Статті в журналах: "MOBILE SINK STRATEGY"

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 (August 1, 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 the super node then it sends the data to the base station. Here, static or moving obstacles are present when the mobile sink moves the path scheduling by spanning graph. This algorithm is introduced to discovering the obstacle avoiding shortest path. The source selects the route by the updated cuckoo search algorithm. The simulation results show that the OAMPS improved the throughput and minimized the delay in the network.</span>

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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 energy consumption. In this paper, an energy efficient mobile sink path planning strategy (EEPP) is proposed. In this strategy, LEACH protocol is introduced to balance the static network energy consumption; A heuristic path optimization method is utilized to further shorten the mobile sink path and reduce network latency. Simulation results show that our algorithm has good performance on the network energy consumption balancing, thus extending the network lifetime.

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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 (January 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 will have to readjust the routes to the current position of the mobile sinks. The route re-adjustment process could result in a significant maximization in the communication cost, which boosts the total energy depletion. This paper proposes a lightweight routes re-adjustment strategy for mobile sink wireless sensor networks (LRAS-MS) aimed at minimizing communication cost and energy consumption by reducing route re-adjustment in a cluster-based WSN environment. The simulation results show a significant reduction in communication costs and extending the network lifetime while maintaining comparable low data delivery delay. </span>

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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 (July 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 in accordance with the maximum-farthest criterion, and the shortest path connecting all rendezvous points is taken as the mobile path of sink. Furthermore, the monitoring nodes employ the distance probability transmission strategy to have the transmission moment selected and the energy consumption optimized with reference to the path control information sent by the sink. The virtual potential fields and the rendezvous points are recalculated periodically according to the dynamic changes of both the node residual energy and the real-time cache. The simulation results showed that excellent transmission efficiency and network lifetime, and the combination of virtual potential field-based strategy and distance probability transmission strategy can have the fairness and real time of nodes guaranteed, thus it may meet the needs of large-scale farmland data collection.

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5

Mohapatra, Seli, Prafulla Kumar Behera, Prabodh Kumar Sahoo, Manoj Kumar Ojha, Chetan Swarup, Kamred Udham Singh, Saroj Kumar Pandey, Ankit Kumar, and Anjali Goswami. "Modified Ring Routing Protocol for Mobile Sinks in a Dynamic Sensor Network in Smart Monitoring Applications." Electronics 12, no. 2 (January 5, 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 network life span. Consequently, we suggested a novel, distributed advanced ring routing strategy, in this work, for the mobile wireless sensor network. Extensive simulations and performance evaluation, in comparison to previous distributed mobile approaches, reveal a 37% and 40% boost in the network throughput and end-to end delay, respectively. Additionally, the lifespan of a network is determined by the control overhead and energy demand.

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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 (June 30, 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 (October 30, 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 message will use the probe message to forward their own source information to the mobile sink. On receiving these probe messages, the mobile sink then constructs an opportunistic connection random graph by analyzing the source information included in them, and calculates the optimal path from itself to each node in this random graph, therefore a spanning tree could be generated with the mobile sink play as the root node, finally, it broadcasts this spanning tree so that each node could obtain an optimal path from itself to the mobile sink to forward the sensing data. In addition, a routing protocol that adapts to different nodes operating statuses is proposed to improve the reliability of data transmission. Simulation results show that the proposed scheme works better concerning the packet delivery rate, energy consumption and network lifetime.

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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 (April 25, 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 (February 27, 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 (June 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. We applied NS2 to evaluate its performance and analyze the simulation results by the energy model. Simulation results show that the MSEERP balances the energy consumption of the network, saves nodes energy and extends the network lifetime.

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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 (April 1, 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 this paper, a well-rounded strategy involving an energy-efficient routing protocol along with a controllable-based sink mobility method is proposed to extirpate the energy sink-holes problem. This paper fused the fuzzy A-star as a routing protocol for mitigating the energy consumption during data forwarding along with a novel sink mobility method which adopted a grid partitioning system and fuzzy system that takes account of the average residual energy, sensors density, average traffic load, and sources angles to detect the optimal next location of the mobile sink. By utilizing diverse performance metrics, the empirical analysis of our proposed work showed an outstanding result as compared with fuzzy A-star protocol in the case of a static sink.

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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 (March 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 data-forwarding tree, and then heuristically selects collection points and plans a touring path at the same time. The performance evaluation shows that the end-to-end strategy can improve the network lifetime of wireless sensor network compared to other approaches, especially in the unbalanced distribution scenario of sensors. The end-to-end strategy is also capable of being integrated with other methods.

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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, and dynamic routing adjustment. Experiments on NS-2 platform show that the proposed algorithm can efficiently balance the regular and burst data traffic with a low-delay and low loss rate performance of the network.

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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 (March 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 (June 4, 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 (October 8, 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 coverage ratio and to maintain in low energy consumption, which embodies optimum performance of the network deployment.

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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 (September 30, 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 (March 1, 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 heuristic operator. The selected lower layer operator set plans the path of each mobile sink nodes. Compared with other famous meta-heuristic algorithms, it is proved that the proposed hyper-heuristic algorithm is an effective, efficient and robust algorithm, which can effectively solve the path planning problem in view of multiple sink nodes, reduce network delay and reduce network energy consumption.

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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 (September 1, 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 (December 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 is the key problem of post-disaster rescue, and the research of user mobility model is the basis of the above problems. This article presents an Autonomy-Oriented Proximity Mobile Social Network modeling for emergency rescue in smart city, which simulates the network operating environment. First, we verify the performance of Autonomy-Oriented Proximity Mobile Social Network model in terms of self-organization, scale-free, aggregation, and community structure. Then, the rescue efficiency is discussed through the coverage of mobile sensors. Finally, performance of the routing strategy based on Autonomy-Oriented Proximity Mobile Social Network model is analyzed, and the effectiveness of the method is proved.

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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 energy balancing routing protocol based on sink Mobility and prolongs the lifetime of network. It adopts the strategy of sink movement which makes the hot nodes inside the network take turns, balances the load among them. In SERP, firstly, the WSN deployment area is divided into finite Virtual cells ;Secondly ,we make the center of each virtual cell as the mobile position of sink node; at last, we confirm the residence time when sink node stays in each position through linear programming. Finally, the paper makes simulation al analysis aiming at above-mentioned routing protocols . The result shows that the inside node energy consumption is comparatively balanced and efficient, and the network lifetime is prolonged effectively.

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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 (September 6, 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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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 (May 29, 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 this paper, we summarize the state of the art in task offloading in MEC. First, we introduce the basic concepts and typical application scenarios of MEC, and then we formulate the task offloading problem. In this paper, we analyze and summarize the state of research in the industry in terms of key technologies, schemes, scenarios, and objectives. Finally, we provide an outlook on the challenges and future research directions of computational offloading techniques and indicate the suggested direction of follow-up research work.

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34

Zhang, Shun-Miao, Sheng-Bo Gao, Thi-Kien Dao, De-Gen Huang, Jin Wang, Hong-Wei Yao, Osama Alfarraj, and Amr Tolba. "An Analysis Scheme of Balancing Energy Consumption with Mobile Velocity Control Strategy for Wireless Rechargeable Sensor Networks." Sensors 20, no. 16 (August 11, 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 expenditure of nodes. A minimum reliable energy balanced spanning tree is constructed based on data collection to optimize the data transmission paths, balance energy consumption, and reduce data loss during transmission. Experimental results are compared with the other methods in the literature that show that the proposed scheme offers a more effective alternative in reducing the network packet loss rate, balancing the nodes’ energy consumption, and charging capacity of the nodes than the competitors.

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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 (February 19, 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 selection is made with the greedy approach that is based on the interaction fitness value, energy node degree, and distance to adjacent nodes in a compromised manner. The best trajectories, thanks to intersection edge points of the visited CHs, are obtained in the proposed routing algorithm. In this way, the MS entry to transmission range boundaries of the CH has been a sufficient strategy to collect information. As in energy model, we adopt energy consumption costs of listening and sensing channel as well as transmit and receive costs. Comprehensive performance analyzes have been seriously carried out via the Matlab 2016a environment. We validate that the proposed scheme outperforms existing studies in terms of several performance metrics as simulations.

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38

Chao, Fan, Zhiqin He, Renkuan Feng, Xiao Wang, Xiangping Chen, Changqi Li, and Ying Yang. "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 routing strategies and tour planning of MS are jointly optimized. First, the issue of network coverage is discussed before the appropriate number of clusters being calculated. A dynamic clustering scheme is then developed where a virtual cluster center is defined as the MS sojourn for data collection. Afterwards, a tour planning of MS based on prediction is proposed subject to minimizing the traveling distance to collect data. The proposed method is simulated in a MATLAB platform to show the overall performance of the developed system. Furthermore, the physical tests on a test rig are also carried out where a small WSN based on an unmanned aerial vehicle (UAV) is developed in our laboratory. The test results validate the feasibility and effectiveness of the method proposed.

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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 of our research was to increase the lifespan of sensor networks and to diminish the length of the data collection task. In order to achieve our objective, we proposed a new approach in WSNs, which took into consideration the criterion of an appropriate number of MAs, the criterion of the appropriate grouping of SNs, and finally the criterion of the optimal itinerary followed by each MA to visit all its SNs. Thus, we suggested an approach that may be classified as a centralized planning model where the itinerary schedule is entirely shaped by the base station (sink) which, unlike other approaches, is no longer constrained by energy consumption. A series of simulations to measure the performance of the new planning process was also carried out.

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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 (March 31, 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 network moreenergy efficient. Another way to make the sensor network energyefficient is to logically divide the deployment area into static clusters. Byadopting the strategy of static cluster, energy consumption can beminimized. The two major wireless standards used by WSN are 802.15.4and Zigbee [1],[2] .They are low-power protocols. Maximum distance isaround 100m (at 2.4 GHz). However, performance is an issue. In orderto assure the Wireless sensor network (WSN)s survivability and increasethe lifetime of network in such environments, various energy efficiencyschemes have been proposed in the literature. Energy is a valuablecommodity in wireless networks due to the limited battery of the handydevices. The energy problem becomes stiffer in ad-hoc WSN).

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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 (October 16, 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 robots but also its battery capacity. If the UAV cannot visit all CH robots, then the CH robots not visited by the UAV transmit their data to another CH robot to forward it. The decision of transmission paths of transmitting robots is included in the cost optimization. Our contribution passes beyond the existing paradigms in the literature by considering the constant battery capacity for the UAV. We derive the optimal approach analytically for this problem. For various numbers of clusters, the performance of our strategy is compared with the approach in the close literature in terms of total energy consumed by CH robots, which affects network lifetime. Numerical results demonstrate that our strategy outperforms the approach in the close literature.

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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 sensor data as a stream data service and utilizes composing multiple services to realize the cooperation among sensor devices. Firstly, we propose a stream data service model based on Event-Condition-Action rules, which can encapsulate steam data as services and continuously and timely process stream data into value-added events. Then, we propose a declarative method which can dynamically compose stream data services. Based on two kinds of declarative rules, that is, sink-rules and connect-rules, multiple data streams can be dynamically integrated through flexible service composition. To ensure the performance of service composition, we also employ a sensor partition strategy and process multiple service compositions in parallel. Through comprehensive evaluations by experiments, our service composition method shows both good efficiency and effectiveness.

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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 network edge node. Through the mutual cooperation between computing nodes, the number of nodes that can be calculated is more, the types are more comprehensive, and the computing range is even greater. Broadly, it makes up for the shortcomings of cloud computing technology. Although edge computing technology has many advantages and has certain research and application results, how to allocate a large number of computing tasks and computing resources to computing nodes and how to schedule computing tasks at edge nodes are still challenges for edge computing. In view of the problems encountered by edge computing technology in resource allocation and task scheduling, this paper designs a dynamic task scheduling strategy for edge computing with delay-aware characteristics, which realizes the reasonable utilization of computing resources and is required for edge computing systems. This paper proposes a resource allocation scheme combined with the simulated annealing algorithm, which minimizes the overall performance loss of the system while keeping the system low delay. Finally, it is verified through experiments that the task scheduling and resource allocation methods proposed in this paper can significantly reduce the response delay of the application.

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Alanezi, Mohammed A., Abdulazeez F. Salami, Yusuf A. Sha’aban, Houssem R. E. H. Bouchekara, Mohammad S. Shahriar, Mohammed Khodja, and Mostafa K. Smail. "UBER: UAV-Based Energy-Efficient Reconfigurable Routing Scheme for Smart Wireless Livestock Sensor Network." Sensors 22, no. 16 (August 17, 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 balancing ratio (LBR), and topology fluctuation effect ratio (TFER). Obtained results demonstrated that operating with a UAV altitude of 230 m yields gains of 31.58%, 61.67%, and 75.57% for NST, LBR, and TFER, respectively. A comparative performance evaluation of UBER was carried out with respect to hybrid heterogeneous routing (HYBRID) and mobile sink using directional virtual coordinate routing (MS-DVCR). The performance indicators employed for this comparative analysis are energy consumption (ENC), network coverage (COV), received packets (RPK), SN failures detected (SNFD), route failures detected (RFD), routing overhead (ROH), and end-to-end delay (ETE). With regard to the best-obtained results, UBER recorded performance gains of 46.48%, 47.33%, 15.68%, 19.78%, 46.44%, 29.38%, and 58.56% over HYBRID and MS-DVCR in terms of ENC, COV, RPK, SNFD, RFD, ROH, and ETE, respectively. The results obtained demonstrated that the UBER scheme is highly efficient with competitive performance against the benchmarked CBR schemes.

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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 (May 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 concentration was observed in flower buds, flowers, and hulls. Recent work has demonstrated that B forms a B-sorbitol complex in Prunus species. This B-sorbitol complex is phloem mobile and is transported to sink organs. Here we demonstrate that fall-applied B is absorbed by the leaf and is subsequently transported (presumably as the B-sorbitol complex) to floral buds where it is available to flowers and, hence, influences fruit set and yield. It is concluded that fall foliar-applied B is a useful fertilization strategy that can be used to optimize tissue B concentration in species in which B is phloem mobile. Boron applied at 245 and/or 490 ppm significantly increased fruit set in `Butte' and `Mono' and increased yield of `Butte' in 1994 on open-pollinated trees (yield was not determined in 1993). The highest initial and second fruit set was associated with either the 245 or 490 ppm B treatments in both cultivars and both years. This increased fruit set resulted in yield increases of 53% and 4%, respectively, for `Butte' and `Mono'. Of the two cultivars, `Butte', which had lower tissue B concentration before B application, responded more significantly in yield to B application. Application of 735 ppm B was less effective than either 245 and 490 ppm B; however, no visual symptoms of excess B were observed.

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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 (November 1, 2011): 3528–36. http://dx.doi.org/10.1166/asl.2011.1905.

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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 (September 7, 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 by a dynamical caching strategy in MEC. Furthermore, a two-level computing strategy called joint task offloading and service caching (JTOSC) is proposed to solve the optimized problem. The outer layer in JTOSC iteratively updates the service caching decisions based on the Gibbs sampling. The inner layer in JTOSC adopts the fairness-aware allocation algorithm and the offloading revenue preference-based bilateral matching algorithm to get a great computing resource allocation and task offloading scheme. The simulation results indicate that the proposed strategy outperforms the other four comparison strategies in terms of maximum offloading delay, service cache hit rate, and edge load balance.

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50

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 (September 13, 2022): 9170. http://dx.doi.org/10.3390/app12189170.

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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 of the algorithm. In addition, nonlinear convex decreasing weights are introduced to balance the ability of the algorithm for global exploration and local exploitation to achieve dynamic updating of the predator and prey population positions. At the same time, the golden sine algorithm idea is combined to update the prey position, narrow the search range of the predator population, and improve the convergence accuracy and speed. Furthermore, the superiority of the proposed FMMPA is verified by comparison with the original MPA and several well-known intelligent algorithms on 16 classical benchmark functions, the Wilcoxon rank sum test and part of the CEC2014 complex test functions. Finally, the feasibility of FMMPA in practical application optimization problems is verified by testing and analyzing the mobile robot path planning application design experiments.

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