Distributed Adaptive VoIP Load Balancing in Hybrid Clouds (original) (raw)

Adaptive Energy Efficient Distributed VoIP Load Balancing in Federated Cloud Infrastructure

Cloud computing is widely being adopted by many companies because it allows to maximize the utilization of resources. However, the complexity of cloud computing systems with the existence of many cloud providers makes infeasible for the end user the optimal or near-optimal resource provisioning and utilization, especially in presence of uncertainty of very dynamic and unpredictable environment. Hence, dynamic adaptive load balancing algorithms are a fundamental part of the research in cloud computing. We formulate the problem and propose an adaptive load balancing algorithm for distributed computer environments. We also discuss the energy efficiency of our solution for the domain of VoIP computations on federated clouds.

Empirical analysis of dynamic load balancing techniques in cloud computing

International journal of smart sensors and ad hoc networks, 2022

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.

IJERT-Effective Distributed Dynamic Load Balancing For The Clouds

International Journal of Engineering Research and Technology (IJERT), 2013

https://www.ijert.org/effective-distributed-dynamic-load-balancing-for-the-clouds https://www.ijert.org/research/effective-distributed-dynamic-load-balancing-for-the-clouds-IJERTV2IS2511.pdf "Cloud computing" is a term, which involves virtualization, distributed computing, networking, software and web services. A cloud consists of several elements such as clients, datacenter and distributed servers. It includes fault tolerance, high availability, scalability, flexibility, reduced overhead for users, reduced cost of ownership, on demand services etc. Central to these issues lies the establishment of an effective load balancing algorithm. The load can be CPU load, memory capacity, delay or network load. Load balancing is the process of distributing the load among various nodes of a distributed system to improve both resource utilization and job response time while also avoiding a situation where some of the nodes are heavily loaded while other nodes are idle or doing very little work. Load balancing ensures that all the processor in the system or every node in the network does approximately the equal amount of work at any instant of time. This technique can be sender initiated, receiver initiated, symmetric (combination of sender initiated, receiver initiated types) static, dynamic centralized or distributed type. Various studies show that up to 80% of the workstations are idle depending on time of day [12], therefore these are advantageous to use. The idle time and computing power of processors can be used to make the processing cost-effective. Our objective is to explain the concept of load balancing, types of load balancing algorithms, general idea about dynamic load balancing algorithms and the different policies that can be used in it and gives an overall description of various distributed load balancing algorithms that can be used in case of clouds.

A Methodological Survey on Different types of Load Balancing Algorithms in Cloud Computing

Cloud Computing is one of the quickly developing area in research industry today. Cloud Computing spins around web based computing which leads to the provision of the resources automatically to the customer based on pay per use service. As cloud computing is the mixture of different technologies such as distributed computing, parallel computing and virtualization which leads to the development of the new era. Due to evolution of the cloud, there is a feasibility about how different services can be provided to the customer through internet. Today due to the recent advancements there are various cloud service providers which provides the services based on the user demand. Although there are various challenges for the cloud service provider but one of the major goal for the cloud service provider is to utilize the resources efficiently and to balance the load among the resources efficiently. In this paper we will try to explore the concept of the load balancing and will also study about the different types of load balancing algorithms along with it we will also try to pinpoint different issues related to the concept of load balancing.

CHALLENGES OF CLOUD COMPUTE LOAD BALANCING ALGORITHMS

IRJMETS Publication, 2022

Cloud computing reshaped the modern world by offering solutions to all problems faced by organizations. Cloud computing provides computational services for users in a pay-per-use fashion. Hence, they do not need to purchase these resources for their use. With the help of cloud computing services, users can use Software, Hardware, infrastructure, and many other computational resources without taking the pain of their maintenance. Because of their versatile services, cloud computing service providers face many challenges such as security, privacy, quality of service and load balancing. In this research, we focus on load-balancing issues and investigate significant challenges in the load-balancing domain of cloud computing. At the start, we introduce domain knowledge related to cloud computing technologies and then briefly discuss load balancing techniques. At last, we present some potential challenges in load balancing techniques.

Dynamic Method for Load Balancing in Cloud Computing

The state-of-art of the technology focuses on data processing and sharing to deal with huge amount of data and client's needs. Cloud computing is a promising technology, which enables one to achieve the aforesaid goal, leading towards enhanced business performance. Cloud computing comes into center of attention immediately when you think about what IT constantly needs: a means to increase capacity or add capabilities on the fly without investing in new infrastructure, training new human resources, or licensing new software. The cloud should provide resources on demand to its clients with high availability, scalability and with reduced cost. Cloud Computing System has widely been adopted by the industry, though there are many existing issues which have not been so far wholly addressed. Load balancing is one of the primary challenges, which is required to distribute the dynamic workload across multiple nodes to ensure that no single node is overwhelmed. This Paper gives an efficient dynamic load balancing algorithm for cloud workload management by which the load can be distributed not only in a balanced approach, but also it allocates the load systematically and uniformly by checking certain parameters like number of requests the server is handling currently. It balances the load on the overloaded node to under loaded node so that response time from the server will decrease and performance of the system is increased.

IJERT-Survey of Load Balancing Algorithms in Clouds

International Journal of Engineering Research and Technology (IJERT), 2015

https://www.ijert.org/survey-of-load-balancing-algorithms-in-clouds https://www.ijert.org/research/survey-of-load-balancing-algorithms-in-clouds-IJERTV4IS030428.pdf Cloud computing is the way of computing, via the internet that shares computer resources instead of using software or storage on a local PC. It stores the data and resources in the open environment. So now a day's amount of data storage increase quickly. Load Balancing is the main issues in Cloud which is required to distribute the dynamic workload across multiple nodes to ensure that no single node is overwhelmed. Load Balancing provides proper utilization of resources and enhancing the performance of the system. The existing algorithms that can provide load balancing and also provide better strategies through efficient job scheduling and resource scheduling techniques. In order to gain maximize the profit and balancing algorithms, it is necessary to utilize resources efficiently. This paper discusses some of the existing load balancing algorithms in cloud computing.

A Literature Survey on Algorithms for the Optimal Load Balancing in Cloud Computing Environments

International Journal for Research in Applied Science & Engineering Technology (IJRASET), 2022

This paper provides a survey of the existing literature and research carried out in the area of Optimal load balancing in servers. Load balancing in cloud computing is one of the important aspects for efficient delivery of resources and computing. The process of distributing workloads and computing resources in a cloud computing environment is cloud load balancing. It allows enterprises to manage application or workload demands by allocating resources among multiple computers, networks or servers. Hosting the distribution of workload traffic and demands that reside over the internet. It helps enterprises achieve high performance levels for very reasonable costs which is lower than traditional on premises load balancing technology. By taking advantage of clouds' scalability and agility cloud load balancing technology meets rerouted work demands and also improves overall availability. Load balancing can provide health checks for cloud in addition to the workload and traffic distribution .Performance analysis of different existing load balancing algorithms based on different parameters is to be carried out and the algorithm will be optimized for the better performance in cloud. The main purpose of the proposed paper will be to get help in the design of new algorithms in future. I.

Development of a Suitable Load Balancing Strategy In Case Of a Cloud Computing Architecture

IJMER

Cloud computing is an attracting technology in the field of computer science. In Gartner’s report, it says that the cloud will bring changes to the IT industry. The cloud is changing our life by providing users with new types of services. Users get service from a cloud without paying attention to the details. NIST gave a definition of cloud computing as a model for enabling ubiquitous, convenient, on-demand network access to a shared pool of configurable computing resources (e.g., networks, servers, storage, applications, and services) that can be rapidly provisioned and released with minimal management effort or service provider interaction. More and more people pay attention to cloud computing. Cloud computing is efficient and scalable but maintaining the stability of processing so many jobs in the cloud computing environment is a very complex problem with load balancing receiving much attention for researchers. Since the job arrival pattern is not predictable and the capacities of each node in the cloud differ, for load balancing problem, workload control is crucial to improve system performance and maintain stability. Load balancing schemes depending on whether the system dynamics are important can be either static or dynamic. Static schemes do not use the system information and are less complex while dynamic schemes will bring additional costs for the system but can change as the system status changes. A dynamic scheme is used here for its flexibility. The model has a main controller and balancers to gather and analyze the information. Thus, the dynamic control has little influence on the other working nodes. The system status then provides a basis for choosing the right load balancing strategy. The load balancing model given in this research article is aimed at the public cloud which has numerous nodes with distributed computing resources in many different geographic locations. Thus, this model divides the public cloud into several cloud partitions. When the environment is very large and complex, these divisions simplify the load balancing. The cloud has a main controller that chooses the suitable partitions for arriving jobs while the balancer for each cloud partition chooses the best load balancing strategy.

A Survey of Load Balancing Algorithms in Cloud Computing

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.