An efficient genetic algorithm approach for solving routing and spectrum assignment problem

Hai, Dao Thanh; Hoàng, Mạnh Kha

doi:10.1109/sigtelcom.2017.7849820

Cited by 22 publications

(6 citation statements)

References 24 publications

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“…In line of these, a heuristic‐based genetic algorithm (GA) approach for solving static RSA problem in EONs was proposed in the work of Hai and Hoang 7 . The GA provides near optimal solution for the problem in manageable running time and minimize spectrum bandwidth requirement as compared to the exact approaches based on the ILP (integer linear programming) model and other traditional heuristic approaches.…”

Section: Related Workmentioning

confidence: 99%

“…The conventional wavelength division multiplexing (WDM) technology‐based optical networks are inefficient to fulfill the present need. In WDM networks, the minimum bandwidth allocation size is 50 GHz, which is fixed and rigid in nature 7,8 . However, the requested bandwidth by a connection request is less than the minimum bandwidth size, leading to increase the wastage of spectrum bandwidth in WDM networks.…”

Section: Introductionmentioning

confidence: 99%

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Cost function‐based class of service provisioning strategy in elastic optical networks

Dixit

Batham

Narwaria

2020

Int J Communication

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SummaryThe recent fog‐and‐cloud computing, Internet of things (IoT), artificial intelligence, machine learning, and store‐and‐forward datacenter applications gradually increase the Internet traffic. The arrival of this traffic is periodic, which remains high during certain time duration (known as peak or working/office hour) each day, resulting in an increase in the resource bottleneck problem, which causes high connections blocking. Due to these, many commercial and business data services may lose their connections which contain the urgent and important information. In order to handle such a critical situation in elastic optical networks (EONs), prioritization of connection requests based on the differentiated class of service (CoS) is a must. In this paper, the network traffic is categorized into three CoS requests. These are CoS1 (real‐time traffic), CoS2 (nonreal‐time traffic), and CoS3 (delay‐tolerant traffic) and proposed a cost function‐based CoS provisioning (CFCoSP) strategy in which the connection requests are served as per an increasing value of cost function. The cost function is a cumulative function of CoS, pathlength, and requested bandwidth demand (i.e., number of frequency slots required). The simulations are performed on INDIAN and ARPANET network topologies under uniform CoS ratio (i.e., CoS1:CoS2:CoS3 = 1:1:1) on the metrics of connection established, bandwidth blocking probability, resource utilization ratio, and network capacity utilization. The simulation results verify that the proposed CFCoSP strategy shows significantly improved performances as compared to an existing non‐cost CoS provisioning (CoSP) strategy on the investigated metrics.

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Section: Related Workmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Cost function‐based class of service provisioning strategy in elastic optical networks

Dixit

Batham

Narwaria

2020

Int J Communication

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“…Airlines also use GAs to help create flight schedules [10], and crew management. Numerous other wireless applications of GAs have been explored by researchers in papers [11], [12] moreover, GA has promising results in routing and spectrum assignments (RSA) [13]- [15]. Researchers have even recently discovered a potential use of GA in cryptanalysis [16], recruitment systems [17], course scheduling [18], and various other fields [19], [20].…”

Section: Introductionmentioning

confidence: 99%

Analysis and comparison of a proposed mutation operator and its effects on the performance of genetic algorithm

Ullah

Salam²,

Masood³

2022

IJEECS

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Genetic algorithms (GAs) are dependent on various operators and parameters. The most common evolutionary operators are parent selection, crossover, and mutation. Each operator has broad implementations with its pros and cons. A successful GA is highly dependent on genetic diversity which is the main driving force that steers a GA towards an optimal solution. Mutation operator implements the idea of exploration to search for uncharted areas and introduces diversity in a population. Thus, increasing the probability of GA to converge to a globally optimum solution. In this paper, a new variant of mutation operator is proposed, and its functions are studied and compared with the existing operators. The proposed mutation operator as well as others such as m-mutation, shuffle, swap, and inverse are tested for their ability to introduce diversity in population and hence, their effects on the performance of GA. All these operators are applied to Max one problem. The results concluded that the proposed variant is far more superior to the existing operators in terms of introducing diversity and hence early convergence to an optimum solution.

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“…Furthermore, various studies carried out towards securing sensors in WSN where the discussion has been carried out towards the need for further improvement in the data aggregation process [14]- [19]. Apart from this, various optimization approaches [20]- [22], as well as studies towards quality of services [23], [24], have also been presented toward improving data transmission in WSN. The existing system [25] reports incorporating the intelligence in the mobile agents in WSN to enhance its performance towards autonomy, executability, and mobility.…”

Section: Introductionmentioning

confidence: 99%

Energy-efficient data-aggregation for optimizing quality of service using mobile agents in wireless sensor network

Basappa¹,

Shobha²,

Thanuja

2022

IJECE

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<p>Quality of service (QoS) is essential for carrying out data transmission using resource-constrained sensor nodes in wireless sensor network (WSN). The introduction of mobile agent-based data aggregation is reported to offer energy efficiency; however, it has limitations, especially using a single mobile agent, where QoS optimization is not feasible. A review of existing studies showcases some dedicated attempts to use a mobile agent-based approach and address QoS enhancements. However, they were never combined studied. Therefore, this paper introduces a unique concept of retaining maximum QoS performance during data aggregation using a single mobile agent. The model introduces a unique communication framework, transmission provisioning using exceptional routine management, and simplified energy modeling. The proposed model has aimed for a lower delay and faster data aggregation speed with lower consumption of transmittance energy. The implementation and assessment of the model are carried out considering the challenging environment of WSN with multiple scales of data priority. The proposed model also contributes to evolving out with simplified communication vectors in a highly decentralized method. MATLAB's simulation outcome shows that the proposed system offers better delay performance, optimal energy management, and faster response time than existing schemes.</p>

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An efficient genetic algorithm approach for solving routing and spectrum assignment problem

Cited by 22 publications

References 24 publications

Cost function‐based class of service provisioning strategy in elastic optical networks

Cost function‐based class of service provisioning strategy in elastic optical networks

Analysis and comparison of a proposed mutation operator and its effects on the performance of genetic algorithm

Energy-efficient data-aggregation for optimizing quality of service using mobile agents in wireless sensor network

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