Gotowe bibliografie tematyczne / Node scheduling

Gotowa bibliografia na temat „Node scheduling”

Autor: Grafiati
Data publikacji: 4 czerwca 2021
Data aktualizacji: 1 lutego 2022

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Artykuły w czasopismach na temat "Node scheduling"

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Wang, Zhangquan, Yourong Chen, Banteng Liu, Haibo Yang, Ziyi Su i Yunkai Zhu. "A sensor node scheduling algorithm for heterogeneous wireless sensor networks". International Journal of Distributed Sensor Networks 15, nr 1 (styczeń 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 i Guangquan Xu. "A Node-Oriented Discrete Event Scheduling Algorithm Based on Finite Resource Model". Journal of Organizational and End User Computing 31, nr 3 (lipiec 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 i Ness B. Shroff. "Node weighted scheduling". ACM SIGMETRICS Performance Evaluation Review 37, nr 1 (15.06.2009): 97–108. http://dx.doi.org/10.1145/2492101.1555361.

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Feng, Juan, i Hongwei Zhao. "Energy-Balanced Multisensory Scheduling for Target Tracking in Wireless Sensor Networks". Sensors 18, nr 10 (22.10.2018): 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, nr 2 (10.04.2021): 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 i Mengqiu Tian. "Energy-Efficient Connected-Coverage Scheme in Wireless Sensor Networks". Sensors 20, nr 21 (28.10.2020): 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 i Zhigang Wen. "A Coverage Algorithm based on Key Node Scheduling". International Journal of Online Engineering (iJOE) 11, nr 9 (29.10.2015): 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 i 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 i Xiyan Sun. "Node-Subset Scheduling with a Subset-Reset Mechanism for the Decoding Algorithm of Nonbinary LDPC Codes". Mobile Information Systems 2021 (10.05.2021): 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 i M. Udin Harun Al Rasyid. "Dynamic Sleep Scheduling on Air Pollution Levels Monitoring with Wireless Sensor Network". EMITTER International Journal of Engineering Technology 5, nr 2 (13.01.2018): 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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Rozprawy doktorskie na temat "Node scheduling"

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Tian, Di. "Node activity scheduling schemes in large-scale wireless sensor networks". Thesis, University of Ottawa (Canada), 2005. http://hdl.handle.net/10393/29266.

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In wireless sensor networks that consist of a large number of low-power, short-lived, unreliable sensors, one of the main design challenges is to obtain long system lifetime without sacrificing sensing quality; i.e. sensing coverage in this context. In this thesis, we first propose a node-scheduling scheme, which can reduce system overall energy consumption, therefore increasing system lifetime, by identifying redundant nodes with respect to sensing coverage and then assigning them an off duty operation mode which has lower energy consumption than the normal on-duty mode. Our scheme aims at completely preserving original sensing coverage. Practically, sensing coverage degradation caused by location error, packet loss and node failure is very limited, not more than 1%, as shown by our experimental results. We implement the proposed scheme in NS-2, as an extension of the LEACH protocol and compare its energy consumption with the original LEACH. Simulation results exhibit noticeably longer system lifetime with our scheme as compared to earlier algorithm. The first scheme we propose aims at completely preserving sensing coverage. This, however, requires each node to get, in some way, the knowledge of its own and its neighbors' location information. Also, in that scheme, each node has to perform some calculations to determine whether to take an off-duty status. To alleviate these restrictions, we propose and study several alternative node-scheduling schemes, which cannot guarantee the complete preservation of the original system coverage, but are nonetheless more light-weighted and flexible than the previous one. The simulation results compare these schemes with the previous one and demonstrate their effectiveness. In a single wireless sensor network, sensors are performing two operations: sensing and communication. Therefore, there might exist two kinds of redundancy in the network. Most of the previous work addressed only one kind of redundancy: sensing or communication alone. Although there have been research efforts trying to combine consideration of coverage and connectivity maintenance in a single activity scheduling, their theoretical basis for safe scheduling integration condition is only applicable in those networks that are initially fully covered by sensors. Random node deployment often makes initial sensing holes inside the deployed area inevitable, even in an extremely high-density network. Therefore, in this thesis, we enhance these works to support general wireless sensor networks by proving another conclusion: "the communication range is twice the sensing range" is the sufficient condition and the tight lower bound to ensure that complete coverage preservation implies connectivity among active nodes, if the original network topology (consisting of all the deployed nodes) is connected. Also, we extend the results to k-degree network connectivity and k-degree coverage preservation.
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Khasawneh, Samer Fayiz. "Static Scheduling for Synchronous Data Flow Graphs". University of Akron / OhioLINK, 2007. http://rave.ohiolink.edu/etdc/view?acc_num=akron1184612284.

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SEETHARAMAN, SUMATHI. "SELF-ORGANIZED SCHEDULING OF NODE ACTIVITY IN LARGE-SCALE SENSOR NETWORKS". University of Cincinnati / OhioLINK, 2004. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1092939502.

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Pazand, Babak. "Location-free node scheduling schemes for energy efficient, fault tolerant and adaptive sensing in wireless sensor networks". University of Western Australia. School of Computer Science and Software Engineering, 2008. http://theses.library.uwa.edu.au/adt-WU2008.0185.

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Node scheduling is one of the most effective techniques to maximize the lifetime of a wireless sensor network. It is the process of selecting a subset of nodes to monitor the sensor field on behalf of redundant nodes. At every round of the scheduling a small group of nodes are active while the rest of the sensor nodes are in sleep mode. In this thesis, we propose a novel node scheduling solution for wireless sensor networks. The main characteristic of our approach is its independence from location information as well as distance information. Moreover, it does not rely on unrealistic circular radio propagation models. In order to have a comprehensive solution, we have considered different relations between sensing range and transmission range. When these ranges are equal in addition to the case that transmission range is higher than sensing range, we devise a node scheduling scheme based on the concept of Minimum Dominating Set. Two heuristics are presented to determine a collection of minimum dominating sets of the graph of the wireless sensor network. At each round of the scheduling only one set is active. Minimum dominating sets are scheduled to be rotated periodically. Moreover, every set is synchronized prior to the end of its active period in order to minimize the effect of clock drift of sensor nodes. Two components are considered to address node failures during the on-duty period of minimum dominating sets. These are probing environment and adaptive sleeping. The former is responsible for probing the working nodes of the active set to detect any node failure. The latter adjusts the frequency of probing for minimizing the overhead of probing while preserving an adequate level of robustness for discovery of node failure. This framework is based on the PEAS protocol that has been developed by Fan Ye et al. [98, 99]. We propose a different node scheduling scheme with a three-tier architecture for the case that sensing range is higher than transmission range. The coverage tier includes a set of nodes to monitor the region of the interest. We propose a heuristic to determine a collection of d-dominating sets of the graph of the wireless sensor network. At every round of the scheduling one d-dominating set forms the coverage tier. Connectivity tier consists of sensor nodes that relay the data collected at the coverage tier back to the base station. Finally, the coverage management tier is responsible for managing different patterns of coverage such as cyclic or uniform coverage.
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Mahfoudh, Saoucene. "Energy efficiency in wireless ad hoc and sensor networks : routing, node activity scheduling and cross-layering". Phd thesis, Université Pierre et Marie Curie - Paris VI, 2010. http://tel.archives-ouvertes.fr/tel-00757251.

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In this thesis, we consider wireless ad hoc and sensor networks where energy matters. Indeed, sensor nodes are characterized by a small size, a low cost, an advanced communication technology, but also a limited amount of energy. This energy can be very expensive, difficult or even impossible to renew. Energy efficient strategies are required in such networks to maximize network lifetime. We distinguish four categories of strategies: 1. Energy efficient routing, 2. Node activity scheduling, 3. Topology control by tuning node transmission power and 4. Reduction of the volume of information transferred. Our contribution deals with energy efficient routing and node activity scheduling. For energy efficient routing, the idea consists in reducing the energy spent in the transmission of a packet from its source to its destination, while avoiding nodes with low residual energy. The solution we propose, called EOLSR, is based on the link state OLSR routing protocol. We show by simulation that this solution outperforms the solution that selects routes minimizing the end-to-end energy consumption, as well as the solution that builds routes based on node residual energy. We then show how we can improve the benefit of energy efficient routing using cross layering. Informa- tion provided by the MAC layer improves the reactivity of the routing protocol and the robustness of routes. Moreover, taking into account the specificities of some applications like data gathering allows the routing protocol to reduce its overhead by maintaining routes only to the sink nodes. Concerning node activity scheduling, since the sleep state is the least power consuming state, our aim is to schedule node state between sleeping and active to minimize energy consumption while ensuring network and application functionalities. We propose a solution, called SERENA, based on node coloring. The idea is to assign a color to each node, while using a small number of colors and ensuring that two nodes with the same color can transmit without interfering. This color is mapped into a slot in which the node can transmit its messages. Consequently, each node is awake during its slot and the slots granted to its one-hop neighbors. It sleeps the remaining time. We show how this algorithm can adapt to different application requirements: broadcast, immediate acknowledgement of unicast transmissions... The impact of each additional requirement is evaluated by simulation. An originality of this work lies in taking into account real wireless propagation conditions. Color conflicts are then possible. A cross-layering approach with the MAC layer is used to solve these conflicts. We also show how cross-layering with the application layer can improve the coloring per- formance for data gathering applications. This work has been done for the ANR OCARI project whose aim is to design and implement a wireless sensor network for applications in harsh environments such as power plants and war- ships. The network layer including SERENA and EOLSR has been specified and is now under implementation.
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Fan, Yuqi. "Burst Scheduling, Grooming and QoS Provisioning in Optical Burst-Switched Networks". Wright State University / OhioLINK, 2009. http://rave.ohiolink.edu/etdc/view?acc_num=wright1239828363.

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Khan, Farhan, i Muhammad Umer Khan and Noman Ellahi. "Ad Hoc Network Nodes Scheduling using DS and FH CDMA". Thesis, Blekinge Tekniska Högskola, Sektionen för ingenjörsvetenskap, 2013. http://urn.kb.se/resolve?urn=urn:nbn:se:bth-4784.

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Nowadays most communication networks like GSM, WLan or WiMAX are based on pre-existing infrastructure. These infrastructures are complicated, costly and difficult to deploy in very short time. Whereas Wireless Ad Hoc Networks are infrastructure-free self organizing networks which consist of co-operating nodes. These networks are highly desirable for various emerging applications for military and to extend the range and capacity of infrastructure based wireless networks. One critical issue that we face in Ad Hoc Network is the problem of scheduling. Scheduling algorithms in an Ad Hoc Network allows the nodes to share the wireless channel efficiently. But on the other hand, the scheduling algorithm needs to be easily implementable in a distributed fashion with little, if any, coordination between nodes in the network. Spread spectrum technologies allow interference averaging and therefore are employed in Ad Hoc networks. There are two major types of spread spectrum physical layer, which are frequency hopping (FH) spread spectrum and direct sequence (DS) spread spectrum. FH-CDMA divides the bandwidth into M sub channels, the receiver only sees the interference from the transmitter side which is on the same sub channel whereas in DS-CDMA we increase the spreading code M to decrease the signal to interference plus noise ratio (SINR) requirement. The purpose of research is to study a hybrid spread spectrum based on physical layer, in which the direct sequence signal is also frequency hoped. The DS will reduce the region of dominating interferes, while frequency hopping will be used within this region intelligently and allow the dominating interferes to transmit on different frequencies. First the system bounds on the transmission capacity of the proposed scheme is evaluated, and than a comparative analysis of different multiple access schemes is done with our proposed model with respect to their transmission capacity to evaluate its performance.
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Schönemann, René [Verfasser], Jürgen [Akademischer Betreuer] Siegmann, Jürgen [Gutachter] Siegmann i Thomas [Gutachter] Siefer. "Scheduling rail freight node operations through a slot allocation approach / René Schönemann ; Gutachter: Jürgen Siegmann, Thomas Siefer ; Betreuer: Jürgen Siegmann". Berlin : Technische Universität Berlin, 2016. http://d-nb.info/1156181763/34.

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Bountourelis, Theologos. "Efficient pac-learning for episodic tasks with acyclic state spaces and the optimal node visitation problem in acyclic stochastic digaphs". Diss., Atlanta, Ga. : Georgia Institute of Technology, 2008. http://hdl.handle.net/1853/28144.

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Thesis (M. S.)--Industrial and Systems Engineering, Georgia Institute of Technology, 2009.
Committee Chair: Reveliotis, Spyros; Committee Member: Ayhan, Hayriye; Committee Member: Goldsman, Dave; Committee Member: Shamma, Jeff; Committee Member: Zwart, Bert.
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Bekono, Nina Pelagie. "Impact du changement du protocole de routage dans un réseau". Thesis, Université Clermont Auvergne‎ (2017-2020), 2018. http://www.theses.fr/2018CLFAC058/document.

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Les protocoles de routage dans les réseaux peuvent être amenés à changer pour de nombreuses raisons : la détection d'un événement particulier, un changement de topologie planifié ou non, la mobilité des nœuds, l'obsolescence de version, etc. Ces changements ne pouvant être simultanément détectés ou pris en compte par tous les nœuds du réseau, il est nécessaire de considérer le cas où certains nœuds utilisent le protocole de routage initial, tandis que d'autres ont migré vers le nouveau protocole de routage. Les travaux de cette thèse portent sur le problème de boucles de routage susceptibles d'apparaître dans ce contexte, et qui dégradent considérablement les performances du réseau. Nous proposons des solutions d'ordonnancement des nœuds, dans le but de contrôler la migration afin d'éviter ces boucles. Premièrement, nous considérons le contexte des réseaux statiques et des protocoles centralisés avec pour cas particulier le changement de métriques dans le réseau. Nous proposons deux solutions d'évitement des boucles centralisées : SCH-m (amélioration mineure d'un protocole existant), et ACH (nouvelle contribution), basées sur l'identification des boucles de routage dans les composantes connexes que contient l'union des deux protocoles de routage. Nous accélérons la migration du réseau par une opération de fusion étape par étape des différentes transitions produites. Deuxièmement, nous évoluons vers les protocoles distribués en conservant le contexte statique du réseau, et considérons le cas particulier du retrait ou de la panne d'un nœud. Nous proposons également deux solutions : RTH-d (amélioration mineure d'un protocole existant) et DLF (nouvelle contribution traitant les boucles de taille 2) basées sur un échange de messages entre les nœuds tant pour la détection de la panne que pour la notification de la migration. Troisièmement, nous considérons le contexte de mobilité des nœuds, et étudions les performances de DLF-k (version améliorée de DLF qui prend en compte les boucles de taille inférieures ou égales à k, avec k >= 2) sur deux types d'applications : les applications avec un unique nœud mobile qui est la destination, et les applications avec un groupe de nœuds mobiles
Routing protocols in networks may change for many reasons: detection of a particular event, planned or unplanned change of topology, mobility of nodes, version obsolescence, etc. As these changes can not be simultaneously detected or taken into account by all nodes of the network, it is necessary to consider the case where some nodes use the initial routing protocol, while others have migrated to the new routing protocol. The work of this thesis deals with the problem of routing loops that may appear in this context, and which considerably degrade the performance of the network. We propose node scheduling solutions to control migration to avoid these loops. First, we consider the context of static networks and centralized protocols with the particular case of changing metrics. We propose two centralized avoidance solutions: SCH-m (minor improvement of an existing heuristic), and ACH (new contribution), based on the identification of the routing loops in the strongly connected components contained in the union of the two routing protocols. We accelerate the migration of the network by a step-by-step merge operation of the different transitions produced. Second, we evolve towards the distributed protocols while preserving the static context of the network, and consider the particular case of the withdrawal or breakdown of a node. We also propose two solutions: RTH-d (minor improvement of an existing heuristic) and DLF (new contribution for loops of size 2) based on message exchange of nodes for both failure detection and for migration notification. Thirdly, we consider the context of nodes mobility, and study the performance of DLF- k (improved version of DLF which takes into account loops of size less than or equal to k, with k >= 2) on two types of applications: applications with a single mobile node that is the destination, and applications with a group of mobile nodes
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Książki na temat "Node scheduling"

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United Nations Commission on International Trade Law. Provisional agenda, annotations thereto and scheduling of meetings of the twenty-fifth session: Note by the Secretariat. [New York]: United Nations General Assembly, 1992.

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United Nations Commission on International Trade Law. Provisional agenda, annotations thereto and scheduling of meetings of the twenty-seventh session: Note by the Secretariat. [New York]: United Nations General Assembly, 1994.

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Yuan lai shou zhang zhe yang wan. Xinbei Shi Xindian Qu: Ye ren wen hua gu fen you xian gong si, 2014.

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translator, Chen Huili, red. Maikenxi de bi ji shu: Ding jian gu wen de si kao, shu xie ji qiao = The McKinsey way : techniques for taking notes on problem-solving = Makkinzē no erīto wa nōto ni nani o kaite iru noka : toppu konsarutanto no kangaeru gijutsu kaku gijutsu. 2015.

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Części książek na temat "Node scheduling"

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Kesidis, George. "Bandwidth Scheduling for a Single Node". W ATM Network Performance, 35–53. Boston, MA: Springer US, 1996. http://dx.doi.org/10.1007/978-1-4757-4568-9_3.

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Kesidis, George. "Bandwidth Scheduling for a Single Node". W ATM Network Performance, 41–68. Boston, MA: Springer US, 2000. http://dx.doi.org/10.1007/978-1-4615-4559-0_3.

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Pereira, Romain, Adrien Roussel, Patrick Carribault i Thierry Gautier. "Communication-Aware Task Scheduling Strategy in Hybrid MPI+OpenMP Applications". W OpenMP: Enabling Massive Node-Level Parallelism, 197–210. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-85262-7_14.

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Tsujita, Yuki, i Toshio Endo. "Data Driven Scheduling Approach for the Multi-node Multi-GPU Cholesky Decomposition". W Job Scheduling Strategies for Parallel Processing, 69–82. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-61756-5_4.

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Wan, Michael, Reagan Moore, George Kremenek i Ken Steube. "A batch scheduler for the Intel Paragon with a non-contiguous node allocation algorithm". W Job Scheduling Strategies for Parallel Processing, 48–64. Berlin, Heidelberg: Springer Berlin Heidelberg, 1996. http://dx.doi.org/10.1007/bfb0022287.

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Nakamura, Fabíola Guerra, Frederico Paiva Quintão, Gustavo Campos Menezes i Geraldo Robson Mateus. "An Optimal Node Scheduling for Flat Wireless Sensor Networks". W Networking - ICN 2005, 475–82. Berlin, Heidelberg: Springer Berlin Heidelberg, 2005. http://dx.doi.org/10.1007/978-3-540-31956-6_56.

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Jiang, Jie, Zhen Song, Heying Zhang i Wenhua Dou. "On Lightweight Node Scheduling Scheme for Wireless Sensor Networks". W Distributed Computing – IWDC 2005, 318–28. Berlin, Heidelberg: Springer Berlin Heidelberg, 2005. http://dx.doi.org/10.1007/11603771_35.

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Xiangyu, Wang. "Node Wake-Up Scheduling Mechanism for Delay Tolerant Networks". W Advances in Computer Science, Intelligent System and Environment, 495–500. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-23756-0_79.

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Huang, Liang. "Energy Harvesting Sensor Node Scheduling in Wireless Sensor Networks". W Encyclopedia of Wireless Networks, 411–14. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-319-78262-1_260.

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Huang, Liang. "Energy Harvesting Sensor Node Scheduling in Wireless Sensor Networks". W Encyclopedia of Wireless Networks, 1–4. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-32903-1_260-1.

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Streszczenia konferencji na temat "Node scheduling"

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Gupta, Gagan R., Sujay Sanghavi i Ness B. Shroff. "Node weighted scheduling". W the eleventh international joint conference. New York, New York, USA: ACM Press, 2009. http://dx.doi.org/10.1145/1555349.1555361.

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Abawajy, Jemal H., Saeid Nahavandi i Fahed Al-Neyadi. "Sensor Node Activity Scheduling Approach". W 2007 International Conference on Multimedia and Ubiquitous Engineering (MUE'07). IEEE, 2007. http://dx.doi.org/10.1109/mue.2007.190.

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Wu, Yue, Zhongru Wang, Qiang Ruan, Jinyu Shi i Binxing Fang. "Node Scheduling: A Blockchain-Based Node Selection Approach on Sapiens Chain". W 2019 IEEE International Conference on Big Data and Smart Computing (BigComp). IEEE, 2019. http://dx.doi.org/10.1109/bigcomp.2019.8679303.

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Zhang, Zeqi, Chunxiao Jiang, Song Guo, Zuyao Ni i Yong Ren. "Optimal Satellite Scheduling with Critical Node Analysis". W 2017 IEEE Wireless Communications and Networking Conference (WCNC). IEEE, 2017. http://dx.doi.org/10.1109/wcnc.2017.7925895.

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Sarkar, Chayan, R. Venkatesha Prasad, Raj Thilak Rajan i Koen Langendoen. "Sleeping Beauty: Efficient Communication for Node Scheduling". W 2016 IEEE 13th International Conference on Mobile Ad Hoc and Sensor Systems (MASS). IEEE, 2016. http://dx.doi.org/10.1109/mass.2016.018.

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Tak, Sungwoo, Hangeul Kim, Donglyul Kim i Yougyung Kim. "Energy-Aware Scheduling for Sensor Node Platforms". W 2014 15th International Conference on Parallel and Distributed Computing, Applications and Technologies (PDCAT). IEEE, 2014. http://dx.doi.org/10.1109/pdcat.2014.18.

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Hakim, Hela, Wessam Ajib i Hatem Boujemaa. "Scheduling schemes for N-node cooperative networks". W 2010 17th International Conference on Telecommunications (ICT 2010). IEEE, 2010. http://dx.doi.org/10.1109/ictel.2010.5478648.

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Ji, Bo, i Jie Wu. "Node-based scheduling with provable evacuation time". W 2015 49th Annual Conference on Information Sciences and Systems (CISS). IEEE, 2015. http://dx.doi.org/10.1109/ciss.2015.7086428.

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Jun, QIN, SONG Yanyan i ZONG Ping. "Research on Task Scheduling Strategy based on the Trustworthiness of MapReduce". W International Conference on AI, Machine Learning and Applications (AIMLA 2021). Academy and Industry Research Collaboration Center (AIRCC), 2021. http://dx.doi.org/10.5121/csit.2021.111304.

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Streszczenie:
With the rapid development and popularization of information technology, cloud computing technology provides a good environment for solving massive data processing. Hadoop is an open-source implementation of MapReduce and has the ability to process large amounts of data. Aiming at the shortcomings of the fault-tolerant technology in the MapReduce programming model, this paper proposes a reliability task scheduling strategy that introduces a failure recovery mechanism, evaluates the trustworthiness of resource nodes in the cloud environment, establishes a trustworthiness model, and avoids task allocation to low reliability node, causing the task to be re-executed, wasting time and resources. Finally, the simulation platform CloudSim verifies the validity and stability of the task scheduling algorithm and scheduling model proposed in this paper.
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Snoussi, Hichem, i Cedric Richard. "Information-theoretic node scheduling in collaborative sensor networks". W 2007 9th International Symposium on Signal Processing and Its Applications (ISSPA). IEEE, 2007. http://dx.doi.org/10.1109/isspa.2007.4555503.

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