Joint Topology-Transparent Scheduling and QoS Routing in Ad Hoc Networks

Su, Yi-Sheng; Su, Szu‐Lin; Li, Jung-Shian

doi:10.1109/tvt.2013.2274806

Cited by 12 publications

(8 citation statements)

References 42 publications

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“…And this paper [10] develops a theoretical model for estimating the available bandwidth of a path based on interference from both background traffic and traffic along the path. The researcher shows that the clique constraint widely used to construct upper bounds does not hold any more when links are allowed to use different rates at different time.…”

Section: Related Workmentioning

confidence: 99%

The Effect of the Multi-Objective Dynamic Metric on the QoS and the Energy in Networks Manets

Lakki¹,

Oubaha²,

Ouacha³

et al. 2019

Int. J. Recent Contrib. Eng. Sci. IT

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<p>The first aim of this article is to find a Intelligent parameter which is based on mobility and Clustering. This metric will be integrate in the selection process of MPRs to improve QoS in Manets networks. The unpredictable mobility and the large quantity of generated traffic by each node interface make communication in network increasingly difficult to manage. Thus, routing protocols need to be adapted to such conditions. In order to make OLSR protocol more robust, piercing and more adaptable to the conditions dictated by the environment of each node, this work proposes a polymorphic metric that changes depending on the network behavior. This metric aims to make the OLSR protocol best suited to each zone. The second objective of this article is to know the behavior of the new OLSR protocol version (SPEED OLSR) in environments with high mobility (pause time = 0).</p><p>To know the effectivity of the speed of the parameters have several criteria. Many simulations would be undergone by NS2 to test and prove the validity of this new metric in environments with high mobility and quantity of traffic</p>

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Section: Related Workmentioning

confidence: 99%

The Effect of the Multi-Objective Dynamic Metric on the QoS and the Energy in Networks Manets

Lakki¹,

Oubaha²,

Ouacha³

et al. 2019

Int. J. Recent Contrib. Eng. Sci. IT

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“…On one hand, there has been much work involved in deterministic algorithms [4], such as the genetic algorithm and the ant colony algorithm, which could finally find optimal solutions for this problem, while the time complexity grows exponentially with the increase of network nodes. On the other hand, there also has been much work involved in designing heuristic solutions for this problem [5][6][7][8][9][10][11][12][13], and they can find multicast trees close to the optimal multicast tree in feasible time, which is more suitable for network multicast use, due to the computing and processing performance of network nodes.…”

Section: Introductionmentioning

confidence: 99%

A Novel QoS Provisioning Algorithm for Optimal Multicast Routing in WMNs

Yang¹,

Chen²

2016

Future Internet

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Abstract:The problem of optimal multicast routing in Wireless Mess Networks (WMNs) with Quality-of-Service (QoS) provisioning, which is Non-Deterministic Polynomial (NP)-complete, is studied in this paper. The existing algorithms are not very efficient or effective. In order to find an approximation optimal solution for WMNs in feasible time from source to the set of destination nodes, combining the previous deterministic algorithm with the well-known Minimum Path Cost Heuristic (MPH) algorithm, a novel multicast heuristic approximation (NMHA) algorithm with QoS provisioning is proposed in this paper to deal with it. The theoretical validations for the proposed algorithm are presented to show its performance and efficiency. After that, the random static networks with different destination nodes are evaluated. Simulations in these networks show that the proposed algorithm can achieve the approximate optimal solution with the approximation factor of 2(1 + ε)(1´1/q) and the time complexity of O(qmn 2 τ K´1 ).

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“…Their algorithms resort to rounding and scaling to guarantee a solution within a factor (1 )   of the optimal solution. Other works that consider graph models with fixed edge weighs and employing the approximation algorithm for finding the optimal multicast routing tree or the optimal path can be found in [10][11][12][13][14][15][16][17].…”

Section: Introductionmentioning

confidence: 99%