Load-balancing algorithms in cloud computing: A survey

IRJET, 2022

Cloud Computing is a recent developmental paradigm in the field of computing offering huge power to next-generation computers. The dynamic provisioning acts as a base for cloud computing facilitating and supporting the network services. It focuses on making the vision of utility computing a reality with pay-as-you-go. It offers immense potential to bloom the world with applications and products focusing on greater resource utilization and scalability. This paper presents the survey on the basics of cloud computing, the concepts of load balancing, and the scheduling of tasks in the cloud. It elaborates on the existing load scheduling algorithms with their merits and demerits, suitability in the cloud, heterogeneous computing environment, and proposes a new perspective for better results as per desired parameters.

International Journal of Advanced Trends in Computer Science and Engineering, 2021

The Internet has become a fundamental necessity of daily activity. It has a more significant impact on modernizing the digital world. Therefore, cloud computing has been one of the most promising technological advances in recent days. It aims to provide millions of consumers around the globe with smooth computing services. In workload distributions and system behavior, the cloud environment is extremely dynamic, leading to load imbalances across data center resources. Balancing load across the systems is a crucial component of cloud computing, avoiding some nodes' overloading while others have little or no work to do. The problem of load balancing in the cloud has been linked to a large amount of research, recognizing its role and impact. This paper bestows a thorough investigation of the new load balancing algorithms for the cloud environment. This study's primary focus is the concept of load balancing, a literature review on load balancing and task scheduling techniques, and different measurement parameters.

Load Balancing is essential for efficient operations in distributed environments. As Cloud Computing is growing rapidly and clients are demanding more services and better results, load balancing for the Cloud has become a very interesting and important research area. Many algorithms were suggested to provide efficient mechanisms and algorithms for assigning the client's requests to available Cloud nodes. These approaches aim to enhance the overall performance of the Cloud and provide the user more satisfying and efficient services. In this paper, we investigate the different algorithms proposed to resolve the issue of load balancing and task scheduling in Cloud Computing. We discuss and compare these algorithms to provide an overview of the latest approaches in the field.

Eighth Sense Research Group

ABSTRACT Cloud computing is overtaking the existing conventional methods of computation and communication over the network. The entire Internet community is often lured by a new paradigm that provides a great level of availability and security with nominal usage charges. Cloud computing, in this perspective, is an important way of disseminating information and providing computational capabilities over the network. The amount of data being stored and the services being provided are increasing at a very fast rate which, in turn, demands greater storage and computing hardware. With a huge number of requests in the form of load to the servers, load balancing becomes an important issue in cloud computing. The aim here is to distribute the load amongst the available nodes in such a way that no single node is flooded with requests, while some other node is lightly loaded. The prevalent scheduling algorithms have been addressing this issue by making use of job scheduling and resource provisioning strategies efficiently. This paper discusses the popular load balancing algorithms, along with the challenges faced. Keywords:- Cloud computing, Virtualization, Software as a Service, Public cloud, Utility computing, Private cloud, Virtual machine, Starvation.

2016

Cloud Computing is an emerging computing paradigm. It aims to share data, calculations, and service transparently over a scalable network of nodes. Since Cloud computing stores the data and disseminated resources in the open environment. So, the amount of data storage increases quickly. In the cloud storage, load balancing is a key issue. It would consume a lot of cost to maintain load information, since the system is too huge to timely disperse load. Load balancing is one of the main challenges in cloud computing which is required to distribute the dynamic workload across multiple nodes to ensure that no single node is overwhelmed. It helps in optimal utilization of resources and hence in enhancing the performance of the system. A few existing scheduling algorithms can maintain load balancing and provide better strategies through efficient job scheduling and resource allocation techniques as well. In order to gain maximum profits with optimized load balancing algorithms, it is nece...

Journal of King Saud University - Computer and Information Sciences

Scheduling or the allocation of user requests (tasks) in the cloud environment is an NP-hard optimization problem. According to the cloud infrastructure and the user requests, the cloud system is assigned with some load (that may be underloaded or overloaded or load is balanced). Situations like underloaded and overloaded cause different system failure concerning the power consumption, execution time, machine failure, etc. Therefore, load balancing is required to overcome all mentioned problems. This load balancing of tasks (those are may be dependent or independent) on virtual machines (VMs) is a significant aspect of task scheduling in clouds. There are various types of loads in the cloud network such as memory load, Computation (CPU) load, network load, etc. Load balancing is the mechanism of detecting overloaded and underloaded nodes and then balance the load among them. Researchers proposed various load balancing approaches in cloud computing to optimize different performance parameters. We have presented a taxonomy for the load balancing algorithms in the cloud. A brief explanation of considered performance parameters in the literature and their effects is presented in this paper. To analyze the performance of heuristic-based algorithms, the simulation is carried out in CloudSim simulator and the results are presented in detail.

American Journal of Applied Mathematics, 2014

Cloud computing is one of the real innovation in giving a shared pool of resources globally. In cloud computing there exist diverse sorts of architectures in particular private, public, hybrid and so on. The cloud computing is also meant for providing service via platform (PaaS), Infrastructure (IaaS), Software (SaaS). The term capacity planning is used to dynamically upscale or downscale the computing resources accordingly. There will be many job requests which require to get executed among the available resources in a particular cloud in order to achieve the maximum throughput, minimum waiting time and best overall performance. In this paper a systematic review is made on various job scheduling algorithms along with their working procedure and a comparison among these algorithms is presented. The paper concludes with a proposed system with improvised QoS parameters to provide a load balanced task scheduling algorithm for public clouds.

Cloud computing provides services to users to access SaaS, PaaS and IaaS services Over the Internet. There are many issues in Cloud computing like security, energy efficiency, big data, load balancing etc. One of the challenging issue is load balancing. Load balancing means distribute the workload to nodes or computers or resources so that we can achieve resource utilization, maximize throughput, reduce response time etc.Load balancing and job scheduling in cloud computing is very necessary for efficiency of resource utilization. Some algorithms are used for load balancing but some issues occur. So we can use another load balancing strategies for better load balancing and checks its efficiency through simulation results using simulator.

International Journal of Computer Sciences and Engineering

Cloud computing is sharing various computing resources rather than having local servers or personal devices to handle applications over internet. There is lots of data stored on cloud and multiple requests come for resources, due to this increase load on data servers and sometimes unable to provide resources on time. So to manage the load by scheduling task appropriately researchers have introduced some load balancing techniques. Job scheduling can be done by various algorithms like FCFS, Round Robin, and Priority Scheduling. In this paper we are reviewing existing static and dynamic load balancing techniques like Min-Min, Max-Min, Ant colony optimization etc.

Cloud computing is emerging as a new paradigm for manipulating, configuring, and accessing large scale distributed computing applications over the network. Load balancing is one of the main Challenges in cloud computing which is required to distribute the workload evenly across all the nodes. Load is a measure of the amount of work that a computation system performs which can be classified as CPU load, network load, memory capacity and storage capacity. It helps to achieve a high user satisfaction and resource utilization ratio by ensuring an efficient and fair allocation of every computing resource. Proper load balancing aids in implementing fail-over, enabling scalability, over-provisioning, minimizing resource consumption and avoiding bottlenecks etc. This paper describes a survey on load balancing algorithms in cloud computing environment along with their corresponding advantages, disadvantages and performance metrics are discussed in detail.