5G heterogeneous network selection and resource allocation optimization based on cuckoo search algorithm

2021 ◽  
Vol 168 ◽  
pp. 170-177
Author(s):  
Ning Ai ◽  
Bin Wu ◽  
Boyu Li ◽  
Zhipeng Zhao
Keyword(s):  
Resource Allocation ◽  
Heterogeneous Network ◽  
Search Algorithm ◽  
Cuckoo Search ◽  
Cuckoo Search Algorithm ◽  
Network Selection

scholarly journals Resource Allocation and Joint Mode Selection for Device-to-Device Communications Using Cuckoo Search Algorithm

2021 ◽  
pp. 429-436
Author(s):  
Nethravathi H M ◽  
◽  
S. Akhila
Keyword(s):  
Resource Allocation ◽  
Search Algorithm ◽  
Mode Selection ◽  
Cuckoo Search ◽  
Problem Formulation ◽  
Cuckoo Search Algorithm ◽  
Device To Device ◽  
Optimal Resource ◽  
Radio Resources ◽  
Selection For

In this study, Resource Allocation and Joint Mode Selection for Device-to-Device Communications (D2D) has been modelled using the cuckoo search algorithm (CSA). The implementation is made for equal power control and constraints ensuring that the existing sub-channels are used efficiently and optimally. Simultaneous access to radio resources in a coexistence scenario through D2D technology with optimal mode selection is considered. Initially, the problem formulation for resource allocation is written, then, a cuckoo search optimized solution for optimal resource allocation and mode selection in uplink cellular communications has been proposed and the same has been evaluated using throughput analysis.

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

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.

scholarly journals Optimization strategy of wireless charger node deployment based on improved cuckoo search algorithm

2021 ◽  
Vol 2021 (1) ◽  
Author(s):  
Yang Wang ◽  
Feifan Wang ◽  
Yujun Zhu ◽  
Yiyang Liu ◽  
Chuanxin Zhao
Keyword(s):  
Sensor Network ◽  
Sensor Node ◽  
Search Algorithm ◽  
Optimal Solution ◽  
Cuckoo Search ◽  
Cuckoo Search Algorithm ◽  
Sensor Nodes ◽  
Optimization Strategy ◽  
Multi Objective ◽  
Received Power

AbstractIn wireless rechargeable sensor network, the deployment of charger node directly affects the overall charging utility of sensor network. Aiming at this problem, this paper abstracts the charger deployment problem as a multi-objective optimization problem that maximizes the received power of sensor nodes and minimizes the number of charger nodes. First, a network model that maximizes the sensor node received power and minimizes the number of charger nodes is constructed. Second, an improved cuckoo search (ICS) algorithm is proposed. This algorithm is based on the traditional cuckoo search algorithm (CS) to redefine its step factor, and then use the mutation factor to change the nesting position of the host bird to update the bird’s nest position, and then use ICS to find the ones that maximize the received power of the sensor node and minimize the number of charger nodes optimal solution. Compared with the traditional cuckoo search algorithm and multi-objective particle swarm optimization algorithm, the simulation results show that the algorithm can effectively increase the receiving power of sensor nodes, reduce the number of charger nodes and find the optimal solution to meet the conditions, so as to maximize the network charging utility.

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