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Journal ArticleDOI

A genetic approach to joint routing and link scheduling for wireless mesh networks

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TLDR
This paper investigates the joint link scheduling and routing issues involved in the delivery of a given backlog from any node of a wireless mesh network towards a specific node (which acts as a gateway), within a given deadline.
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Journal ArticleDOI

Routing, scheduling and channel assignment in Wireless Mesh Networks: Optimization models and algorithms

TL;DR: This paper studies the radio resource assignment optimization problem in Wireless Mesh Networks assuming a time division multiple access (TDMA) scheme, a dynamic power control able to vary emitted power slot-by-slot, and a rate adaptation mechanism that sets transmission rates according to the signal-to-interference-and-noise ratio (SINR).
Journal ArticleDOI

Genetic algorithms in wireless networking: techniques, applications, and issues

TL;DR: This paper is the first paper, to the best of the knowledge, which focuses on Genetic algorithms application in wireless networks and provides both an exposition of common GA models and configuration and a broad-ranging survey of GA techniques in Wireless networks.
Book ChapterDOI

GAR: An Energy Efficient GA-Based Routing for Wireless Sensor Networks

TL;DR: A Genetic algorithm based routing scheme called GAR (Genetic Algorithm-based Routing) that considers the energy consumption issues by minimizing the total distance travelled by the data in every round and is better than the existing techniques in terms of network life time, energy consumption and the totaldistance covered in each round.
Journal Article

Solving the Wireless Mesh Network Design Problem using Genetic Algorithm and Simulated Annealing Optimization Methods

TL;DR: In this paper, the authors used a genetic algorithm and simulated annealing to enable searching for a low-cost WMN configuration with constraints and determine the number of used gateways.
Journal ArticleDOI

Network-Lifetime Maximization of Wireless Sensor Networks

TL;DR: The optimal but excessive-complexity algorithm, namely, the exhaustive search algorithm (ESA) and a near-optimal single objective genetic algorithm (SOGA) exhibiting a reduced complexity in a fully connected WSN.
References
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Book

Genetic Algorithms + Data Structures = Evolution Programs

TL;DR: GAs and Evolution Programs for Various Discrete Problems, a Hierarchy of Evolution Programs and Heuristics, and Conclusions.
Journal ArticleDOI

The capacity of wireless networks

TL;DR: When n identical randomly located nodes, each capable of transmitting at W bits per second and using a fixed range, form a wireless network, the throughput /spl lambda/(n) obtainable by each node for a randomly chosen destination is /spl Theta/(W//spl radic/(nlogn)) bits persecond under a noninterference protocol.
Book

Integer programming

TL;DR: The principles of integer programming are directed toward finding solutions to problems from the fields of economic planning, engineering design, and combinatorial optimization as mentioned in this paper, which is a standard of graduate-level courses since 1972.
Journal ArticleDOI

Wireless mesh networks: a survey

TL;DR: This paper presents a detailed study on recent advances and open research issues in WMNs, followed by discussing the critical factors influencing protocol design and exploring the state-of-the-art protocols for WMNs.
Journal ArticleDOI

Theoretical and numerical constraint-handling techniques used with evolutionary algorithms: a survey of the state of the art

TL;DR: A comprehensive survey of the most popular constraint-handling techniques currently used with evolutionary algorithms, including approaches that go from simple variations of a penalty function, to others, more sophisticated, that are biologically inspired on emulations of the immune system, culture or ant colonies.
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