Journal of Internet Protocol Technology 15, no. 3/4 (2022): 161. http://dx.doi.org/10.1504/ijipt.2022.10051095.

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13

Liu, Honglei, Yunzhou Zhang, Huiyu Liu, and Xiaolin Su. "Inhomogeneous Distribution Strategy Based on Mobile Sink Nodes in Wireless Sensor Networks." Wireless Personal Communications 83, no. 1 (2015): 411–26. http://dx.doi.org/10.1007/s11277-015-2400-8.

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14

Salarian, Hamidreza, Kwan-Wu Chin, and Fazel Naghdy. "An Energy-Efficient Mobile-Sink Path Selection Strategy for Wireless Sensor Networks." IEEE Transactions on Vehicular Technology 63, no. 5 (2014): 2407–19. http://dx.doi.org/10.1109/tvt.2013.2291811.

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15

Lin, Zhi Gui, Hui Qi Zhang, Xu Yang Wang, Fang Qin Yao, and Zhen Xing Chen. "Energy-Efficient Routing Protocol on Mobile Sink in Wireless Sensor Network." Advanced Materials Research 787 (September 2013): 1050–55. http://dx.doi.org/10.4028/www.scientific.net/amr.787.1050.

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To the disadvantages, such as high energy consumption and the energy consumption imbalance, we proposed an energy-efficient routing protocol on mobile sink (MSEERP) in this paper. In the MSEERP, the network is divided into several square virtual grids based on GAF, each grid is called a cluster, and the cluster head election method of GAF is improved. In addition, the MSEERP introduces a mobile sink in the network, the sink radios in limited number of hops and uses control moving strategy, namely the sink does not collect the information until it moves to a cluster with highest residual energy

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16

D. Aljubaily, Mohammed, and Imad Alshawi. "Energy sink-holes avoidance method based on fuzzy system in wireless sensor networks." International Journal of Electrical and Computer Engineering (IJECE) 12, no. 2 (2022): 1776. http://dx.doi.org/10.11591/ijece.v12i2.pp1776-1785.

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The existence of a mobile sink for gathering data significantly extends wireless sensor networks (WSNs) lifetime. In recent years, a variety of efficient rendezvous points-based sink mobility approaches has been proposed for avoiding the energy sink-holes problem nearby the sink, diminishing buffer overflow of sensors, and reducing the data latency. Nevertheless, lots of research has been carried out to sort out the energy holes problem using controllable-based sink mobility methods. However, further developments can be demonstrated and achieved on such type of mobility management system. In t

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17

Wu, Xiaofeng, Zhuangqi Chen, Yi Zhong, Hui Zhu, and Pingjian Zhang. "End-to-end data collection strategy using mobile sink in wireless sensor networks." International Journal of Distributed Sensor Networks 18, no. 3 (2022): 155013292210779. http://dx.doi.org/10.1177/15501329221077932.

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Several data collection algorithms, which are based on the combination of using mobile sinks and multiple-hop forwarding, have been proposed to prolong the network lifetime of wireless sensor networks. However, most approaches treat the collection point selection and touring path planning as two independent problems, which leads to a sub-optimal solution for data collection. This article proposed an ant colony optimization based end-to-end data collection strategy to perform the collection point selection and the touring path planning simultaneously. The proposed algorithm first constructs a d

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18

Zhang, Ling, and Cheng Wan. "Dynamic Path Planning Design for Mobile Sink with Burst Traffic in a Region of WSN." Wireless Communications and Mobile Computing 2019 (February 3, 2019): 1–8. http://dx.doi.org/10.1155/2019/2435712.

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In mobile wireless sensor networks, priori-trail planning for the mobile sink is a commonly used solution to data collection from the whole network, for its low protocol overhead. However, these trail-based approaches lack efficient load balance mechanism to handle burst WSN traffic, which needs to be sent to the base station correctly with low delay. This paper proposed a dynamic path planning for mobile sink to balance load and avoid traffic bottleneck. It contains grid partition of the network, priori-trail creation, burst-traffic awareness and estimation, resources collaborative strategy,

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19

Tang, Xiaofeng, and Li Xie. "Data Collection Strategy in Low Duty Cycle Wireless Sensor Networks with Mobile Sink." International Journal of Communications, Network and System Sciences 10, no. 05 (2017): 227–39. http://dx.doi.org/10.4236/ijcns.2017.105b023.

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20

Park, Soochang, Euisin Lee, Min-Sook Jin, and Sang-Ha Kim. "Novel strategy for data dissemination to mobile sink groups in wireless sensor networks." IEEE Communications Letters 14, no. 3 (2010): 202–4. http://dx.doi.org/10.1109/lcomm.2010.03.092001.

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21

Lee, Keontaek, Young-Hun Kim, Hak-Jin Kim, and Seungjae Han. "A myopic mobile sink migration strategy for maximizing lifetime of wireless sensor networks." Wireless Networks 20, no. 2 (2013): 303–18. http://dx.doi.org/10.1007/s11276-013-0606-9.

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22

Chauhan, Vinith, and Surender Soni. "Mobile sink-based energy efficient cluster head selection strategy for wireless sensor networks." Journal of Ambient Intelligence and Humanized Computing 11, no. 11 (2019): 4453–66. http://dx.doi.org/10.1007/s12652-019-01509-6.

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23

Zeng, Xia Ling. "Coverage Control Strategy for Mobile Sensor Network Based on Voronoi Division." Applied Mechanics and Materials 602-605 (August 2014): 3278–81. http://dx.doi.org/10.4028/www.scientific.net/amm.602-605.3278.

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According to the multilayer sensor network structure of mobile nodes, proposing a coverage optimization control policy based on voronoi division. Based on the mobile policy of Sink nodes by the voronoi division, the essay proposes a coverage optimization control algorithm (COCA) based on coverage hole calculating to optimize the initial random deployment of sensor nodes, and then to eliminate coverage holes and improve the coverage performance of network. Simulation results show that, compared with the random deployed network, the COCA algorithm only requires fewer nodes to achieve a higher co

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24

Benting Wan. "The Maximum Lifetime Optimization Strategy of Linear Wireless Sensor Networks Based on Mobile Sink." Journal of Convergence Information Technology 6, no. 9 (2011): 396–402. http://dx.doi.org/10.4156/jcit.vol6.issue9.46.

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25

Qian, Lanmei, Haifei Zhang, Jianlin Qiu, Xudong Zhang, Hassan Fouad, and Torki Altameem. "Mobile Multiple Sink Path Planning for Large-Scale Sensor Networks Based on Hyper-Heuristic Artificial Bee Colony Algorithm." Journal of Nanoelectronics and Optoelectronics 18, no. 3 (2023): 329–37. http://dx.doi.org/10.1166/jno.2023.3400.

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Large-scale wireless sensor networks consists a terrific amount of nodes, a wide range of deployment, extended data transmission time, and large network energy consumption. To solve the above problems, a mobile multiple Sink path planning based on hyper-heuristic artificial bee colony algorithm is proposed. The artificial bee colony algorithm is used as the high-level strategy. In view of the changes in the network operation process, namely the number of nodes and energy changes, the design of three stages of the artificial bee colony algorithm is used to choose and manipulate the low-level he

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26

Yue, Yinggao, Li Cao, Bo Hang, and Zhongqiang Luo. "A Swarm Intelligence Algorithm for Routing Recovery Strategy in Wireless Sensor Networks With Mobile Sink." IEEE Access 6 (2018): 67434–45. http://dx.doi.org/10.1109/access.2018.2879364.

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27

Lu, Yong, Na Sun, and Xiuqin Pan. "Mobile Sink-Based Path Optimization Strategy in Wireless Sensor Networks Using Artificial Bee Colony Algorithm." IEEE Access 7 (2019): 11668–78. http://dx.doi.org/10.1109/access.2018.2885534.

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28

Li, Xian, Qiuling Tang, and Changyin Sun. "Energy efficient dispatch strategy for the dual-functional mobile sink in wireless rechargeable sensor networks." Wireless Networks 24, no. 3 (2016): 671–81. http://dx.doi.org/10.1007/s11276-016-1363-3.

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29

Chunxiao, Zhao, and Guo Junjie. "Autonomy-oriented proximity mobile social network modeling in smart city for emergency rescue." International Journal of Distributed Sensor Networks 17, no. 12 (2021): 155014772110612. http://dx.doi.org/10.1177/15501477211061252.

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Nearest neighbor mobile social network means that movers approaching in position communicate through their social sensors, which is called Proximity Mobile Social Network. Proximity Mobile Social Network can provide more social and business opportunities for users. To carry out disaster relief work in post-disaster environment, we need to collect incident information during the search process and report to the sink in time. Proximity Mobile Social Network provides flexible systems for emergency handling and disaster relief. Therefore, how to find a better data forwarding and routing strategy i

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30

Ma, Yu Fang, and Yan Li Wang. "Sink Mobility Based and Energy Balancing Routing Protocol." Applied Mechanics and Materials 380-384 (August 2013): 2177–82. http://dx.doi.org/10.4028/www.scientific.net/amm.380-384.2177.

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In the wireless sensor network routing protocol design, the sensor node monitoring data in multi-hop relay approach to sink node for transmission. For sink aggregation node fixed network, the nearby sink nodes of sensor nodes need to transfer other nodes of the monitoring data, consequently, it consumes large amounts of energy, and it's easy to premature death, making the network connectivity decline, even making the network intersected, shorten the lifetime of the network. In order to solve this problem, from the view of sink node, this thesis brings forward a protocol of SERP, which is a ene

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31

Zhu, Chuan, Sai Zhang, Guangjie Han, Jinfang Jiang, and Joel Rodrigues. "A Greedy Scanning Data Collection Strategy for Large-Scale Wireless Sensor Networks with a Mobile Sink." Sensors 16, no. 9 (2016): 1432. http://dx.doi.org/10.3390/s16091432.

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32

Sha, Chao, Dandan Song, Rui Yang, Hancheng Gao, and Haiping Huang. "A Type of Energy-Balanced Tree Based Data Collection Strategy for Sensor Network With Mobile Sink." IEEE Access 7 (2019): 85226–40. http://dx.doi.org/10.1109/access.2019.2924919.

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33

Zhou, Shuchen, Waqas Jadoon, and Iftikhar Ahmed Khan. "Computing Offloading Strategy in Mobile Edge Computing Environment: A Comparison between Adopted Frameworks, Challenges, and Future Directions." Electronics 12, no. 11 (2023): 2452. http://dx.doi.org/10.3390/electronics12112452.

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With the proliferation of the Internet of Things (IoT) and the development of wireless communication technologies such as 5G, new types of services are emerging and mobile data traffic is growing exponentially. The mobile computing model has shifted from traditional cloud computing to mobile edge computing (MEC) to ensure QoS. The main feature of MEC is to “sink” network resources to the edge of the network to meet the needs of delay-sensitive and computation-intensive services, and to provide users with better services. Computation offloading is one of the major research issues in MEC. In thi

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34

Zhang, Shun-Miao, Sheng-Bo Gao, Thi-Kien Dao, et al. "An Analysis Scheme of Balancing Energy Consumption with Mobile Velocity Control Strategy for Wireless Rechargeable Sensor Networks." Sensors 20, no. 16 (2020): 4494. http://dx.doi.org/10.3390/s20164494.

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Wireless Rechargeable Sensor Networks (WRSN) are not yet fully functional and robust due to the fact that their setting parameters assume fixed control velocity and location. This study proposes a novel scheme of the WRSN with mobile sink (MS) velocity control strategies for charging nodes and collecting its data in WRSN. Strip space of the deployed network area is divided into sub-locations for variant corresponding velocities based on nodes energy expenditure demands. The points of consumed energy bottleneck nodes in sub-locations are determined based on gathering data of residual energy and

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35

Naganjaneyulu, P. V., D. N. Rao, and V. T. Venkateswarlu. "Rendezvous agents-based routing protocol for delay sensitive data transmission over wireless sensor networks with mobile sink." International Journal of Intelligent Enterprise 7, no. 1/3 (2020): 338. http://dx.doi.org/10.1504/ijie.2020.10026355.

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36

Venkateswarlu, V. T., P. V. Naganjaneyulu, and D. N. Rao. "Rendezvous agents-based routing protocol for delay sensitive data transmission over wireless sensor networks with mobile sink." International Journal of Intelligent Enterprise 7, no. 1/2/3 (2020): 338. http://dx.doi.org/10.1504/ijie.2020.104665.

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37

Yalçın, Sercan, and Ebubekir Erdem. "Bacteria Interactive Cost and Balanced-Compromised Approach to Clustering and Transmission Boundary-Range Cognitive Routing In Mobile Heterogeneous Wireless Sensor Networks." Sensors 19, no. 4 (2019): 867. http://dx.doi.org/10.3390/s19040867.

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The improvement of stable, energy-efficient mobile-based clustering and routing protocols in wireless sensor networks (WSNs) has become indispensable so as to develop large-scale, versitale, and adaptive applications. Data is gathered more efficiently and the total path length is shortened optimally by means of mobile sink (MS). Two algorithms as bacterial interaction based cluster head (CH) selection and energy and transmission boundary range cognitive routing algorithm with novel approach for heterogeneous mobile networks are proposed in this study. The more reliable and powerful CH selectio

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38

Chao, Fan, Zhiqin He, Renkuan Feng, et al. "Predictive Trajectory-Based Mobile Data Gathering Scheme for Wireless Sensor Networks." Complexity 2021 (January 5, 2021): 1–17. http://dx.doi.org/10.1155/2021/3941074.

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Tradition wireless sensor networks (WSNs) transmit data by single or multiple hops. However, some sensor nodes (SNs) close to a static base station forward data more frequently than others, which results in the problem of energy holes and makes networks fragile. One promising solution is to use a mobile node as a mobile sink (MS), which is especially useful in energy-constrained networks. In these applications, the tour planning of MS is a key to guarantee the network performance. In this paper, a novel strategy is proposed to reduce the latency of mobile data gathering in a WSN while the rout

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39

Bendjima, Mostefa, Mohammed Feham, and Mohamed Lehsaini. "Directional Itinerary Planning for Multiple Mobile Agents in Wireless Sensor Networks." Wireless Communications and Mobile Computing 2021 (July 8, 2021): 1–13. http://dx.doi.org/10.1155/2021/5584581.

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Currently, the majority of research in the area of wireless sensor networks (WSNs) is directed towards optimizing energy use during itinerary planning by mobile agents (MAs). The route taken by the MA when migrating can get a significant effect on energy consumption and the lifespan of the network. Conversely, finding an ideal arrangement of Source Nodes (SNs) for mobile agents to visit could be a problematic issue. It is within this framework that this work focused on solving certain problems related to itinerary planning based on a multimobile agent (MMA) strategy in networks. The objective

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40

Sadia Batool and Mohtishim Siddique. "Energy Efficient Schemes for Wireless Sensor Network (WSN)." Lahore Garrison University Research Journal of Computer Science and Information Technology 1, no. 1 (2017): 54–61. http://dx.doi.org/10.54692/lgurjcsit.2017.01016.

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Conservation of energy is the main design issue in wirelesssensor network (WSN) which is usually available at each node. Althoughdifferent solutions have been introduced for typical wireless networks,cellular networks, MANET, and other short-range wireless local areanetworks, yet they are not often much feasible for a large scale WSN.For this purpose, multiple mobile sink nodes can be deployed to increasethe life of sensor network. The purpose can be achieved by splitting thelife time into equal time interval known as rounds. Similarly, byemploying multiple sink nodes can also make the sensor

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41

Gul, Omer Melih, and Aydan Muserref Erkmen. "Energy-Efficient Cluster-Based Data Collection by a UAV with a Limited-Capacity Battery in Robotic Wireless Sensor Networks." Sensors 20, no. 20 (2020): 5865. http://dx.doi.org/10.3390/s20205865.

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In this work, our motivation focuses on an energy-efficient data collection problem by a mobile sink, an unmanned aerial vehicle (UAV) with limited battery capacity, in a robot network divided into several robot clusters. In each cluster, a cluster head (CH) robot allocates tasks to the remaining robots and collects data from them. Our contribution is to minimize the UAV total energy consumption coupled to minimum cost data collection from CH robots by visiting optimally a portion of the CH robots. The UAV decides the subset of CH robots to visit by considering not only the locations of all CH

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42

Zhang, Zhongmei, Zhongguo Yang, Sikandar Ali, Muhammad Asshad, and Shaher Suleman Slehat. "A Dynamic Declarative Composition Scheme for Stream Data Services." Mobile Information Systems 2021 (October 12, 2021): 1–8. http://dx.doi.org/10.1155/2021/2502083.

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With the fast development of Sensor Network, Internet of Things, mobile devices, and pervasive computing, enormous amounts of sensor devices are deployed in physical world. Data streams produced by these sensor devices, deployed broadly, can be used to create various value-added applications. Facing continuous, real-time, high-frequency, low-valued data streams, how to flexibly and efficiently cooperate them for creating valuable application is very crucial. In this study, we propose a service-oriented manner to realize flexible streams integration. It considers data stream produced by one sen

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43

Zhang, Zhenzhong, Wei Sun, and Yanliang Yu. "Research on Intelligent Scheduling Mechanism in Edge Network for Industrial Internet of Things." Security and Communication Networks 2022 (January 5, 2022): 1–14. http://dx.doi.org/10.1155/2022/5358873.

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With the vigorous development of the Internet of Things, the Internet, cloud computing, and mobile terminals, edge computing has emerged as a new type of Internet of Things technology, which is one of the important components of the Industrial Internet of Things. In the face of large-scale data processing and calculations, traditional cloud computing is facing tremendous pressure, and the demand for new low-latency computing technologies is imminent. As a supplementary expansion of cloud computing technology, mobile edge computing will sink the computing power from the previous cloud to a netw

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44

Alanezi, Mohammed A., Abdulazeez F. Salami, Yusuf A. Sha’aban, et al. "UBER: UAV-Based Energy-Efficient Reconfigurable Routing Scheme for Smart Wireless Livestock Sensor Network." Sensors 22, no. 16 (2022): 6158. http://dx.doi.org/10.3390/s22166158.

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This paper addresses coverage loss and rapid energy depletion issues for wireless livestock sensor networks by proposing a UAV-based energy-efficient reconfigurable routing (UBER) scheme for smart wireless livestock sensor networking applications. This routing scheme relies on a dynamic residual energy thresholding strategy, robust cluster-to-UAV link formation, and UAV-assisted network coverage and recovery mechanism. The performance of UBER was evaluated using low, normal and high UAV altitude scenarios. Performance metrics employed for this analysis are network stability (NST), load balanci

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45

Nyomora, Agnes M. S., Patrick H. Brown, and M. Freeman. "Fall Foliar-applied Boron Increases Tissue Boron Concentration and Nut Set of Almond." Journal of the American Society for Horticultural Science 122, no. 3 (1997): 405–10. http://dx.doi.org/10.21273/jashs.122.3.405.

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Fruit set is the major determinant of productivity in almond [Prunus dulcis (Mill D.A. Webb)] where seed is the commercial product. Boron influences flowering and fruit set in a number of crops, but little has been reported on this subject in almond. Here, we investigated the effect of a fall foliar application of B on fruit set and tissue B concentration in open pollinated `Butte' and `Mono' almond over a 2-year period. Early fall B application significantly increased the vegetative, floral, and fruit tissue B concentration in the subsequent year. The greatest increase in organ B concentratio

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46

Bi, Yanzhong, Limin Sun, and Na Li. "BoSS: a moving strategy for mobile sinks in wireless sensor networks." International Journal of Sensor Networks 5, no. 3 (2009): 173. http://dx.doi.org/10.1504/ijsnet.2009.026365.

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47

Al-Kaseem, Bilal R., Zahraa K. Taha, Sarah W. Abdulmajeed, and Hamed S. Al-Raweshidy. "Optimized Energy – Efficient Path Planning Strategy in WSN With Multiple Mobile Sinks." IEEE Access 9 (2021): 82833–47. http://dx.doi.org/10.1109/access.2021.3087086.

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48

Huang, Zhi, Sanyang Liu, and Xiaogang Qi. "A Genetic Algorithm Based Strategy for Mobile Sinks in Wireless Sensor Networks." Advanced Science Letters 4, no. 11 (2011): 3528–36. http://dx.doi.org/10.1166/asl.2011.1905.

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49

Liu, Xiang, Xu Zhao, Guojin Liu, Fei Huang, Tiancong Huang, and Yucheng Wu. "Collaborative Task Offloading and Service Caching Strategy for Mobile Edge Computing." Sensors 22, no. 18 (2022): 6760. http://dx.doi.org/10.3390/s22186760.

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Mobile edge computing (MEC), which sinks the functions of cloud servers, has become an emerging paradigm to solve the contradiction between delay-sensitive tasks and resource-constrained terminals. Task offloading assisted by service caching in a collaborative manner can reduce delay and balance the edge load in MEC. Due to the limited storage resources of edge servers, it is a significant issue to develop a dynamical service caching strategy according to the actual variable user demands in task offloading. Therefore, this paper investigates the collaborative task offloading problem assisted b

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Yang, Luxian, Qing He, Liu Yang, and Shihang Luo. "A Fusion Multi-Strategy Marine Predator Algorithm for Mobile Robot Path Planning." Applied Sciences 12, no. 18 (2022): 9170. http://dx.doi.org/10.3390/app12189170.

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Abstract:

Path planning is a key technology currently being researched in the field of mobile robotics, but traditional path planning algorithms have complex search spaces and are easily trapped in local minima. To solve the above problems and obtain the global optimal path of the mobile robot, a fusion multi-strategy marine predator algorithm (FMMPA) is proposed in this paper. The algorithm uses a spiral complex path search strategy based on Archimedes’ spiral curve for perturbation to expand the global exploration range, enhance the global search ability of the population and strengthen the steadiness

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