Static and dynamic minimum energy broadcast problem in wireless ad-hoc networks: A PSO-based approach and analysis

Hsiao, Ping-Che; Chiang, Tsung-Che; Fu, Li‐Chen

doi:10.1016/j.asoc.2013.08.008

Cited by 10 publications

(9 citation statements)

References 42 publications

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“…The MEB problem has been proved to be NP-hard and a flurry of heuristic algorithms have been proposed [14]- [19]. Local search is usually employed to integrate with other algorithms for solving the MEB problem, such as nested partitioning and linear programming [16], swarm optimization (PSO) [17] and genetic algorithm (GA) [18]. GA based approach may drop into local optimal solutions or may find the optimal solution by slow convergence speed.…”

Section: Related Work and Paper Contributionsmentioning

confidence: 99%

Energy Efficient Resource Allocation and Scheduling for Delay-Constrained Multi-Cell Broadcast Networks

2020

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Resource allocation in wireless cellular networks has been an important and challenging issue. With the rapid development of wireless communications, more and more mobile multimedia and innovative applications (e.g. augmented reality and video conferences) have emerged, which are suitable for wireless broadcast and have requirements on transmission delay. In this paper, we focus on delayconstrained multi-cell broadcast networks, taking user mobility into consideration for future channel estimation. The promising network coding technique is also adopted to improve transmission efficiency. The objective is to minimize total transmission energy consumption via joint resource allocation and scheduling optimization. Both optimal and heuristic solutions are proposed. Simulation results show that the proposed schemes perform better than other benchmark schemes, in terms of transmission energy consumption and success rate.

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Section: Related Work and Paper Contributionsmentioning

confidence: 99%

Energy Efficient Resource Allocation and Scheduling for Delay-Constrained Multi-Cell Broadcast Networks

2020

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“…Čagalj et al (2002) prove that MEB, and thereby MEM, is NP-hard. Numerous contributions to fast, but possibly inexact methods for MEM have thus appeared, and the interested reader is referred to (Hsiao et al 2013) for an overview. Another study concerning MEM is the work by Guo and Yang (2004), who investigate energy conservation while using adaptive antennas.…”

Section: Literature Overviewmentioning

confidence: 99%

Integer programming formulations for the shared multicast tree problem

Ivanová

Haugland

2019

J Comb Optim

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We study the Shared Multicast Tree (SMT) problem in wireless networks. To support a multicast session between a set of network nodes, SMT aims to establish a wireless connection between them, such that the total energy consumption is minimized. All destinations of the multicast message must be connected, while non-destinations are optional nodes that can be used to relay messages. The objective function reflecting power consumption distinguishes SMT clearly from the traditional minimum Steiner tree problem. We develop two integer programming formulations for SMT. Both models are subsequently extended and strengthened. Theorems on relations between the LP bounds corresponding to the models are stated and proved. As the number of variables in the strongest formulations is a polynomial of degree four in the number of network nodes, the models are impractical for computing lower bounds in instances beyond a fairly small size, and therefore a constraint generation scheme is developed. Results from computational experiments with the models demonstrate good promise of the approaches taken.

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“…Performance measures taken into account for comparison and evaluation purpose includes loss ratio, control overhead, Packet delivery ratio, latency and energy efficiency and lifetime of network. In the year 2013, Hsiao, Ping-Che, Tsung-Che Chiang, and Li-Chen Fu [48] author proposed algorithm comprises of PSO and Intensified r-shrink procedure for efficient local search. The algorithm has been mapped with the problem as follows: Power degree encoding is used for solution reorientation.…”

Section: Other Evolutionary Algorithm Based Solution Modelsmentioning

confidence: 99%

Minimum Energy Broadcasting Problem in Wireless Sensor Network: A Review

Mohamed¹

2019

IJATCSE

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Construction of MEB tree is one of the emerging problem in WSN which have the tendency of keeping the lifetime of the network alive. This minimum energy broadcasting tree has been constructed previously with the use of exact algorithms and some heuristic algorithms for minimum energy consumption. Later after bio inspired algorithms comes into lime light for solving combinatorial optimization problems MEB grasps a number of researchers for solving it. This part of interest leads the researchers to produce many algorithms for solving MEB along with hybrid models for efficient local search procedure. In this paper a survey of MEB solved methods using generic solutions and bio-inspired algorithms are provided. Literature survey based on evolutionary algorithms provides, author, title of the paper, year of publication, issues described, constraints considered, mapping of MEB with the proposed method, algorithm used for solving MEB, modifications taken over original algorithm, need for the modification, performance measures, parameters used, algorithms compared with the proposed method are provided. Along with this some of the papers holds advantages and disadvantages of the proposed from this Thesis author's point of view.

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Static and dynamic minimum energy broadcast problem in wireless ad-hoc networks: A PSO-based approach and analysis

Cited by 10 publications

References 42 publications

Energy Efficient Resource Allocation and Scheduling for Delay-Constrained Multi-Cell Broadcast Networks

Energy Efficient Resource Allocation and Scheduling for Delay-Constrained Multi-Cell Broadcast Networks

Integer programming formulations for the shared multicast tree problem

Minimum Energy Broadcasting Problem in Wireless Sensor Network: A Review

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