Load Balancing Techniques for Efficient Traffic Management in Cloud Environment

Cloud computing is an internet based computing. This computing paradigm has enhanced the use of network where the capability of one node can be utilized by other node. Cloud service provides access on demand to distributive resources such as database, servers, software, infrastructure etc. in pay as you go basis. Load balancing is one of the vexing issues in distributed environment. Resources of service provider need to balance the load of client request. Load balancing is adapted in order to increase the resource consumption in Data centers that leads to enhance the overall performance of system achieving client satisfaction

Experimental setup for investigating the efficient load balancing algorithms on virtual cloud

Cloud computing has emerged as the primary choice for developers in developing applications that require high-performance computing. Virtualization technology has helped in the distribution of resources to multiple users. Increased use of cloud infrastructure has led to the challenge of developing a load balancing mechanism to provide optimized use of resources and better performance. Round robin and least connections load balancing algorithms have been developed to allocate user requests across a cluster of servers in the cloud in a time-bound manner. In this paper, we have applied the round robin and least connections approach of load balancing to HAProxy, virtual machine clusters and web servers. The experimental results are visualized and summarized using Apache Jmeter and a further comparative study of round robin and least connections is also depicted. Experimental setup and results show that the round robin algorithm performs better as compared to the least connections algorithm in all measuring parameters of load balancer in this paper

Hybrid Load Balancing Algorithm in Heterogeneous Cloud Environment

Cloud computing is a heterogeneous environment offers a rapidly and on-demand wide range of services to the end users.It's a new solution and strategy for high performance computing where, it achieve high availability, flexibility, cost reduced and on demand scalability. The need to efficient and powerful load balancing algorithms is one of the most important issues in cloud computing to improve the performance. This paper proposed a hybrid load balancing algorithm to improve the performance and efficiency in heterogeneous cloud environment. The algorithm considers the current resource information and the CPU capacity factor and takes advantages of both random and greedy algorithms. The hybrid algorithm has been evaluated and compared with other algorithms using cloud Analyst simulator. The experiment results show that the proposed algorithm improves the average response time and average processing time compared with other algorithms

Empirical analysis of dynamic load balancing techniques in cloud computing

Virtualization, dispersed registration, systems administration, programming, and web administrations are all examples of distributed computing. Customers, datacenters, and scattered servers are just a few of the components that make up a cloud. It includes things like internal failure adaption, high accessibility, flexibility, adaptability, lower client overhead, lower ownership costs, on-demand advantages, and so on. The basis of a feasible load adjusting computation is key to resolving these challenges. CPU load, memory limit, deferral, and system load are all examples of heaps. Burden adjustment is a method for distributing the load across the many hubs of a conveyance framework in order to optimize asset utilization and employment response time while avoiding a situation where some hubs are heavily loaded while others are idle or performing little work. Burden adjustment ensures that at any one time, each processor in the framework or each hub in the system does about the same amount of work. This method may be initiated by the sender, the collector, or the symmetric sort (the blend of sender-started and recipient started types). With some example data center loads, the goal is to create several dynamic load balancing techniques such as Round Robin, Throttled, Equally Spread Current Execution Load, and Shortest Job First algorithms

An optimized Load Balancing Technique for Virtual Machine Migration in Cloud Computing

Cloud computing (CC) is a service that uses subscription storage & computing power. Load balancing in distributed systems is one of the most critical pieces. CC has been a very interesting and important area of research because CC is one of the best systems that stores data with reduced costs and can be viewed over the internet at all times. Load balance facilitates maintaining high user retention & resource utilization by ensuring that each computing resource is correctly and properly distributed. This paper describes cloud-based load balancing systems. CC is virtualization of hardware like storage, computing, and security by virtual machines (VM). The live relocation of these machines provides many advantages, including high availability, hardware repair, fault tolerance, or workload balancing. In addition to various VM migration facilities, during the migration process, it is subject to significant security risks which the industry hesitates to accept. In this paper we have discussed CC besides this we also emphasize various existing load balancing algorithms, advantages& also we describe the PSO optimization technique

AN EFFICIENT ALGORITHM FOR LOAD BALANCING IN CLOUD COMPUTING

Cloud computing is a computing provided over the internet. The principle aspect of cloud computing is virtualization that deals with the construction and management of virtual machines efficiently. As the number of consumers and requests for the services are increasing day by day in cloud computing, therefore load balancing is an important research area for handling the users’ requests efficiently. For efficient & effective management and usage of cloud service provider’s resources, many load balancing algorithms have been already proposed. This paper proposed and implemented a hybrid approach for virtual machine level load balancing

Implementation of Latency by Using Distributed Load Balancing Algorithm for Logistics

Cloud computing provides a data center at any location in the world. There are so many resources used in a distributed data center that a logistics suppliers and users can buy, sell and rent like execution time, bandwidth, cost, storage and memory. The logistics suppliers and users do not need to know where the data center is located and how to operate or maintain their resources by using cloud computing. They only need to know how to connect to these resources and use of applications needed to perform their jobs. Many companies want to services by using its own local data centers. In logistics information system, information sharing, transfer mode of information using cloud service provider to different logistics partners is a big challenge. Every logistics user wants that information sharing should be in real time within minimum cost. The number of logistics partners and logistics users is growing and they need services for balancing the network traffic and load. The paper has different sections as follows: Section 2 discusses related works. Section 3 discusses scheduling and load balancing algorithms. Section 4 provides our proposed algorithm’s design. Section 5 provides experimental result and performance analysis. Section 6 concludes our research work and future work. Keywords: Cloud Computing, Logistics information system, Load balancing algorithms, DSB

A Novel Method of Butterfly Optimization Algorithm for Load Balancing in Cloud Computing

Cloud computing is frequently alluded to as a model that furnishes boundless information handling conveniences with a compensation for each utilization framework. Present day cloud foundations resources as virtual machines (VMs) to actual machines utilizing virtualization innovation. All VMs works their involved structure and exhaust resources from their actual machine which behaves like a host. For load adjusting, Cloud moves VMs from exceptionally troubled real machines to low troubled actual machines. The delay of this calculation expansions in the organization as virtual machines are relocated. This work puts forward a new algorithm, namely Butterfly optimization for VM migration. The proposed optimization algorithm has been implemented in the MATLAB software.  A comparative analysis is performed between the outcomes of the preceding and the new algorithm.  The proposed algorithm has been evaluated over three performance parameters including delay, bandwidth used, and space used