SMOSA: Spider monkey optimization‐based scheduling algorithm for heterogeneous Hadoop

2021 ◽  
Author(s):  
Conghui Zhang ◽  
Shaopeng Guan ◽  
Yi Li ◽  
Wenwen Sun
Keyword(s):  
Scheduling Algorithm ◽  
Spider Monkey ◽  
Spider Monkey Optimization

Hybrid optimization-based pilot scheduling for reducing pilot contamination in massive MIMO systems

2020 ◽  
Vol 18 (04) ◽  
pp. 2050028
Author(s):  
Ambala Pradeep Kumar ◽  
Tadisetty Srinivasulu
Keyword(s):  
Massive Mimo ◽  
Mimo Systems ◽  
Mimo System ◽  
Fitness Function ◽  
Scheduling Algorithm ◽  
Multiple Input Multiple Output ◽  
Spider Monkey ◽  
Achievable Rate ◽  
Pilot Contamination ◽  
Spider Monkey Optimization

Massive multiple-input multiple-output (MIMO) is an emerging technology used in next-generation cellular networks. The major challenge in the massive MIMO system is the pilot contamination. The contamination of the pilot sequences causes inaccurate channel estimation leading to huge errors in the transmissions. This paper proposes an approach for pilot contamination reduction in massive MIMO systems. In order to reduce the pilot contamination, a pilot scheduling algorithm is devised by proposing an optimization algorithm named Elephant-based Spider Monkey Optimization (ESMO) for scheduling the pilots. The proposed ESMO is designed by combining Elephant Herding Optimization (EHO) into Spider Monkey Optimization (SMO). The pilot scheduling approach employs proposed ESMO and user degradation for scheduling the pilots. Moreover, the optimal pilot scheduling is carried out using the newly devised fitness function that considers achievable rate using various user grouping parameters, such as utility function, and grouping parameter. Thus, the proposed ESMO-based pilot scheduling and fitness function are responsible for initiating optimal pilot scheduling. The performance of the proposed method is compared with the existing methods, and the proposed ESMO outperformed the existing methods with maximal achievable rate value of 39.257[Formula: see text]bps/Hz, and maximal SINR with value 118.75[Formula: see text]dB, respectively.

Spider Monkey Optimization Algorithm for Load Balancing in Cloud Computing Environments

2021 ◽  
Vol 18 (5) ◽  
Author(s):  
Sawsan Alshattnawi ◽  
Mohammad AL-Marie
Keyword(s):  
Cloud Computing ◽  
Load Balancing ◽  
Response Time ◽  
Virtual Machines ◽  
Scheduling Algorithm ◽  
Round Robin ◽  
Spider Monkey ◽  
Spider Monkeys ◽  
Cloud Computing Environment ◽  
Spider Monkey Optimization

Scheduling of tasks is one of the main concerns in the Cloud Computing environment. The whole system performance depends on the used scheduling algorithm. The scheduling objective is to distribute tasks between the Virtual Machines and balance the load to prevent any virtual machine from being overloaded while other is underloaded. The problem of scheduling is considered an NP-hard optimization problem. Therefore, many heuristics have been proposed to solve this problem up to now. In this paper, we propose a new Spider Monkeys algorithm for load balancing called Spider Monkey Optimization Inspired Load Balancing (SMO-LB) based on mimicking the foraging behavior of Spider Monkeys. It aims to balance the load among virtual machines to increase the performance by reducing makespan and response time. Experimental results show that our proposed method reduces tasks' average response time to 10.7 seconds compared to 24.6 and 30.8 seconds for Round Robin and Throttled methods respectively. Also, the makespan was reduced to 21.5 seconds compared to 35.5 and 53.0 seconds for Round Robin and Throttled methods respectively.

Plant leaf disease identification using exponential spider monkey optimization

2020 ◽  
Vol 28 ◽  
pp. 100283 ◽  
Author(s):  
Sandeep Kumar ◽  
Basudev Sharma ◽  
Vivek Kumar Sharma ◽  
Harish Sharma ◽  
Jagdish Chand Bansal
Keyword(s):  
Spider Monkey ◽  
Plant Leaf ◽  
Leaf Disease ◽  
Disease Identification ◽  
Spider Monkey Optimization

scholarly journals Multi-Level Planning and Scheduling for Parallel PCB Assembly Lines Using Hybrid Spider Monkey Optimization Approach

IEEE Access ◽  
2019 ◽  
Vol 7 ◽  
pp. 18685-18700 ◽  
Author(s):  
Jabir Mumtaz ◽  
Zailin Guan ◽  
Lei Yue ◽  
Zhengya Wang ◽  
Saif Ullah ◽  
...  
Keyword(s):  
Spider Monkey ◽  
Optimization Approach ◽  
Assembly Lines ◽  
Planning And Scheduling ◽  
Pcb Assembly ◽  
Multi Level ◽  
Spider Monkey Optimization
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