Distributed Multicast Tree Construction in Wireless Sensor Networks

Gong, Hongyu; Fu, Luoyi; Fu, Xinzhe; Zhao, Lutian; Wang, Kainan; Wang, Xinbing

doi:10.1109/tit.2016.2623317

Cited by 45 publications

(15 citation statements)

References 31 publications

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“…This method has good scalability, but it does not consider the influence of network congestion. Gong et al [28] proposed a multicast tree building method based on the Steiner tree in order to achieve lower cost and lower power consumption. Aibin et al [29] focus on a problem related to joint optimization of unicast, anycast, and multicast traffic.…”

Section: Related Workmentioning

confidence: 99%

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Q-Learning Based Content Placement Method for Dynamic Cloud Content Delivery Networks

Liu¹,

Lu²,

Zhang³

et al. 2019

IEEE Access

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How to reduce the content placement cost of cloud content delivery networks (CCDNs) is a hot topic in recent years. Traditional content placement methods mainly reduce the cost of content placement by constructing delivery trees, but they cannot adapt to the dynamic deployment of cloud proxy servers in the CCDNs. In addition, the traditional content placement method only provides delivery paths according to local decision-making without considering global dynamics of the congestion in the CCDNs, which is also one of the main factors causing high cost of content placement. To solve these problems, we propose a content placement model based on Q-learning for the dynamic CCDNs, called Q-content placement model (Q-CPM). This Q-learning approach can lead to better routing decisions due to up-to-date and more reliable congestion values. Then, based on the Q-CPM model, an algorithm is proposed to construct the Q-adaptive delivery tree (Q-ADT). In this algorithm, local and nonlocal congestion information is propagated over network learning packets. Through this algorithm, the paths with low congestion cost will be selected and can adapt to the dynamic cloud delivery environment. The experimental results show that the method can adapt to the dynamic changes of the CCDNs flexibly and reduce the overall congestion cost of content placement effectively.

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Section: Related Workmentioning

confidence: 99%

“…Many people model delivery tree optimization problems as Steiner tree problems. The Toward Source Tree (TST) [28] is a Steiner tree approximation algorithm to generate approximate Steiner Trees. Therefore, we compare the proposed algorithm with TST.…”

Section: Experimental Analysismentioning

confidence: 99%

Q-Learning Based Content Placement Method for Dynamic Cloud Content Delivery Networks

Liu¹,

Lu²,

Zhang³

et al. 2019

IEEE Access

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“…Finally, the mobile sink visits the sub-trees to collect data and to reconstruct them when their residual energy is low. In [8], the authors present an algorithm called Toward Source Tree (TST) that constructs a tree which forwards information from a source to multiple receivers (i.e., a multicast tree). TST aims at minimizing the tree length and, as a consequence, the delay.…”

Section: Related Workmentioning

confidence: 99%

Dynamic minimum spanning tree construction and maintenance for Wireless Sensor Networks

Diaz

Méndez

2019

Rev.Fac.Ing.Univ.Antioquia

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In a wireless sensor network (WSN), finding the optimal route from each node to the sink is not a straightforward task because of the distributed and dynamic characteristics of the network. For instance, the network suffers frequent changes because the channel quality varies over time and the nodes can leave or join the network at any moment. In order to deal with this variability, we propose the Dynamic Gallager-Humblet-Spira (DGHS) algorithm that builds and maintains a minimum spanning tree for distributed and dynamic networks, and we have found that DGHS reduces the number of control messages and the energy consumption, at the cost of a slight increase in the memory size and convergence time. This paper presents a detailed description of the different stages of the DGHS algorithm (neighbor discovery, tree construction and data collection), an in-depth analysis of extensive results that validates our proposal, and an exhaustive description of the GHS limitations.

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“…Wu et al [16] proposed energy efficient bandwidth aggregation strategy which aggregate energy rate adaption, constrained delay unequal protection and quality packet distribution to leverage energy conservation and minimize end to end delay in wireless network [17]. Aiming to minimize energy consumption, Gong et al [18] explored the transmission from origin server to multiple receivers and construct a minimum multicast tree. Fu et al [19] studied the problem of minimum energy consumption and proposed a framework for optimizing energy transmission in delay constrained wireless networks, where information from the source server distributed to all the k destinations.…”

Section: Related Work a Content Placement Algorithmmentioning

confidence: 99%

Cost Optimization for the Coupled Video Delivery Networks

Chen

Zhang

et al. 2019

IEEE Access

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Video delivery networks (VDNs) are one of the key enablers for alleviating contradiction between demands increasing for online video and response time of users accessing video content. However, existed works mainly adopt either proactive or reactive delivery scheme, which leads to the problems of backbone traffic overloaded and delays increased. In these works, the impact of performance indicators, such as bandwidth, delay, and personalized demand on delivery cost are not comprehensively taken into account. To overcome these problems, we propose a cost optimization for coupled video delivery model (CO-CVDM), which combines coupled proactive delivery and coupled reactive delivery method to minimize delivery cost in terms of bandwidth consumption, delay performance, personalized demand and construct a multicast delivery tree for the video delivery. The coupled delivery cost minimization problem under constraint conditions is formulated. Since this problem is NP-hard and is prohibitively difficult to solve, we develop a heuristic multicast delivery tree (HMDT) algorithm to provide more optimized approximate cost. Based on this, we extend CO-CVDM to distribute video in a dynamic scenario. Specifically, with dynamic change of user's requirement for video, the process of video delivery is truncated into a sequence of static graphs and the change of interest attenuation is modeled with human forgetting curve. Finally, the numerical simulations are conducted to validate the advantage of CO-CVDM in terms of optimization delivery cost, and the delivery cost is inversely proportional to the attenuation of user interest. INDEX TERMS Coupled video delivery, cost optimization, bandwidth, delay, personalized demand.

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Distributed Multicast Tree Construction in Wireless Sensor Networks

Cited by 45 publications

References 31 publications

Q-Learning Based Content Placement Method for Dynamic Cloud Content Delivery Networks

Q-Learning Based Content Placement Method for Dynamic Cloud Content Delivery Networks

Dynamic minimum spanning tree construction and maintenance for Wireless Sensor Networks

Cost Optimization for the Coupled Video Delivery Networks

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