scholarly journals Multi-Objective Caching Optimization for Wireless Backhauled Fog Radio Access Network

Symmetry ◽  
2021 ◽  
Vol 13 (4) ◽  
pp. 708
Author(s):  
Alaa Bani-Bakr ◽  
MHD Nour Hindia ◽  
Kaharudin Dimyati ◽  
Effariza Hanafi ◽  
Tengku Faiz Tengku Mohmed Noor Izam
Keyword(s):  
Pareto Front ◽  
Search Algorithm ◽  
Access Network ◽  
Cuckoo Search ◽  
Cuckoo Search Algorithm ◽  
Multi Objective ◽  
Radio Access ◽  
Caching Scheme ◽  
Cache Placement ◽  
Fog Radio Access Network

Proactive content caching in a fog radio access network (F-RAN) is an efficient technique used to alleviate delivery delay and traffic congestion. However, the symmetric caching of the content is impractical due to the dissimilarity among the contents popularity. Therefore, in this paper, a multi-objective random caching scheme to balance the successful transmission probability (STP) and delay in wireless backhauled F-RAN is proposed. First, stochastic geometry tools are utilized to derive expressions of the association probability, STP, and average delivery delay. Next, the complexity is reduced by considering the asymptotic STP and delay in the high signal-to-noise ratio (SNR) regime. Then, aiming at maximizing the STP or minimizing the delay, the multi-objective cache placement optimization problem is formulated. A novel projected multi-objective cuckoo search algorithm (PMOCSA) is proposed to obtain the Pareto front of the optimal cache placement. The numerical results show that PMOCSA outperforms the original multi-objective cuckoo search algorithm (MOCSA) in terms of convergence to a feasible Pareto front and its rate. It also shows that the proposed multi-objective caching scheme significantly outperforms the well-known benchmark caching schemes by up to 40% higher STP and 85% lower average delay.

scholarly journals Joint Successful Transmission Probability, Delay, and Energy Efficiency Caching Optimization in Fog Radio Access Network

Electronics ◽  
2021 ◽  
Vol 10 (15) ◽  
pp. 1847
Author(s):  
Alaa Bani-Bakr ◽  
Kaharudin Dimyati ◽  
MHD Nour Hindia ◽  
Wei Ru Wong ◽  
Tengku Faiz Tengku Mohmed Noor Izam
Keyword(s):  
Optimization Problem ◽  
Search Algorithm ◽  
Access Network ◽  
Cuckoo Search ◽  
Transmission Probability ◽  
Cuckoo Search Algorithm ◽  
Radio Access ◽  
Cache Placement ◽  
Fog Radio Access Network ◽  
Successful Transmission Probability

The fog radio access network (F-RAN) is considered an efficient architecture for caching technology as it can support both edge and centralized caching due to the backhauling of the fog access points (F-APs). Successful transmission probability (STP), delay, and energy efficiency (EE) are key performance metrics for F-RAN. Therefore, this paper proposes a proactive cache placement scheme that jointly optimizes STP, delay, and EE in wireless backhauled cache-enabled F-RAN. First, expressions of the association probability, STP, average delay, and EE are derived using stochastic geometry tools. Then, the optimization problem is formulated to obtain the optimal cache placement that maximizes the weighted sum of STP, EE, and negative delay. To solve the optimization problem, this paper proposes the normalized cuckoo search algorithm (NCSA), which is a novel modified version of the cuckoo search algorithm (CSA). In NCSA, after generating the solutions randomly via Lévy flight and random walk, a simple bound is applied, and then the solutions are normalized to assure their feasibility. The numerical results show that the proposed joint cache placement scheme can effectively achieve significant performance improvement by up to 15% higher STP, 45% lower delay, and 350% higher EE over the well-known benchmark caching schemes.

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.

scholarly journals Cuckoo search algorithm for multi-objective supply chain problem

2018 ◽  
Vol 189 ◽  
pp. 06001 ◽  
Author(s):  
Fathy Elkazzaz ◽  
Abdelmageed Mahmoud ◽  
Ali Maher
Keyword(s):  
Supply Chain ◽  
Search Algorithm ◽  
Cuckoo Search ◽  
Cuckoo Search Algorithm ◽  
Chain Model ◽  
Multi Objective ◽  
Optimum Configuration ◽  
Bee Colony ◽  
Bee Colony Optimization ◽  
Chain Problem

A meta-heuristic algorithm called, the cuckoo search algorithm is proposed in dealing with the multi-objective supply chain model to find the optimum configuration of a given supply chain problem which minimizes the total cost and the total lead-time. The supply chain problem utilized in this study is taken from literature to show the performance of the proposed model; in addition, the results have been compared to those achieved by the bee colony optimization algorithm and genetic algorithm. Those obtained results indicate that the proposed cuckoo search algorithm is able to get better Pareto solutions (non-dominated set) for the supply chain problem.

Solving multi-objective optimization problem using cuckoo search algorithm based on decomposition

2020 ◽  
Vol 51 (1) ◽  
pp. 143-160
Author(s):  
Liang Chen ◽  
Wenyan Gan ◽  
Hongwei Li ◽  
Kai Cheng ◽  
Darong Pan ◽  
...  
Keyword(s):  
Optimization Problem ◽  
Search Algorithm ◽  
Cuckoo Search ◽  
Cuckoo Search Algorithm ◽  
Multi Objective Optimization ◽  
Multi Objective
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