Higher power relay nodes can be used as cluster heads in two-tiered sensor networks to achieve improved network lifetime. The relay nodes may form a network among themselves to route data towards the base station. In this model, the lifetime of a network is determined mainly by the lifetimes of these relay nodes. An energy-aware communication strategy can greatly extend the lifetime of such networks. However, integer linear program (ILP) formulations for optimal, energy-aware routing quickly become computationally intractable and are not suitable for practical networks. In this paper, we have proposed an efficient solution, based on a genetic algorithm (GA), for scheduling the data gathering of relay nodes, which can significantly extend the lifetime of a relay node network. For smaller networks, where the global optimum can be determined, our GA based approach is always able to find the optimal solution. Furthermore, our algorithm can easily handle large networks, where it leads to significant improvements compared to traditional routing schemes.

A genetic algorithm based approach for energy efficient routing in two-tiered sensor networks

Computational intelligence in photonics technology and optical networks: A survey and future perspectives

A wireless sensor network (WSN) is a large-scale ad-hoc multi-hop network deployed (usually, at random) in a region of interest for surveillance purpose. Coverage is one of the important aspects of wireless sensor networks and many approaches are introduced to maximize it. In this paper we propose a novel approach for maximizing coverage. Voronoi diagram divides the field into cells and inside of each cell some holes exist. Additional nodes must be placed inside cells to cover the holes. Genetic algorithm is used to determine best places for additional nodes maximizing the coverage. Optimal placement of nodes can guarantee the maximum coverage with less number of nodes and energy consumption decreases. Simulations results show that our new approach can outperform other earlier works.

Node Placement for Maximum Coverage Based on Voronoi Diagram Using Genetic Algorithm in Wireless Sensor Networks

https://ir.nctu.edu.tw:443/bitstream/11536/9852/1/000262946000004.pdf

Multicast routing and wavelength assignment with delay constraints in WDM networks with heterogeneous capabilities

In this paper, we propose an integrated Quality of Service (QoS) routing algorithm for optical networks. Given a QoS multicast request and the delay interval specified by users, the proposed algorithm can find a flexible-QoS-based cost suboptimal routing tree. The algorithm first constructs the multicast tree based on the multipopulation parallel genetic simulated annealing algorithm, and then assigns wavelengths to the tree based on the wavelength graph. In the algorithm, routing and wavelength assignment are integrated into a single process. For routing, the objective is to find a cost suboptimal multicast tree. For wavelength assignment, the objective is to minimize the delay of the multicast tree, which is achieved by minimizing the number of wavelength conversion. Thus both the cost of multicast tree and the user QoS satisfaction degree can approach the optimal. Our algorithm also considers load balance. Simulation results show that the proposed algorithm is feasible and effective. We also discuss the practical realization mechanisms of the algorithm.

/pdf/a-multipopulation-parallel-genetic-simulated-annealing-based-1rx69g4cqh.pdf

A multipopulation parallel genetic simulated annealing-based QoS routing and wavelength assignment integration algorithm for multicast in optical networks

Because optical WDM networks will become a realistic choice for buildings backbones, multicasting in the WDM network should be supported for various network applications. In this paper, a new multicast problem, Multicast Routing under Delay Constraint Problem (MRDCP), routing a request with delay bound to all destinations in a WDM network with different light splitting is solved by genetic algorithms (GAs), where different light splitting means that nodes in the network can transmit one copy or multiple copies to other nodes by using the same wavelength. The MRDCP can be reduced to the Minimal Steiner Tree Problem (MSTP) which has been shown to be NP-Complete. We propose a destination-oriented representation to represent chromosomes, three general genetic operators (selection, crossover, and mutation), four types of operators (Chromosome Crossover, Individual Crossover, Chromosome Mutation, and Individual Mutation). Four mutation heuristics (Random Mutation (RM), Cost First Mutation (CFM), Delay First Mutation (DFM), and Hybrid Mutation (HM)) are employed in the GA method. Finally, experimental results show that our solution model can obtain a near optimal solution.

A Genetic Algorithm for Multicast Routing under Delay Constraint in WDM Network with Different Light Splitting

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A Genetic Algorithm for Multicast Routing under Delay Constraint in WDM Network with Different Light Splitting