Recursive First Fit: A Highly Parallel Optimal Solution to Spectrum Allocation

Cognitive radio systems have taken a fore-running position in the wireless communication technology. With most of the communication taking place through multi-carrier systems, the allocation of available spectrum to various carriers is a prominent issue. Since cognitive systems provide an environment of dynamic spectrum allocation, it becomes necessary to perform dynamic spectrum allocation swiftly with due consideration of parameters, like power consumption, fair distribution and minimal error. This paper considers a Particle Swarm Optimization-based approach, popularly used for solving large problems involving complex solution spaces to reach an optimal solution within feasible time. The mentioned spectrum allocation problem has been solved using PSO with a view to maximize the total transfer rate of the system, within specified constraints of maximum error rate, maximum power consumption and minimum transfer rate per user. The results have been compared with the existing Genetic Algorithm-based approach and have proved to be more effective.

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Routing and Spectrum Allocation in Spectrum-Sliced Elastic Optical Path Networks: A Primal-Dual Framework

Electronics ◽

10.3390/electronics10222809 ◽

2021 ◽

Vol 10 (22) ◽

pp. 2809

Author(s):

Yang Wang ◽

Chaoyang Li ◽

Qian Hu ◽

Jabree Flor ◽

Maryam Jalalitabar

Keyword(s):

Heuristic Algorithms ◽

Fundamental Problem ◽

Optimal Solution ◽

Optical Path ◽

Spectrum Allocation ◽

Computational Time ◽

Solution Quality ◽

Traffic Demand ◽

Primal Dual ◽

Routing And Spectrum Allocation

The recent decade has witnessed a tremendous growth of Internet traffic, which is expected to continue climbing for the foreseeable future. As a new paradigm, Spectrum-sliced Elastic Optical Path (SLICE) networks promise abundant (elastic) bandwidth to address the traffic explosion, while bearing other inherent advantages including enhanced signal quality and extended reachability. The fundamental problem in SLICE networks is to route each traffic demand along a lightpath with continuously and consecutively available sub-carriers, which is known as the Routing and Spectrum Allocation (RSA) problem. Given its NP-Hardness, the solutions to the RSA problem can be classified into two categories: optimal solutions using link-based, path-based, and channel-based Integer Linear Programming (ILP) models, which require extensive computational time; and sub-optimal heuristic and meta-heuristic algorithms, which have no guarantee on the solution quality. In this work, inspired by a channel-based ILP model, we propose a novel primal-dual framework to address the RSA problem, which can obtain a near-optimal solution with guaranteed per-instance closeness to the optimal solution.

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Review

Advances in Wireless Technologies and Telecommunication - Next-Generation Wireless Networks Meet Advanced Machine Learning Applications ◽

10.4018/978-1-5225-7458-3.ch005 ◽

2019 ◽

pp. 100-122

Author(s):

Madhushi P. Ranasinghe ◽

Malka N. Halgamuge

Keyword(s):

Energy Efficiency ◽

Cognitive Radio ◽

Network Management ◽

Spectrum Sensing ◽

Communication Systems ◽

Research Work ◽

Optimal Solution ◽

Spectrum Allocation ◽

Scientific Publications ◽

Work Related

Cognitive radio technology (CRNs) will be the fundamental driving force behind the next generation (5G) mobile communication systems as it provides the optimal solution for the problem of spectrum scarcity via dynamic spectrum usage. The CRNs, however, pose several key challenges such as network management, spectrum allocation, and access, energy efficiency, interference, cost, spectrum sensing, security, and quality of service (QoS). In this chapter, the authors undertake a comprehensive analysis of 30 peer-reviewed scientific publications collated from 2017 to 2018 April that examine cognitive radio networks to identify practical solutions proposed to overcome critical challenges in this field. Nine distinct challenges were considered: network management, spectrum allocation, and access, energy efficiency, interference, cost, spectrum sensing, security, and QoS. The analysis demonstrates that the majority of research work related to CRN focuses on approaches to improve network management and, specifically, optimization of networks.

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Spectrum Allocation in Cognitive Radio - Simplified Swarm Optimization Based Method

International Journal of Engineering and Advanced Technology - Regular Issue ◽

10.35940/ijeat.c5439.029320 ◽

2020 ◽

Vol 9 (3) ◽

pp. 1636-1641

Keyword(s):

Average Power ◽

Optimal Solution ◽

Radio Spectrum ◽

Spectrum Allocation ◽

Channel Utilization ◽

Swarm Optimization ◽

System A ◽

End To End Delay ◽

Average Power Consumption ◽

Maximum Utilization

Communication through wireless mode is accelerated its expansion in broad manner that make a way to communicate with different type of computing devices to interact each other. As the number of users continues to increase, there is a constant demand for the usability of radio spectrum, which is a limited resource.Therefore a maximum utilization of spectrum is necessary at any moment. Moreover it is desired to share the capacity of the bandwidth between the user’s application on the basis of different channel utilization without compromising efficiency and fairness. Because cognitive system accommodate a dynamic spectrum allocation environment and it becomes an essential to compare performance in terms of Throughput, Latency, End-To-End Delay, Average Power Consumption, Average Adaptation Time and Average Total Utility were provided to illustrate the improved behaviour of the proposed system. A quality conscious spectrum assessment work is proposed, where spectrum bands are examined based on the requirements of application as well as the complex existence of the spectrum bands. The author used Simplified Swam Optimization (SSO) in this paper to communicate spectrum allocation and the performance of the proposed method is compared with the existing methods; Genetic Algorithm (GA) and Particle Swam Optimization (PSO) . It has been found that SSO gives an optimal solution than GA and PSO.

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Identifying Measurement Invariant Item Sets in Cross-Cultural Settings Using an Automated Item Selection Procedure

Methodology ◽

10.1027/1614-2241/a000155 ◽

2018 ◽

Vol 14 (4) ◽

pp. 177-188 ◽

Cited By ~ 2

Author(s):

Martin Schultze ◽

Michael Eid

Keyword(s):

Measurement Invariance ◽

Optimal Solution ◽

Selection Procedure ◽

Cross Cultural ◽

Item Selection ◽

Ant System ◽

Item Quality ◽

Ant System Algorithm ◽

Selection For ◽

Selection Of

Abstract. In the construction of scales intended for the use in cross-cultural studies, the selection of items needs to be guided not only by traditional criteria of item quality, but has to take information about the measurement invariance of the scale into account. We present an approach to automated item selection which depicts the process as a combinatorial optimization problem and aims at finding a scale which fulfils predefined target criteria – such as measurement invariance across cultures. The search for an optimal solution is performed using an adaptation of the [Formula: see text] Ant System algorithm. The approach is illustrated using an application to item selection for a personality scale assuming measurement invariance across multiple countries.

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Optimal broadcast scheduling method for VANETs: An adaptive discrete firefly approach

Journal of Intelligent & Fuzzy Systems ◽

10.3233/jifs-189134 ◽

2020 ◽

Vol 39 (6) ◽

pp. 8125-8137

Author(s):

Jackson J Christy ◽

D Rekha ◽

V Vijayakumar ◽

Glaucio H.S. Carvalho

Keyword(s):

Intelligent Transportation System ◽

Search Algorithm ◽

Mac Protocol ◽

High Mobility ◽

Optimal Solution ◽

Cuckoo Search ◽

Cuckoo Search Algorithm ◽

Traffic Density ◽

Scheduling Problem ◽

Broadcast Scheduling

Vehicular Adhoc Networks (VANET) are thought-about as a mainstay in Intelligent Transportation System (ITS). For an efficient vehicular Adhoc network, broadcasting i.e. sharing a safety related message across all vehicles and infrastructure throughout the network is pivotal. Hence an efficient TDMA based MAC protocol for VANETs would serve the purpose of broadcast scheduling. At the same time, high mobility, influential traffic density, and an altering network topology makes it strenuous to form an efficient broadcast schedule. In this paper an evolutionary approach has been chosen to solve the broadcast scheduling problem in VANETs. The paper focusses on identifying an optimal solution with minimal TDMA frames and increased transmissions. These two parameters are the converging factor for the evolutionary algorithms employed. The proposed approach uses an Adaptive Discrete Firefly Algorithm (ADFA) for solving the Broadcast Scheduling Problem (BSP). The results are compared with traditional evolutionary approaches such as Genetic Algorithm and Cuckoo search algorithm. A mathematical analysis to find the probability of achieving a time slot is done using Markov Chain analysis.

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Aplikasi Metode Hungarian Dalam Optimalisasi Waktu Penugasan Karyawan dan Keuntungan Produksi Home Industry

Talenta Conference Series Science and Technology (ST) ◽

10.32734/st.v2i2.470 ◽

2019 ◽

Vol 2 (2) ◽

Author(s):

Empya Charlie ◽

Siti Rusdiana ◽

Rini Oktavia

Keyword(s):

Sensitivity Analysis ◽

Optimal Solution ◽

Optimal Scheduling ◽

Total Work ◽

Work Time ◽

Hungarian Method ◽

Total Work Time

Penelitian ini bertujuan untuk mengoptimalkan penjadwalan karyawan di CV. Karya Indah Bordir dalam melakukan tugas-tugas tertentu menggunakan metode Hungaria, serta menganalisis sensitivitas solusi optimal jika ada pengurangan waktu karyawan untuk menyelesaikan tugas-tugas. Metode Hongaria diterapkan pada proses bordir yang melibatkan 11 karyawan dan 10 tugas. Hasil penjadwalan yang optimal meminimalkan waktu produksi bordir perusahaan. Hasil penjadwalan optimal yang ditemukan adalah: karyawan 1 mengerjakan tas Mambo, karyawan 2 mengerjakan tas Elli, karyawan 3 mengerjakan tas Lonjong, karyawan 4 mengerjakan tas Tampang bunga, karyawan 6 mengerjakan tas Ransel, karyawan 7 mengerjakan tas Tima, karyawan 8 mengerjakan tas Keong, karyawan 9 mengerjakan tas Alexa, karyawan 10 mengerjakan tas Luna, dan karyawan 11 mengerjakan tas Mikha, dengan total waktu kerja adalah 13,7 jam. Setelah metode Hongaria diterapkan, CV. Karya Indah Bordir mendapat peningkatan pendapatan sebanyak 9,09%. Analisis sensitivitas dilakukan dengan mengurangi waktu karyawan dalam menyulam tas. Hasil analisis sensitivitas adalah beberapa batasan untuk variabel basis dan non basis untuk mempertahankan solusi optimal. This research has a purpose to optimize the scheduling of employees in CV. Karya Indah Bordir in doing certain tasks using Hungarian method, as well as analyzing the sensitivity of the optimal solution if there is a reduction on the employees time to finish the tasks. The Hungarian method was applied on the embroidery process involving 11 employees and 10 tasks. The optimal scheduling result minimize the time of the embroidery production of the company. The optimal scheduling result found is: employee 1 does the Mambo bag, employee 2 does the Elli bag, employee 3 does the Lonjong bag, employee 4 does the Tampang bunga bag, employee 6 does the Ransel, employee 7 does the Tima bag, employee 8 does the Keong bag, employee 9 does the Alexa bag, employees 10 does the Luna bag, and employee 11 does the Mikha bag, with the total work time is 13,7 hours. After the Hungarian method was applied, CV. Karya Indah Bordir got the increasing revenue as much as 9,09 %. The sensitivity analysis was conducted by reducing the time of the employees take in embroidery the bags. The results of the sensitivity analysis are some boundaries for basis and non basis variables to maintain the optimal solution.

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