Real-Time Agent-Based Load-Balancing Algorithm for Internet of Drone (IoD) in Cloud Computing

2022 ◽  
pp. 81-94
Author(s):  
Savita Saini ◽  
Ajay Jangra ◽  
Gurpreet Singh
2018 ◽  
Author(s):  
Dongsheng Zhang

Web traffic is highly jittery and unpredictable. Load balancer plays a significant role in mitigating the uncertainty in web environments. With the growing adoption of cloud computing infrastructure, software load balancer becomes more common in recent years. Current load balancer services distribute the network requests based on the number of network connections to the backend servers. However, the load balancing algorithm fails to work when other resources such as CPU or memory in a backend server saturates. We experimented and discussed the resilience evaluation and enhancement of container-based software load balancer services in cloud computing environments. We proposed a pluggable framework that can dynamically adjust the weight assigned to each backend server based on real-time monitoring metrics.


2015 ◽  
Vol 45 ◽  
pp. 832-841 ◽  
Author(s):  
Aarti Singh ◽  
Dimple Juneja ◽  
Manisha Malhotra

2018 ◽  
Author(s):  
Dongsheng Zhang

Web traffic is highly jittery and unpredictable. Load balancer plays a significant role in mitigating the uncertainty in web environments. With the growing adoption of cloud computing infrastructure, software load balancer becomes more common in recent years. Current load balancer services distribute the network requests based on the number of network connections to the backend servers. However, the load balancing algorithm fails to work when other resources such as CPU or memory in a backend server saturates. We experimented and discussed the resilience evaluation and enhancement of container-based software load balancer services in cloud computing environments. We proposed a pluggable framework that can dynamically adjust the weight assigned to each backend server based on real-time monitoring metrics.


IEEE Access ◽  
2021 ◽  
pp. 1-1
Author(s):  
Dalia Abdulkareem Shafiq ◽  
NZ Jhanjhi ◽  
Azween Abdullah ◽  
Mohammed A AlZain

2018 ◽  
Vol 7 (4.7) ◽  
pp. 131
Author(s):  
NV Abhinav Chand ◽  
A Hemanth Kumar ◽  
Surya Teja Marella

Emerging cloud computing technology is a big step in virtual computing. Cloud computing provides services to clients through the internet. Cloud computing enables easy access to resources distributed all over the world. Increase in the number of the population has further increased the challenge. The main challenge of cloud computing technology is to achieve efficient load balancing. Load balancing is a process of assigning load to available resources in such a way that it avoids overloading of resources. If load balancing is performed efficiently, it improves QoS metric including cost, throughput, response time, resource utilization and performance. Efficient load balancing techniques also provide better user satisfaction. Various load balancing algorithms are used in different scenarios for ensuring the same. In the current research, we will study different algorithms for load balancing and benefits and limitations caused to the system due to the algorithms. In this paper, we will compare static and dynamic load balancing algorithms for various measures of efficiency. These will be useful for future research in the concerned field. 


Cloud computing is a research trend which bring various cloud services to the users. Cloud environment face various challenges and issues to provide efficient services. In this paper, a novel Genetic Algorithm based load balancing algorithm has been implemented to balance the load in the network. The literature review has been studied to understand the research gap. More specifically, load balancing technique authenticate the network by enabling Virtual Machines (VM). The proposed technique has been further evaluated using the Schedule Length Runtime (SLR) and Energy consumption (EC) parameters. Overall, the effective results has been obtained such as 46% improvement in consuming the energy and 12 % accuracy for the SLR measurement. In addition, results has been compared with the conventional approaches to validate the outcomes.


2015 ◽  
Vol 7 (1) ◽  
Author(s):  
Endang Wahyu Pamungkas ◽  
Divi Galih Prasetyo Putri

Recently cloud computing technology has been implemented by many companies. This technology requires a really high reliability that closely related to hardware specification and management resource quality used. Adequate hardware would make resource allocation easier. On the other hand, resource allocation will be harder if the resources are limited. This is a common condition in a developing cloud service provider. In this paper, a load balancing algorithm to allocate resources in cloud computing environment that has limited resources has been proposed. This algorithm is developed by taking the advantages of the existing algorithms, Equally Spread Current Execution and Throttled. We merge those algorithm without losing the advantages and we try to eliminate the shortcoming of each algorithm. The result shows that this algorithm is able to give a significant improvement in the limited resources environment. In addition, the algorithm also able to compete with the other algorithm in the more adequate resource environment. Based on the consistent results, this algorithm is expected to be more adaptive in different resources environment.


Sign in / Sign up

Export Citation Format

Share Document