Journal articles on the topic 'Node scheduling'
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Wang, Zhangquan, Yourong Chen, Banteng Liu, Haibo Yang, Ziyi Su, and Yunkai Zhu. "A sensor node scheduling algorithm for heterogeneous wireless sensor networks." International Journal of Distributed Sensor Networks 15, no. 1 (January 2019): 155014771982631. http://dx.doi.org/10.1177/1550147719826311.
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To improve the regional coverage rate and network lifetime of heterogeneous wireless sensor networks, a sensor node scheduling algorithm for heterogeneous wireless sensor networks is proposed. In sensor node scheduling algorithm, heterogeneous perception radius of sensor node is considered. Incomplete coverage constraint and arc coverage interval are analyzed. Regional coverage increment optimization model, arc coverage increment optimization model, and residual energy optimization model are proposed. Multi-objective scheduling model is established using weight factors and integrated function. Furthermore, the heuristic method is proposed to solve the multi-objective optimization model, and scheduling scheme of heterogeneous sensor nodes is obtained. When the network is in operation for a period of time, some sensor nodes are invalid and relevant regions are uncovered. The repair method is proposed to wake up sleep sensor nodes and repair the coverage blind area. The simulation results show that if keeping the same regional coverage rate, sensor node scheduling algorithm improves network lifetime, increases number of living sensor nodes, and keeps average node energy consumption at a low level. Under certain conditions, sensor node scheduling algorithm outperforms DGREEDY, two-tiered scheduling, and minimum connected cover.
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Huang, Yu, Wanxing Sheng, Peipei Jin, Baicuan Nie, Meikang Qiu, and Guangquan Xu. "A Node-Oriented Discrete Event Scheduling Algorithm Based on Finite Resource Model." Journal of Organizational and End User Computing 31, no. 3 (July 2019): 67–82. http://dx.doi.org/10.4018/joeuc.2019070104.
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Discrete event simulation is the most important and essential part in network simulation. The node-oriented model of discrete event scheduling is a model that allocates computing resources as nodes and makes the discrete event simulation as a simulation task on nodes. In this article the reason of low performance in large-scale network simulation is analyzed, and an ideal node-oriented model of discrete event scheduling is presented and a resource-limited node-oriented model of discrete event scheduling by adding some restrictions on network resources is proposed. Then, the authors complete contrast experiments of the resource-limited node-oriented model of discrete event scheduling and NS2. Finally, packet loss in resource-limited node-oriented model of discrete event scheduling is examined. Also, NS2 is discussed in this article and the authors have proposed an improved method for the packet loss algorithm in a resource-limited node-oriented model of discrete event scheduling.
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Gupta, Gagan R., Sujay Sanghavi, and Ness B. Shroff. "Node weighted scheduling." ACM SIGMETRICS Performance Evaluation Review 37, no. 1 (June 15, 2009): 97–108. http://dx.doi.org/10.1145/2492101.1555361.
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Feng, Juan, and Hongwei Zhao. "Energy-Balanced Multisensory Scheduling for Target Tracking in Wireless Sensor Networks." Sensors 18, no. 10 (October 22, 2018): 3585. http://dx.doi.org/10.3390/s18103585.
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One important way to extend the lifetime of wireless sensor networks (WSNs) is to manage the sleep scheduling of sensor nodes after they are deployed. Most of the existing works on node scheduling mainly concentrate on nodes which have only one sensor, and they regard a node and its sensor modules as a whole to manage sleep scheduling. Few works involve the sensed modules scheduling of the sensor nodes, which have multiple sensors. However, some of the sensed modules (such as video sensor) consume a lot of energy. Therefore, they have less energy efficiency for multisensory networks. In this paper, we propose a distributed and energy-balanced multisensory scheduling strategy (EBMS), which considers the scheduling of both the communication modules and the sensed modules for each node in target tracking WSNs. In EBMS, the network is organized as clustering structures. Each cluster head adaptively assigns a sleep time to its cluster members according to the position of the members. Energy-balanced multisensory scheduling strategy also proposes an energy balanced parameter to balance the energy consumption of each node in the network. In addition, multi-hop coordination scheme is proposed to find the optimal cooperation among clusters to maximize the energy conservation. Experimental results show that EBMS outperformed the state-of-the-art approaches.
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Et. al., G. Joel Sunny Deol,. "Hadoop Job Scheduling Using Improvised Ant Colony Optimization." Turkish Journal of Computer and Mathematics Education (TURCOMAT) 12, no. 2 (April 10, 2021): 3417–24. http://dx.doi.org/10.17762/turcomat.v12i2.2403.
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Hadoop Distributed File System is used for storage along with a programming framework MapReduce for processing large datasets allowing parallel processing. The process of handling such complex and vast data and maintaining the performance parameters up to certain level is a difficult task. Hence, an improvised mechanism is proposed here that will enhance the job scheduling capabilities of Hadoop and optimize allocation and utilization of resources. Significantly, an aggregator node is added to the default HDFS framework architecture to improve the performance of Hadoop Name node. In this paper, four entities viz., the name node, secondary name node, aggregator nodes, and data nodes have been modified. Here, the aggregator node assigns jobs to data node, while Name node tracks aggregator nodes. Also, based on the job size and expected execution time, an improvised ant colony optimization method is developed for scheduling jobs.In the end, the results demonstrate notable improvisation over native Hadoop and other approaches.
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Xu, Yun, Wanguo Jiao, and Mengqiu Tian. "Energy-Efficient Connected-Coverage Scheme in Wireless Sensor Networks." Sensors 20, no. 21 (October 28, 2020): 6127. http://dx.doi.org/10.3390/s20216127.
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In the wireless sensor network, the lifetime of the network can be prolonged by improving the efficiency of limited energy. Existing works achieve better energy utilization, either through node scheduling or routing optimization. In this paper, an efficient solution combining node scheduling with routing protocol optimization is proposed in order to improve the network lifetime. Firstly, to avoid the redundant coverage, a node scheduling scheme that is based on a genetic algorithm is proposed to find the minimum number of sensor nodes to monitor all target points. Subsequently, the algorithm prolongs the lifetime of the network through choosing redundant sleep nodes to replace the dead node. Based on the obtained minimum coverage set, a new routing protocol, named Improved-Distributed Energy-Efficient Clustering (I-DEEC), is proposed. When considering the energy and the distance of the sensor node to the sink, a new policy choosing the cluster head is proposed. To make the energy load more balanced, uneven clusters are constructed. Meanwhile, the data communication way of sensor nodes around the sink is also optimized. The simulation results show that the proposed sensor node scheduling algorithm can reduce the number of redundant sensor nodes, while the I-DEEC routing protocol can improve the energy efficiency of data transmission. The lifetime of the network is greatly extended.
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Zhu, Li, Chunxiao Fan, Huarui Wu, and Zhigang Wen. "A Coverage Algorithm based on Key Node Scheduling." International Journal of Online Engineering (iJOE) 11, no. 9 (October 29, 2015): 67. http://dx.doi.org/10.3991/ijoe.v11i9.5068.
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Network coverage rate is a key standard of measuring the quality of network coverage. This thesis aims at solving the differences between node energy and task, which causes coverage holes and blind spots of Wireless Sensor Network, and proposes a coverage algorithm, based on key node scheduling, divides node subsets, and adjusts the states of individual nodes according to node energy and coverage rate. This algorithm ensures network connectivity while reducing coverage holes and redundancy. Simulation results show that, the proposed algorithm can effectively reduce failure nodes, energy consumption, improve network coverage rate, and demonstrates network convergence and stability.
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Liu, Weirong, Yun He, Xiaoyong Zhang, Fu Jiang, Kai Gao, and Jianming Xiao. "Energy-Efficient Node Scheduling Method for Cooperative Target Tracking in Wireless Sensor Networks." Mathematical Problems in Engineering 2015 (2015): 1–11. http://dx.doi.org/10.1155/2015/627479.
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Using the sensor nodes to achieve target tracking is a challenging problem in resource-limited wireless sensor networks. The tracking nodes are usually required to consume much energy to improve the tracking performance. In this paper, an energy-efficient node scheduling method is proposed to minimize energy consumption while ensuring the tracking accuracy. Firstly, the Kalman-consensus filter is constructed to improve the tracking accuracy and predict the target position. Based on the predicted position, an adaptive node scheduling mechanism is utilized to adjust the sample interval and the number of active nodes dynamically. Rather than using traditional search algorithm, the scheduling problem is decomposed to decouple the sample interval and number of nodes. And the node index is mapped into real domain to get closed-form solution to decide the active nodes. Thus, the NP-complete nature is avoided in the proposed method. The proposed scheduling method can keep the tracking accuracy while minimizing energy consumption. Simulation results validate its effective performance for target tracking in wireless sensor networks.
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Fu, Wentao, Xilun Luo, Yuanfa Ji, and Xiyan Sun. "Node-Subset Scheduling with a Subset-Reset Mechanism for the Decoding Algorithm of Nonbinary LDPC Codes." Mobile Information Systems 2021 (May 10, 2021): 1–16. http://dx.doi.org/10.1155/2021/5548091.
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For the conventional extended min-sum (EMS) algorithm, all check nodes update their check-to-variable (C2V) messages in every iteration. Selected scheduling, which reduces the number of check nodes for message updating in one iteration, can effectively reduce the complexity of the decoding algorithm, but it also lead to some performance degradation. With the introduction of a metric based on node stability, we propose stability-based node-subset scheduling (SNS) for the EMS algorithm, which can improve the performance of node-subset scheduling (NS). Second, to further improve the decoding performance of SNS while maintaining low complexity, we propose the SNS-EMS algorithm with a subset-reset mechanism (RSNS-EMS) based on the abnormal stability found in the processing node subset, which will cause the estimated codeword to fail to converge. The RSNS-EMS algorithm enhances performance through a sliding window detection and reset mechanism, and it resets the elements in the processing node subset to force all check nodes to update new messages when abnormal stability is detected. The simulation results show that the proposed algorithm can reduce complexity by approximately 25% with negligible performance degradation.
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Abror, Gezaq, Rusminto Tjatur Widodo, and M. Udin Harun Al Rasyid. "Dynamic Sleep Scheduling on Air Pollution Levels Monitoring with Wireless Sensor Network." EMITTER International Journal of Engineering Technology 5, no. 2 (January 13, 2018): 209–33. http://dx.doi.org/10.24003/emitter.v5i2.185.
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Wireless Sensor Network (WSN) can be applied for Air Pollution Level Monitoring System that have been determined by the Environmental Impact Management Agency which is PM10, SO2, O3, NO2 and CO. In WSN, node system is constrained to a limited power supply, so that the node system has a lifetime. To doing lifetime maximization, power management scheme is required and sensor nodes should use energy efficiently. This paper proposes dynamic sleep scheduling using Time Category-Fuzzy Logic (Time-Fuzzy) Scheduling as a reference for calculating time interval for sleep and activated node system to support power management scheme. This research contributed in power management design to be applied to the WSN system to reduce energy expenditure. From the test result in real hardware node system, it can be seen that Time-Fuzzy Scheduling is better in terms of using the battery and it is better in terms of energy consumption too because it is more efficient 51.85% when it is compared with Fuzzy Scheduling, it is more efficient 68.81% when it is compared with Standard Scheduling and it is more efficient 85.03% when compared with No Scheduling.
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Wu, Jiaqi, and Huahu Xu. "Wireless Photoelectric Sensor Network Scheduling Algorithm Based on Divisible Load." Journal of Nanoelectronics and Optoelectronics 13, no. 10 (October 1, 2018): 1499–504. http://dx.doi.org/10.1166/jno.2018.2464.
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To discuss the divisible load scheduling in wireless photoelectric sensor networks, a load scheduling algorithm called EDDLT based on residual energy landscape is proposed. In the algorithm, the constant of the time needed for the induction and reporting unit data is adjusted to the variable parameters based on the residual energy. In addition, the ratio of the initial energy to the residual energy is used to carry out the effective load scheduling. By using this algorithm, when the load is allocated to each sensor node, the remaining energy of nodes is considered, and a lighter load is allocated to sensor nodes with less residual energy. EDDLT, compared to the standard divisible load scheduling method SDLT, the number of execution rounds is greatly increased when the first sensor node is dead. The experimental results showed that EDDLT had a certain effect on prolonging the lifetime of wireless photoelectric sensor networks. To sum up, the scheduling algorithm has good performance in exploring divisible load.
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Zhang, Wenbo, Jing Wang, Guangjie Han, Xinyue Zhang, and Yongxin Feng. "A Cluster Sleep-Wake Scheduling Algorithm Based on 3D Topology Control in Underwater Sensor Networks." Sensors 19, no. 1 (January 4, 2019): 156. http://dx.doi.org/10.3390/s19010156.
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3D topology control in underwater sensor networks is of great significance to ensuring reliable and efficient operation of the network. In this paper, by analyzing the characteristics of an underwater sensor network, we take the cube as the basic unit to perform 3D partition of the monitoring area, define the 3D partition unit and basic cluster structure of the underwater sensor network, and arrange rotating temporary control nodes in the cluster. Then, a cluster sleep-wake scheduling algorithm is proposed that compares the remaining node energy. It selects the node with the largest remaining energy as the working node, and the remaining nodes complete the transition of dormancy and waiting states as long as they reach the preset dormancy time. The node state settings of this phase are completed by the temporary control node. Temporary control nodes selecting and sleep-wake scheduling are used in the algorithm through 3D topology control, which reduces energy consumption and guarantees maximum sensing coverage of the entire network and the connection rate of active nodes. Simulation results further verify the effectiveness of the proposed algorithm.
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Radha, S., G. Josemin Bala, E. Grace Mary Kanaga, and P. Nagabushanam. "Scheduling and adaptive listening approaches in MAC for WSN applications: A survey." Journal of High Speed Networks 26, no. 4 (December 23, 2020): 325–38. http://dx.doi.org/10.3233/jhs-200647.
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False data detection, intrusion detection and coverage rate are major challenges in wireless sensor networks (WSN). Scheduling in media access control (MAC) using gateway and relay nodes solve some of the problems. In this paper, we carried out a brief survey on scheduling, delay aware MAC, cooperative communications in MAC, and adaptive listening to keep controlling the energy in sensors. In addition, multichannel MAC and various routing strategy techniques for WSN are discussed. Firefly algorithm for dynamic scheduling pipelined scheduling for linear sensor networks gives better throughput and latency. Heuristic configuration solves the overhearing problem, as node power-based MAC controls power of each node. Based on WSN applications and the performance metrics concentrated, various techniques for MAC are discussed throughout in this paper.
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Jo, Youngtae. "Communication Availability-Based Scheduling for Fair Data Collection with Path-Constrained Mobile Sink in Wireless Sensor Networks." International Journal of Distributed Sensor Networks 2015 (2015): 1–11. http://dx.doi.org/10.1155/2015/287935.
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To effectively transfer sensing data to a sink node, system designers should consider the characteristic of wireless sensor networks in the way of data transmission. In particular, sensor nodes surrounding a fixed sink node have routinely suffered from concentrated network traffic so that their battery energy is rapidly exhausted. The lifetime of wireless sensor networks decreases due to the rapid power consumption of these sensor nodes. To address the problem, a mobile sink model has recently been chosen for traffic load distribution among sensor nodes. However, since a mobile sink continuously changes its location in sensor networks, it has a time limitation to communicate with each sensor node and unstable signal strength from each sensor node. Therefore, fair and stable data collection policy between a mobile sink and sensor nodes is necessary in this circumstance. In this paper, we propose a new scheduling policy to support fair and stable data collection for a mobile sink in wireless sensor networks. The proposed policy performs data collection scheduling based on the communication availability of data transmission between sensor nodes and a mobile sink.
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Meng, Fan Zhi, Yuan Liu, Chun Rui Zhang, Tong Li, and Yang Yue. "Collaborative Scheduling Using Cooperative Sensing Model for Wsns." Applied Mechanics and Materials 687-691 (November 2014): 2175–81. http://dx.doi.org/10.4028/www.scientific.net/amm.687-691.2175.
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One of the major challenges in constructing wireless sensor networks (WSNs) is to ensure the quality of coverage (QoC) as well as save energy. Considering the cooperative sensing model and the random deployment policy, the judgment model of redundant node without location information is presented. Furthermore, the distributed collaborative scheduling algorithm (DCSA) is designed to guarantee the QoC of networks with the least number of nodes. It chooses the uniformly-located working nodes and makes sure that the energy consumption of each node consumes homogeneously. Simulation results show that the DCSA policy not only provides the desired QoC of networks, but also reduces the number of working nodes significantly, saves the energy of the networks, and extends the network lifetime.
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Han, Yufei, Mengqi Cui, and Shaojun Liu. "Optimal Sensor and Relay Nodes Power Scheduling for Remote State Estimation with Energy Constraint." Sensors 20, no. 4 (February 16, 2020): 1073. http://dx.doi.org/10.3390/s20041073.
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We study the sensor and relay nodes’ power scheduling problem for the remote state estimation in a Wireless Sensor Network (WSN) with relay nodes over a finite period of time given limited communication energy. We also explain why the optimal infinite time and energy case does not exist. Previous work applied a predefined threshold for the error covariance gap of two contiguous nodes in the WSN to adjust the trade-off between energy consumption and estimation accuracy. However, instead of adjusting the trade-off, we employ an algorithm to find the optimal sensor and relay nodes’ scheduling strategy that achieves the smallest estimation error within the given energy limit under our model assumptions. Our core idea is to unify the sensor-to-relay-node way of error covariance update with the relay-node-to-relay-node way by converting the former way of the update into the latter, which enables us to compare the average error covariances of different scheduling sequences with analytical methods and thus finding the strategy with the minimal estimation error. Examples are utilized to demonstrate the feasibility of converting. Meanwhile, we prove the optimality of our scheduling algorithm. Finally, we use MATLAB to run our algorithm and compute the average estimation error covariance of the optimal strategy. By comparing the average error covariance of our strategy with other strategies, we find that the performance of our strategy is better than the others in the simulation.
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Lu, Jun, and De Zhi An. "TDMA-Based Time Slots Assignment Algorithm." Applied Mechanics and Materials 241-244 (December 2012): 2445–53. http://dx.doi.org/10.4028/www.scientific.net/amm.241-244.2445.
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In this paper we studied timeliness of TDMA-based MAC scheduling mechanisms. TDMA-based MAC protocols require sensor nodes to deliver data individually so as to eliminate collisions in shared channel. This scheduling mechanism can assist sensor nodes in managing energy efficiently since data resending that collisions induced has a significant impact on battery life. But during medium access arbitration, the elected central node has to receive other nodes’ state messages one by one before assigning time slots for each node. While in large-scale sensor networks, the waiting time would be a relatively long duration and result in timeliness decrease in time-sensitive environments. We propose a novel time slots assignment algorithm for TDMA-based MAC protocols that allows sensor nodes to deliver state messages simultaneously to central node for medium access arbitration and present an analysis in which these two approaches are compared in respect to timeliness. The algorithm is evaluated through simulation. Simulation results have confirmed the timeliness of our new algorithm.
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Chen, Jin Song. "Wireless Sensor Networks Scheduling Algorithm Based on the Probability of Monitoring." Advanced Engineering Forum 4 (June 2012): 32–37. http://dx.doi.org/10.4028/www.scientific.net/aef.4.32.
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This paper introduces the basics of wireless sensor networks, focusing on the concept of sensor network data collection, data collection mechanisms, data collection in-network data aggregation, data collection and data collection applications Research. This paper presents the data collection in WSN node scheduling concept, analyzed the two data collection in WSN scheduling mechanism, which is based on data collection interval node scheduling mechanism and turn the data based on perceived probability of node sleep scheduling mechanism.
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Zhang, Yajun, Gang Qiu, Meng Liu, and Hongjun Wang. "High-density data transmission and scheduling method in wireless sensor networks based on Wi-Fi." International Journal of Distributed Sensor Networks 16, no. 7 (July 2020): 155014772094341. http://dx.doi.org/10.1177/1550147720943414.
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In wireless sensor network, the storage amount of information is high, and the transmission and scheduling of control information is reasonable. The node communication model, network structure model, and energy consumption model are constructed. On this basis, the high-density data in wireless sensor network are scheduled to optimize the time for nodes to perform tasks. The nodes in the network are fully scheduled to control the generation time of packets in the network and the generation time of packets in the network. Experimental results show that in different iterations, the proposed method has lower node delay and node energy consumption, with values less than 0.2 and 2, respectively, and the maximum data fusion quality can reach 98, with high fusion benefits, so as to improve the transmission and scheduling efficiency and quality of high-density data in wireless sensor network.
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Zhou, Xin Lian, and Jian Bo Xu. "The Research of Data Gathering Protocol for Mobile Sensor Networks." Advanced Materials Research 216 (March 2011): 621–24. http://dx.doi.org/10.4028/www.scientific.net/amr.216.621.
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This paper first proposed an energy-efficient distributed clustering technology for mobile sensor nodes and sink node mobility, select the higher residual energy and the nearest node from fixed nodes as cluster heads responsible for collecting sensed data, and all the fixed nodes form routing backbone to forward data, both can save energy and avoid cluster head away. Then, proposed a cross-layer scheduling mechanism to avoid the impact of mobile node and meet expectations cluster coverage. With energy-efficient clustering technology, efficient network topology control technology and mobile sink node, the data collection algorithm MSDBG, not only has considered mobility of nodes and energy saving, but also has achieved prolonging network lifetime.
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WU, JIE, and SHUHUI YANG. "ENERGY-EFFICIENT NODE SCHEDULING MODELS IN SENSOR NETWORKS WITH ADJUSTABLE RANGES." International Journal of Foundations of Computer Science 16, no. 01 (February 2005): 3–17. http://dx.doi.org/10.1142/s0129054105002838.
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In this paper, we study the problem of maintaining sensing coverage by keeping a small number of active sensor nodes and using a small amount of energy consumption in wireless sensor networks. This paper extends a result from 22 where only uniform sensing range among all sensors is used. We adopt an approach that allows non-uniform sensing ranges for different sensors. As opposed to the uniform sensing range node scheduling model in 22, two new energy-efficient models with different sensing ranges are proposed. Our objective is to minimize the overlapped sensing area of sensor nodes, thus to reduce the overall energy consumption by sensing and communication to prolong the whole network's life time, and at the same time to achieve the high ratio of coverage. Extensive simulation is conducted to verify the effectiveness of our node scheduling models.
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Weiquan, Zhao, Yuan Huaqiang, and Wei Xiaorui. "The Experimental Platform Design for NCS Based on CAN Bus." International Journal of Reconfigurable and Embedded Systems (IJRES) 4, no. 1 (March 1, 2015): 22. http://dx.doi.org/10.11591/ijres.v4.i1.pp22-27.
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In order to facilitate research on the performance of Networked Control System, overcome the defects of unable to reflect the system performance, based on the CAN bus a kind of NCS experimental platform is designed. The system is composed of a main node and several slave nodes and Dc motor as the actuator. The master node is designed with ARM + U-boot + Linux structure, connecting with PC via Ethernet. For this experiment platform, using c + + Builder a scheduling algorithm performance testing software is developed, to further research on the effects of different scheduling algorithm on the NCS performance.
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Verma, Parag, Ankur Dumka, Dhawal Vyas, and Anuj Bhardwaj. "Reinforcement Learning based Node Sleep or Wake-up Time Scheduling Algorithm for Wireless Sensor Network." International Journal of Mathematical, Engineering and Management Sciences 5, no. 4 (August 1, 2020): 707–31. http://dx.doi.org/10.33889/ijmems.2020.5.4.057.
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A wireless sensor network is a collection of small sensor nodes that have limited energy and are usually not rechargeable. Because of this, the lifetime of wireless sensor networks has always been a challenging area. One of the basic problems of the network has been the ability of the nodes to effectively schedule the sleep and wake-up time to overcome this problem. The motivation behind node sleep or wake-up time scheduling is to take care of nodes in sleep mode for as long as possible (without losing data packet transfer efficiency) and thus extend their useful life. This research going to propose scheduling of nodes sleeps and wake-up time through reinforcement learning. This research is not based on the nodes' duty cycle strategy (which creates a compromise between data packet delivery and nodes energy saving delay) like other existing researches. It is based on the research of reinforcement learning which gives independence to each node to choose its own activity from the transmission of packets, tuning or sleep node in each time band which works in a decentralized way. The simulation results show the qualified performance of the proposed algorithm under different conditions.
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Shi, Jingyan, Jiaheng Zou, Qingbao Hu, Xiaowei Jiang, and Ge Ou. "An automatic solution to make HTCondor more stable and easier." EPJ Web of Conferences 245 (2020): 07062. http://dx.doi.org/10.1051/epjconf/202024507062.
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HTCondor has been widely adopted by HEP clusters to provide high-level scheduling performance. Unlike other schedulers, HTCondor provides loose management of the worker nodes. We developed a maintenance automation tool called “HTCondor MAT” that focuses on dynamic resource management and automatic error handling. A central database records all worker node information, which is sent to the worker node for the startd configuration. If an error happens for the worker node, the node information stored in the database is updated and the worker node is reconfigured with the new node information. The new configuration stops the startd from accepting error-related jobs until the worker node recovers. The MAT has been deployed in the IHEP HTC cluster to provide a central way to manage the worker nodes and remove the impacts of errors on the worker nodes automatically.
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Pan, Li. "Node localization method for massive sensor networks based on clustering particle swarm optimization in cloud computing environment." International Journal of Wavelets, Multiresolution and Information Processing 18, no. 01 (May 27, 2019): 1941016. http://dx.doi.org/10.1142/s0219691319410169.
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In order to reduce the positioning error of wireless sensor network nodes and deal with the positioning of a large number of sensor network nodes, a mass sensor node positioning method based on particle swarm optimization (SNPSO) is proposed. The node location error of node distance correction value is corrected by SNPSO algorithm, and the sensing data is encoded by the index of cloud computing resources. The dynamic target strategy (DTS) algorithm is used to solve the strict deadline constraints. The algorithm focuses on optimizing execution time to meet deadline constraints, and once feasible solutions are obtained, it focuses on optimizing execution costs within deadline constraints. The performance of the algorithm is simulated and analyzed on the platform of MATLAB 2016. Compared with the sensor positioning method, SNPSO improves the positioning accuracy of mass sensor nodes. The simulation results verify the validity of SNPSO. Compared with the improved quantum genetic algorithm (IQGA) under different scale data scheduling and different deadlines constraints, the proposed algorithm can improve the positioning accuracy of mass sensor nodes. The proposed algorithm can find the optimal solution of cloud computing resource scheduling with lower execution cost under strict deadline constraints, and can more easily meet the needs of massive sensor network node location data processing.
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Liu, Manxing, and Xiufeng Xia. "Research on Priority-based Flexible Job Shop Scheduling Algorithm." E3S Web of Conferences 251 (2021): 03086. http://dx.doi.org/10.1051/e3sconf/202125103086.
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Research on the Flexible Job Shop Scheduling (FJSP) problem in the manufacturing process of aircraft engines has been carried out. It is found that there are real requirements such as order mandatory nodes and equipment selection in the current job scheduling process. Order mandatory node means that some important orders must be delivered on time at a certain point in time, which often affects the quality of workshop scheduling results. In addition, equipment selection is also an important factor affecting the quality of job shop scheduling results. On this basis, an order priority calculation method with manual intervention is designed. Experiments show that the proposed shop job scheduling algorithm effectively improves the quality of job shop scheduling results.
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Weng, Yu, Haozhen Chu, and Zhaoyi Shi. "An Intelligent Offloading System Based on Multiagent Reinforcement Learning." Security and Communication Networks 2021 (March 24, 2021): 1–13. http://dx.doi.org/10.1155/2021/8830879.
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Intelligent vehicles have provided a variety of services; there is still a great challenge to execute some computing-intensive applications. Edge computing can provide plenty of computing resources for intelligent vehicles, because it offloads complex services from the base station (BS) to the edge computing nodes. Before the selection of the computing node for services, it is necessary to clarify the resource requirement of vehicles, the user mobility, and the situation of the mobile core network; they will affect the users’ quality of experience (QoE). To maximize the QoE, we use multiagent reinforcement learning to build an intelligent offloading system; we divide this goal into two suboptimization problems; they include global node scheduling and independent exploration of agents. We apply the improved Kuhn–Munkres (KM) algorithm to node scheduling and make full use of existing edge computing nodes; meanwhile, we guide intelligent vehicles to the potential areas of idle computing nodes; it can encourage their autonomous exploration. Finally, we make some performance evaluations to illustrate the effectiveness of our constructed system on the simulated dataset.
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Zhai, Y., J. Liu, and L. Liu. "MATHEMATICAL ANALYSIS OF VEHICLE DELIVERY SCALE OF BIKE-SHARING RENTAL NODES." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLII-3 (April 30, 2018): 2229–35. http://dx.doi.org/10.5194/isprs-archives-xlii-3-2229-2018.
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Aiming at the lack of scientific and reasonable judgment of vehicles delivery scale and insufficient optimization of scheduling decision, based on features of the bike-sharing usage, this paper analyses the applicability of the discrete time and state of the Markov chain, and proves its properties to be irreducible, aperiodic and positive recurrent. Based on above analysis, the paper has reached to the conclusion that limit state (steady state) probability of the bike-sharing Markov chain only exists and is independent of the initial probability distribution. Then this paper analyses the difficulty of the transition probability matrix parameter statistics and the linear equations group solution in the traditional solving algorithm of the bike-sharing Markov chain. In order to improve the feasibility, this paper proposes a "virtual two-node vehicle scale solution" algorithm which considered the all the nodes beside the node to be solved as a virtual node, offered the transition probability matrix, steady state linear equations group and the computational methods related to the steady state scale, steady state arrival time and scheduling decision of the node to be solved. Finally, the paper evaluates the rationality and accuracy of the steady state probability of the proposed algorithm by comparing with the traditional algorithm. By solving the steady state scale of the nodes one by one, the proposed algorithm is proved to have strong feasibility because it lowers the level of computational difficulty and reduces the number of statistic, which will help the bike-sharing companies to optimize the scale and scheduling of nodes.
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Xiong, Yonghua, Jing Li, and Manjie Lu. "Critical Location Spatial-Temporal Coverage Optimization in Visual Sensor Network." Sensors 19, no. 19 (September 23, 2019): 4106. http://dx.doi.org/10.3390/s19194106.
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Coverage and network lifetime are two fundamental research issues in visual sensor networks. In some surveillance scenarios, there are some critical locations that demand to be monitored within a designated period. However, with limited sensor nodes resources, it may not be possible to meet both coverage and network lifetime requirements. Therefore, in order to satisfy the network lifetime constraint, sometimes the coverage needs to be traded for network lifetime. In this paper, we study how to schedule sensor nodes to maximize the spatial-temporal coverage of the critical locations under the constraint of network lifetime. First, we analyze the sensor node scheduling problem for the spatial-temporal coverage of the critical locations and establish a mathematical model of the node scheduling. Next, by analyzing the characteristics of the model, we propose a Two-phase Spatial-temporal Coverage-enhancing Method (TSCM). In phase one, a Particle Swarm Optimization (PSO) algorithm is employed to organize the directions of sensor nodes to maximize the number of covered critical locations. In the second phase, we apply a Genetic Algorithm (GA) to get the optimal working time sequence of each sensor node. New coding and decoding strategies are devised to make GA suitable for this scheduling problem. Finally, simulations are conducted and the results show that TSCM has better performance than other approaches.
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Wang, Hui, Youming Li, Tingcheng Chang, and Shengming Chang. "An Effective Scheduling Algorithm for Coverage Control in Underwater Acoustic Sensor Network." Sensors 18, no. 8 (August 1, 2018): 2512. http://dx.doi.org/10.3390/s18082512.
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Coverage maintenance is a bottleneck restricting the development of underwater acoustic sensor networks (UASNs). Since the energy of the nodes is limited, the coverage of UASNs may gradually decrease as the network operates. Thus, energy-saving coverage control is crucial for UASNs. To solve the above problems, this paper proposes a coverage-control strategy (referred to as ESACC) that establishes a sleep–wake scheduling mechanism based on the redundancy of deployment nodes. The strategy has two main parts: (1) Node sleep scheduling based on a memetic algorithm. To ensure network monitoring performance, only some nodes are scheduled to work, with redundant nodes in a low-power hibernation state, reducing energy consumption and prolonging the network lifetime. The goal of node scheduling is to find a minimum set of nodes that can cover the monitoring area, and a memetic algorithm can solve this problem. (2) Wake-up scheme. During network operation, sleeping nodes are woken to cover the dead nodes and maintain high coverage. This scheme not only reduces the network energy consumption but takes into account the monitoring coverage of the network. The experimental data show that ESACC performs better than current algorithms, and can improve the network life cycle while ensuring high coverage.
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Zhao, Huiyuan, Yuxing Mao, and Tao Cheng. "Study on the transmission path and timing scheduling for WSNs with heterogeneous nodes." Sensor Review 39, no. 1 (January 21, 2019): 51–57. http://dx.doi.org/10.1108/sr-06-2017-0121.
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Purpose Application environments of wireless sensor networks (WSNs) include heterogeneous nodes with different packet sizes, transmission abilities and tolerable delay times. This study aims to design a reasonable network topology and transmission timing for these heterogeneous nodes to improve the quality of service (QoS) of networks. Design/methodology/approach In this paper, the authors treat node urgency and data packets as the basis of network clustering and to extend the network lifetime. The flow, energy consumption and residual energy of a node are included in the cluster head election. We also propose a delay evaluation function. Findings All the nodes in the network are guaranteed to transmit to the sink nodes efficiently by planning the transmission order in each cluster. Originality/value The simulation results show that the proposed method can balance node urgency and data packets path planning, which not only extends the lifetime of the network but also decreases network delay and improves the overall efficiency.
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Yuan, Kou Lin, Lin Qiao, and Lei Han. "Level and Cluster Based Routing for Wireless Sensor Network." Applied Mechanics and Materials 321-324 (June 2013): 515–22. http://dx.doi.org/10.4028/www.scientific.net/amm.321-324.515.
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This paper proposes a level and cluster based routing approach for a wireless sensor network. Nodes in the network are divided into several levels according to their hops to sink node. Every sensor node has a level number. Using level information, a sensor node can send messages to a sink node in a more efficient way, and a sink node can easily locate other sensor nodes. To make network more balanced, the paper introduces a cluster method, which splits nodes in the same level into different clusters, and chooses a cluster head for every cluster, to switch nodes in the cluster to work in turn. Unlike all other cluster routing methods, a cluster head node takes schedule jobs of sensor nodes in the cluster according to their energy left, instead of sensing. The paper also presents several algorithms for constructing a wireless sensor network, querying and scheduling. The simulation experiment shows that the scalability of our method is approximately linear.
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Bakhsh, Sheikh Tahir, Muhammad Aman Sheikh, and Rayed AlGhamdi. "Self-Schedule and Self-Distributive MAC Scheduling Algorithms for Next-Generation Sensor Networks." International Journal of Distributed Sensor Networks 2015 (2015): 1–17. http://dx.doi.org/10.1155/2015/746216.
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The distributive nature of wireless sensor networks (WSNs) poses great challenges for the design of distributive scheduling to maximize network life and spatial reuse of time slot with minimum frame length. Most of the existing scheduling techniques are either centralized or contentional. The existing techniques cannot efficiently adapt to the dynamic wireless environment. In this paper, self-scheduled and distributed MAC (SSD-MAC) and self-distributive MAC (SD-MAC) medium access control algorithms are proposed to reduce the complexity and variety of scheduling problems. The proposed algorithms do not require any synchronization and can effectively adapt to dynamic topology changes without incurring global communication overhead. According to the proposed algorithms, each node maps a conflict-free time slot for itself up to 2-hop neighboring nodes. Consequently, each node successfully schedules a unique time slot for itself in a heuristic manner based on its local information. Moreover, the proposed algorithms also guarantee conflict-free edge coloring because all the incident edges to a single node are assigned to colors in such a way that none of the edges should have the same color. It has been demonstrated that, with regard to communication overhead, energy consumption and execution time through simulation proposed that algorithms outperform existing distributed randomized scheduling algorithm (DRAND).
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Zhang, Dong Qing, and Deng Li. "High-Density Randomly Deployed Nodes Sleep Scheduling Algorithm in Wireless Sensor Networks." Advanced Materials Research 846-847 (November 2013): 446–51. http://dx.doi.org/10.4028/www.scientific.net/amr.846-847.446.
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The high-density randomly deployment of nodes in Wireless Sensor Networks results in a large number of redundant nodes due to the overlap of sensing areas. A scheduling algorithm for redundant nodes is proposed to effectively prolong the lifetime of WSN. The algorithm focuses on employing different scheduling strategies on border nodes and internal nodes to avoid contraction of the network boundary by judging whether a node is on the network boundary according to the number of working nodes in its neighbor table. The simulation results show that the algorithm can effectively prolong the lifetime of the network.
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Zou, Lida, Qingzhong Li, Wenhao Li, and Lanju Kong. "Acentric Scheduling Strategy for SLA-Based Multi-Tenant Queries." International Journal of Cooperative Information Systems 25, no. 03 (September 2016): 1650009. http://dx.doi.org/10.1142/s021884301650009x.
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The response time for multi-tenant queries is one of the most important indicators in the service level agreements (SLA). The service provider tries to optimize query scheduling strategy to finish queries of different tenants before the deadline to avoid penalty due to jeopardizing the SLA. With continuous expansion of tenants scale, peer-to-peer (P2P) structure becomes more and more popular in organizing and managing multi-tenant data. In this paper we propose an acentric scheduling approach for SLA-based multi-tenant queries according to the distribution characteristics of multi-tenant data. Our scheduling approach deploys multiple scheduling engines on the computing nodes in the cloud, where the computing node of each engine schedules its assigned queries, estimates whether these queries could be finished before the deadline, and migrates the queries that might jeopardize the SLA to another engine which can respond to it before the deadline. Since the high efficiency of the scheduling process is critical, we improve the balanced binary tree and use it to organize queries on each computing node. Using this structure, the online time complexity of the scheduling strategy is [Formula: see text]. Our extensive experiments demonstrate that our scheduling strategy is sufficient to meet the high scheduling efficiency requirement, while the penalty cost can be reduced up to [Formula: see text] compared with the benchmarking solution and with a better scalability.
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Li, Xiao Juan, and Yi Ping Yuan. "Task Scheduling of Product Development Process Based on Complex Features of Web." Advanced Materials Research 201-203 (February 2011): 1003–7. http://dx.doi.org/10.4028/www.scientific.net/amr.201-203.1003.
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Multi-task scheduling networkis extended based on the complex network theory, from new angles and perspectives to study the multi-task scheduling. The description of method and related mathematical models of complex and multi-task directed network aregiven. Combined with topology of the product development process and their own characteristics,the evaluation model and algorithmto describe the importance of the event node are presented. It can assess the nature ofdifferent nodes effectively, including the key nodes, at the same time,the scheduling algorithm based on the importance of active nodes hasbeen proposed.The study has a certain significance toarrange the execution of tasksin complex product development process reasonably and realize optimal allocation of manufacturing resources.
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Choi, Dojin, Hyeonwook Jeon, Jongtae Lim, Kyoungsoo Bok, and Jaesoo Yoo. "Dynamic Task Scheduling Scheme for Processing Real-Time Stream Data in Storm Environments." Applied Sciences 11, no. 17 (August 27, 2021): 7942. http://dx.doi.org/10.3390/app11177942.
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Owing to the recent advancements in Internet of Things technology, social media, and mobile devices, real-time stream balancing processing systems are commonly used to process vast amounts of data generated in various media. In this paper, we propose a dynamic task scheduling scheme considering task deadlines and node resources. The proposed scheme performs dynamic scheduling using a heterogeneous cluster consisting of various nodes with different performances. Additionally, the loads of the nodes considering the task deadlines are balanced by different task scheduling based on three defined load types. Based on diverse performance evaluations it is shown that the proposed scheme outperforms the conventional schemes.
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Liu, Gui Xiong, Jian Long Xu, and Xiao Bin Hong. "Internet of Things Sensor Node Information Scheduling Model and Energy Saving Strategy." Advanced Materials Research 773 (September 2013): 215–20. http://dx.doi.org/10.4028/www.scientific.net/amr.773.215.
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According to energy constraint problem of wireless sensor node in the Internet of Things (IoT) perception layer, this paper proposed sensor information scheduling model based on mixed logical dynamic (MLD) model and energy saving strategy. First, the amount of transmission data control and the energy consumption of wireless communication control were modeled by MLD mode. Secondly, under MLD model, the sensor node communication scheduler was designed, and reliable scheduling strategy and rules were established for sensor node in different scene, which can adopt different strategy according to the change of scene. Finally, the simulation results show that the sensor node information scheduling model and energy saving strategy can reduce the sensor node data traffic and save more than 50% energy consumption, and the overall data error is 0.018. So it can save the energy consumption of sensor node and guarantee data precision.
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Rahmani, Amir Masoud, Saqib Ali, Mohammad Sadegh Yousefpoor, Efat Yousefpoor, Rizwan Ali Naqvi, Kamran Siddique, and Mehdi Hosseinzadeh. "An Area Coverage Scheme Based on Fuzzy Logic and Shuffled Frog-Leaping Algorithm (SFLA) in Heterogeneous Wireless Sensor Networks." Mathematics 9, no. 18 (September 14, 2021): 2251. http://dx.doi.org/10.3390/math9182251.
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Coverage is a fundamental issue in wireless sensor networks (WSNs). It plays a important role in network efficiency and performance. When sensor nodes are randomly scattered in the network environment, an ON/OFF scheduling mechanism can be designed for these nodes to ensure network coverage and increase the network lifetime. In this paper, we propose an appropriate and optimal area coverage method. The proposed area coverage scheme includes four phases: (1) Calculating the overlap between the sensing ranges of sensor nodes in the network. In this phase, we present a novel, distributed, and efficient method based on the digital matrix so that each sensor node can estimate the overlap between its sensing range and other neighboring nodes. (2) Designing a fuzzy scheduling mechanism. In this phase, an ON/OFF scheduling mechanism is designed using fuzzy logic. In this fuzzy system, if a sensor node has a high energy level, a low distance to the base station, and a low overlap between its sensing range and other neighboring nodes, then this node will be in the ON state for more time. (3) Predicting the node replacement time. In this phase, we seek to provide a suitable method to estimate the death time of sensor nodes and prevent possible holes in the network, and thus the data transmission process is not disturbed. (4) Reconstructing and covering the holes created in the network. In this phase, the goal is to find the best replacement strategy of mobile nodes to maximize the coverage rate and minimize the number of mobile sensor nodes used for covering the hole. For this purpose, we apply the shuffled frog-leaping algorithm (SFLA) and propose an appropriate multi-objective fitness function. To evaluate the performance of the proposed scheme, we simulate it using NS2 simulator and compare our scheme with three methods, including CCM-RL, CCA, and PCLA. The simulation results show that our proposed scheme outperformed the other methods in terms of the average number of active sensor nodes, coverage rate, energy consumption, and network lifetime.
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Jiang, Xue Ying, Yao Wang, and Yan Yan Meng. "Research on Information Processing with Dynamic Adaptive Job Scheduling Algorithm Based on Hadoop Platform." Advanced Materials Research 1046 (October 2014): 359–62. http://dx.doi.org/10.4028/www.scientific.net/amr.1046.359.
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Job scheduling and resource allocation problems relate to the overall performance and resource utilization of Hadoop platform. This paper proposes a dynamic adaptive job scheduling algorithm based on Hadoop platform. This algorithm monitors the change of each computing resource nodes in real time. And through the feedback mechanism pass this information to the control node. It implements the purpose of assign the optimal resource for each of tasks.
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Vashisht, Priyanka, Rajesh Kumar, and Anju Sharma. "Efficient Dynamic Replication Algorithm Using Agent for Data Grid." Scientific World Journal 2014 (2014): 1–10. http://dx.doi.org/10.1155/2014/767016.
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In data grids scientific and business applications produce huge volume of data which needs to be transferred among the distributed and heterogeneous nodes of data grids. Data replication provides a solution for managing data files efficiently in large grids. The data replication helps in enhancing the data availability which reduces the overall access time of the file. In this paper an algorithm, namely, EDRA using agents for data grid, has been proposed and implemented. EDRA consists of dynamic replication of hierarchical structure taken into account for the selection of best replica. Decision for selecting the best replica is based on scheduling parameters. The scheduling parameters are bandwidth, load gauge, and computing capacity of the node. The scheduling in data grid helps in reducing the data access time. The distribution of the load on the nodes of data grid is done evenly by considering scheduling parameters. EDRA is implemented using data grid simulator, namely, OptorSim. European Data Grid CMS test bed topology is used in this experiment. The simulation results are obtained by comparing BHR, LRU, No Replication, and EDRA. The result shows the efficiency of EDRA algorithm in terms of mean job execution time, network usage, and storage usage of node.
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Naseera, Shaik. "Dynamic Job Scheduling Strategy for Unreliable Nodes in a Volunteer Desktop Grid." International Journal of Grid and High Performance Computing 8, no. 4 (October 2016): 21–33. http://dx.doi.org/10.4018/ijghpc.2016100102.
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Desktop grid aims to harvest a number of idle desktop computers owned by individuals on the edge of internet. Now days, Desktop grids are gaining increasing popularity because of the advances in the technology and availability of high computing power from the desktops. Volunteer nodes in a Desktop Grid encounter two types of failures: volatility failure and interference failure. Volatile failures are due to periodic maintenance, machine breakdown, system crash or shutdown etc that make node inaccessible to the Desktop Grid user. Interference failures are due to volunteer autonomic nature that the node owner can withdraw participation from public execution due to the need to execute the private jobs. This makes the node inaccessible to the Desktop Grid user and may cause partial or entire loss of the public job execution. Volunteer interferences cause slowdown in the execution of the jobs. In this paper the author present a job scheduling algorithm that analyze the nature of volunteer interference failures for effective scheduling of jobs.
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Nain, Philippe, Pantelis Tsoucas, and Jean Walrand. "Interchange arguments in stochastic scheduling." Journal of Applied Probability 26, no. 4 (December 1989): 815–26. http://dx.doi.org/10.2307/3214386.
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Interchange arguments are applied to establish the optimality of priority list policies in three problems. First, we prove that in a multiclass tandem of two ·/M/1 queues it is always optimal in the second node to serve according to the cµ rule. The result holds more generally if the first node is replaced by a multiclass network consisting of ·/M/1 queues with Bernoulli routing. Next, for scheduling a single server in a multiclass node with feedback, a simplified proof of Klimov's result is given. From it follows the optimality of the index rule among idling policies for general service time distributions, and among pre-emptive policies when the service time distributions are exponential. Lastly, we consider the problem of minimizing the blocking in a communication link with lossy channels and exponential holding times.
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Nain, Philippe, Pantelis Tsoucas, and Jean Walrand. "Interchange arguments in stochastic scheduling." Journal of Applied Probability 26, no. 04 (December 1989): 815–26. http://dx.doi.org/10.1017/s0021900200027686.
Full textAbstract:
Interchange arguments are applied to establish the optimality of priority list policies in three problems. First, we prove that in a multiclass tandem of two ·/M/1 queues it is always optimal in the second node to serve according to the cµ rule. The result holds more generally if the first node is replaced by a multiclass network consisting of ·/M/1 queues with Bernoulli routing. Next, for scheduling a single server in a multiclass node with feedback, a simplified proof of Klimov's result is given. From it follows the optimality of the index rule among idling policies for general service time distributions, and among pre-emptive policies when the service time distributions are exponential. Lastly, we consider the problem of minimizing the blocking in a communication link with lossy channels and exponential holding times.
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Reano, Carlos, Federico Silla, Dimitrios S. Nikolopoulos, and Blesson Varghese. "Intra-Node Memory Safe GPU Co-Scheduling." IEEE Transactions on Parallel and Distributed Systems 29, no. 5 (May 1, 2018): 1089–102. http://dx.doi.org/10.1109/tpds.2017.2784428.
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Zhang, Huanan. "Wireless sensor network node sleep scheduling algorithm." Journal of Physics: Conference Series 1976, no. 1 (July 1, 2021): 012038. http://dx.doi.org/10.1088/1742-6596/1976/1/012038.
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Et.al, Goo Kim. "A Study of BLE Mesh Network Scheduling Algorithm Using A Smartplug." Turkish Journal of Computer and Mathematics Education (TURCOMAT) 12, no. 6 (April 10, 2021): 456–51. http://dx.doi.org/10.17762/turcomat.v12i6.1865.
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This paper proposes a BLE Mesh network scheduling algorithm using SmartPlug. And proposes random-backoff, a very simple method for collision avoidance. The low-energy scheduling algorithm of SmartPlug and BLE node is proposed. SmartPlug periodically broadcasts its own information to inform the surrounding BLE nodes and SmartPlug. A node for data communication with SmartPlug is decided for efficiency. The BLE node periodically transmits data and switches to sleep mode after data transmission. In this paper, propose a very simple method, random-backoff, to reduce collisions when transmitting data in a BLE node. In the simulation of results shows when the data size is 1 ~ 31 bytes and 32 ~ 255 bytes, and random-backoff is effective when 1~31 bytes length. In the case of 32 to 255 bytes, random-backoff is not effective, so additional research is needed. And the simulation conducts under the same condition, but it shows that the data length and the number of transmission attempts has an effect. The simulation results show the transmission success ratio is similar regardless of the data length when random-backoff is not applied. It also shows the number of transmission attempts has an effect. Also, this simulation shows the results that as the number of nodes increases, the wireless environment becomes congested, and the transmission success ratio decreases. As a result of the simulation, random-backoff for collision avoidance is effective in transmitting data of 1 to 31 bytes better than 32 to 255 bytes in the data length.
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Luo, Xu, and Jun Yang. "Node scheduling in heterogeneous IoT systems with cluster topology." E3S Web of Conferences 95 (2019): 01004. http://dx.doi.org/10.1051/e3sconf/20199501004.
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IoT systems are heterogeneous network systems which consist of sensor terminals monitoring different objects. Terminal sensors have different sampling frequencies determined by minimum Nyquist sampling requirements. It is difficult to ensure synchronization when monitoring data of different sensors is transmitted to the data center. In consideration of sampling requirements of different terminals and in order to upload the sampling data timely and avoid data congestion, an applicable node scheduling scheme is necessary. In this paper node scheduling algorithms are proposed in hierarchical IoT systems with cluster topologies. The IoT systems include IoT alarming systems and IoT monitoring systems. In the simulation test, node scheduling methods are tested and the validity is demonstrated quantitatively.
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Kumari, Usha, and Udai Shankar. "COORDINATED DISTRIBUTED SCHEDULING IN WIRELESS MESH NETWORK." INTERNATIONAL JOURNAL OF COMPUTERS & TECHNOLOGY 3, no. 3 (November 22, 2012): 368–74. http://dx.doi.org/10.24297/ijct.v3i3a.2940.
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IEEE 802.16 based wireless mesh networks (WMNs) are a promising broadband access solution to support flexibility, cost effectiveness and fast deployment of the fourth generation infrastructure based wireless networks. Reducing the time for channel establishment is critical for low latency/interactive Applications. According to IEEE 802.16 MAC protocol, there are three scheduling algorithms for assigning TDMA slots to each network node: centralized and distributed the distributed is further divided into two operational modes coordinated distributed and uncoordinated distributed. In coordinated distributed scheduling algorithm, network nodes have to transmit scheduling message in order to inform other nodes about their transfer schedule. In this paper a new approach is proposed to improve coordinated distributed scheduling efficiency in IEEE 802.16 mesh mode, with respect to three parameter Throughput, Average end to end delay and Normalized Overhead. For evaluating the proposed networks efficiency, several extensive simulations are performed in various network configurations and the most important system parameters which affect the network performance are analyzed
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Song, Liang, and Dimitrios Hatzinakos. "Architecture of Wireless Sensor Networks with Mobile Sinks: Multiple Access Case." International Journal of Distributed Sensor Networks 3, no. 3 (July 2007): 289–310. http://dx.doi.org/10.1080/15501320601062130.
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We propose to develop Wireless Sensor Networks with Mobile Sinks (MSSN), under high sensor node density, where multiple sensor nodes need to share one single communication channel in the node-to-sink transmission. By exploiting the tradeoff between the successful information retrieval probability and the nodes energy consumption, a number of multiple nodes transmission scheduling algorithms are proposed. Both optimal and suboptimal algorithms, which exhibit exponential and linear complexity respectively, are discussed under the desired application. Computer simulations show that suboptimal algorithms perform nearly as good as the optimal one. The study leads to the cross-layer Wireless Link layer design for MSSN.