scholarly journals Flow Based Load Balancing: Optimizing Web Servers Resource Utilization

2012 ◽  
Vol 1 (2) ◽  
Author(s):  
Leonardo Richter Bays ◽  
Daniel Stefani Marcon
Keyword(s):  
Load Balancing ◽  
Resource Utilization ◽  
Web Servers

M2FBalancer: A mist-assisted fog computing-based load balancing strategy for smart cities

2021 ◽  
pp. 1-15
Author(s):  
Subhranshu Sekhar Tripathy ◽  
Diptendu Sinha Roy ◽  
Rabindra K. Barik
Keyword(s):  
Load Balancing ◽  
Resource Utilization ◽  
Smart City ◽  
Load Transfer ◽  
Smart Cities ◽  
Fog Computing ◽  
Round Robin ◽  
Healthcare Management ◽  
Optimization Strategy ◽  
Allocation Method

Nowadays, cities are intended to change to a smart city. According to recent studies, the use of data from contributors and physical objects in many cities play a key element in the transformation towards a smart city. The ‘smart city’ standard is characterized by omnipresent computing resources for the observing and critical control of such city’s framework, healthcare management, environment, transportation, and utilities. Mist computing is considered a computing prototype that performs IoT applications at the edge of the network. To maintain the Quality of Service (QoS), it is impressive to employ context-aware computing as well as fog computing simultaneously. In this article, the author implements an optimization strategy applying a dynamic resource allocation method based upon genetic algorithm and reinforcement learning in combination with a load balancing procedure. The proposed model comprises four layers i.e. IoT layer, Mist layer, Fog layer, and Cloud layer. Authors have proposed a load balancing technique called M2F balancer which regulates the traffic in the network incessantly, accumulates the information about each server load, transfer the incoming query, and disseminate them among accessible servers equally using dynamic resources allocation method. To validate the efficacy of the proposed algorithm makespan, resource utilization, and the degree of imbalance (DOI) are considered as the scheduling parameter. The proposed method is being compared with the Least count, Round Robin, and Weighted Round Robin. In the end, the results demonstrate that the solutions enhance QoS in the mist assisted cloud environment concerning maximization resource utilization and minimizing the makespan. Therefore, M2FBalancer is an effective method to utilize the resources efficiently by ensuring uninterrupted service. Consequently, it improves performance even at peak times.

scholarly journals The network architecture optimization based on the server load balancing technology

2021 ◽  
Vol 336 ◽  
pp. 08001
Author(s):  
Ruicai Huo ◽  
Songqiu Liu ◽  
Shiwei He
Keyword(s):  
Load Balancing ◽  
Resource Utilization ◽  
Network Architecture ◽  
Integration Method ◽  
Single Point ◽  
Gateway System ◽  
Architecture Optimization ◽  
Cluster Design

The paper takes the authentication gateway system for internal office network as the research object, for the performance bottleneck and single point of failure problem of the single authentication gateway deployed in the existing primary and standby modes, chooses an authentication gateway integration method based on CA certificate. The practical results show that: through implementing the authentication gateway cluster design and introducing load balancing mechanism, this method solves the performance, stability and single point of failure of the authentication gateway, and improves the resource utilization of the authentication gateway device. This method introduced in this paper can be used for reference for the network architecture optimization based on the server load balancing technology.

scholarly journals Web Server Performance Improvement Using Dynamic Load Balancing Techniques: A Review

2021 ◽  
pp. 47-62
Author(s):  
Ibrahim Mahmood Ibrahim ◽  
Siddeeq Y. Ameen ◽  
Hajar Maseeh Yasin ◽  
Naaman Omar ◽  
Shakir Fattah Kak ◽  
...  
Keyword(s):  
Load Balancing ◽  
Response Time ◽  
Performance Improvement ◽  
Web Server ◽  
Dynamic Load Balancing ◽  
The Internet ◽  
Web Servers ◽  
Web Server Performance ◽  
Server Clusters ◽  
The Web

Today, web services rapidly increased and are accessed by many users, leading to massive traffic on the Internet. Hence, the web server suffers from this problem, and it becomes challenging to manage the total traffic with growing users. It will be overloaded and show response time and bottleneck, so this massive traffic must be shared among several servers. Therefore, the load balancing technologies and server clusters are potent methods for dealing with server bottlenecks. Load balancing techniques distribute the load among servers in the cluster so that it balances all web servers. The motivation of this paper is to give an overview of the several load balancing techniques used to enhance the efficiency of web servers in terms of response time, throughput, and resource utilization. Different algorithms are addressed by researchers and get good results like the pending job, and IP hash algorithms achieve better performance.

Hierarchical Load Balancing Model by Optimal Resource Utilization

2021 ◽  
pp. 150-164
Author(s):  
Jagdish Chandra Patni
Keyword(s):  
Load Balancing ◽  
Grid Computing ◽  
Resource Utilization ◽  
Resource Availability ◽  
High Performance ◽  
Low Cost ◽  
Original Form ◽  
Computing Paradigm ◽  
Optimal Resource ◽  
Performance Computing

Powerful computational capabilities and resource availability at a low cost is the utmost demand for high performance computing. The resources for computing can viewed as the edges of an interconnected grid. It can attain the capabilities of grid computing by balancing the load at various levels. Since the nature of resources are heterogeneous and distributed geographically, the grid computing paradigm in its original form cannot be used to meet the requirements, so it can use the capabilities of the cloud and other technologies to achieve the goal. Resource heterogeneity makes grid computing more dynamic and challenging. Therefore, in this article the problem of scalability, heterogeneity and adaptability of grid computing is discussed with a perspective of providing high computing, load balancing and availability of resources.

A Prolific Scheme for Load Balancing Relying on Task Completion Time

2018 ◽  
Vol 8 (3) ◽  
pp. 1741
Author(s):  
V. Anand ◽  
K. Anuradha
Keyword(s):  
Load Balancing ◽  
Uniform Distribution ◽  
Resource Utilization ◽  
Completion Time ◽  
Computation Time ◽  
Task Completion ◽  
The Internet ◽  
Task Completion Time ◽  
Network Load ◽  
Computation Load

In networks with lot of computation, load balancing gains increasing significance. To offer various resources, services and applications, the ultimate aim is to facilitate the sharing of services and resources on the network over the Internet. A key issue to be focused and addressed in networks with large amount of computation is load balancing. Load is the number of tasks‘t’ performed by a computation system. The load can be categorized as network load and CPU load. For an efficient load balancing strategy, the process of assigning the load between the nodes should enhance the resource utilization and minimize the computation time. This can be accomplished by a uniform distribution of load of to all the nodes. A Load balancing method should guarantee that, each node in a network performs almost equal amount of work pertinent to their capacity and availability of resources. Relying on task subtraction, this work has presented a pioneering algorithm termed as E-TS (Efficient-Task Subtraction). This algorithm has selected appropriate nodes for each task. The proposed algorithm has improved the utilization of computing resources and has preserved the neutrality in assigning the load to the nodes in the network.

A Proficient Approach for Load Balancing in Cloud Computing-Join Minimum Loaded Queue

2020 ◽  
Vol 11 (1) ◽  
pp. 12-36
Author(s):  
Minakshi Sharma ◽  
Rajneesh Kumar ◽  
Anurag Jain
Keyword(s):  
Cloud Computing ◽  
Load Balancing ◽  
Response Time ◽  
Resource Utilization ◽  
Cloud Service ◽  
Cloud Environment ◽  
Cloud Service Provider ◽  
Qos Parameters ◽  
Load Balancing Algorithm

Cloud load balancing is done to persist the services in the cloud environment along with quality of service (QoS) parameters. An efficient load balancing algorithm should be based on better optimization of these QoS parameters which results in efficient scheduling. Most of the load balancing algorithms which exist consider response time or resource utilization constraints but an efficient algorithm must consider both perspectives from the user side and cloud service provider side. This article presents a load balancing strategy that efficiently allocates tasks to virtualized resources to get maximum resource utilization in minimum response time. The proposed approach, join minimum loaded queue (JMLQ), is based on the existing join idle queue (JIQ) model that has been modified by replacing idle servers in the I-queues with servers having one task in execution list. The results of simulation in CloudSim verify that the proposed approach efficiently maximizes resource utilization by reducing the response time in comparison to its other variants.

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