Adaptive load balancing algorithm for wireless distributed computing networks

2016 ◽  
Author(s):  
Mohammed I. M. Alfaqawi ◽  
Mohamed H. Habaebi ◽  
Mohammad U. Siddiqi ◽  
Md. Rafiqul Islam ◽  
Sheroz Khan ◽  
...  
Keyword(s):  
Distributed Computing ◽  
Load Balancing ◽  
Distributed Computing Networks ◽  
Load Balancing Algorithm

A Dynamic Service-Oriented Distributed Computing Framework for Evaluation of Computationally Expensive Black-Box Analyses

2014 ◽  
Author(s):  
George H. Cheng ◽  
Chao Qi ◽  
G. Gary Wang
Keyword(s):  
Distributed Computing ◽  
Service Oriented Architecture ◽  
Experimental Testing ◽  
Black Box ◽  
Small Scale ◽  
Distributed Computing Networks ◽  
Service Oriented ◽  
Computationally Expensive ◽  
Computing Framework ◽  
Load Balancing Algorithm

A practical, flexible, versatile, and heterogeneous distributed computing framework is presented that simplifies the creation of small-scale local distributed computing networks for the execution of computationally expensive black-box analyses. The framework is called the Dynamic Service-oriented Optimization Computing Framework (DSOCF), and is designed to parallelize black-box computation to speed up optimization runs. It is developed in Java and leverages the Apache River project, which is a dynamic Service-Oriented Architecture (SOA). A roulette-based real-time load balancing algorithm is implemented that supports multiple users and balances against task priorities, which is superior to the rigid pre-set wall clock limits commonly seen in grid computing. The framework accounts for constraints on resources and incorporates a credit-based system to ensure fair usage and access to computing resources. Experimental testing results are shown to demonstrate the effectiveness of the framework.

scholarly journals A Detailed Analysis on Several Load Balancing Algorithm in Cloud Computing

10.29007/rnvj ◽  
2018 ◽  
Author(s):  
Shubhra Saxena ◽  
Navneet Sharma ◽  
Akash Saxena ◽  
Jayanti Goyal
Keyword(s):  
Cloud Computing ◽  
Distributed Computing ◽  
Load Balancing ◽  
Detailed Analysis ◽  
Virtual Machine ◽  
Bumble Bee ◽  
Cloud Framework ◽  
Execution Unit ◽  
Broad Variety ◽  
Load Balancing Algorithm

Cloud computing (CC) is rising rapidly; an expansive number of clients are pulled in towards cloud administrations for more fulfillments. Distributed computing is most recent developing innovation for expansive scale dispersed processing and parallel registering. CC gives vast pool of shared assets, program bundle, data, stockpile and a broad variety of uses according to client requests at any example of time. Adjusting the heap has turned out to be all the more intriguing examination zone in this field. Better load adjusting calculation in cloud framework builds the execution and assets use by progressively dispersing work stack among different hubs in the framework. Virtual machine (VM) is an execution unit that goes about as an establishment for distributed computing innovation. Bumble bee conduct propelled stack adjusting enhances the general throughput of handling and need construct adjusting centers with respect to decreasing the measure of time an errand needs to look out for a line of the VM.

scholarly journals Hybrid Nearest-Neighbor Ant Colony Optimization Algorithm for Enhancing Load Balancing Task Management

2021 ◽  
Vol 11 (22) ◽  
pp. 10807
Author(s):  
Fatma Mbarek ◽  
Volodymyr Mosorov
Keyword(s):  
Distributed Computing ◽  
Load Balancing ◽  
Ant Colony Optimization ◽  
Dynamic Load ◽  
Nearest Neighbor ◽  
Ant Colony ◽  
Dynamic Load Balancing ◽  
Distributed Computing Systems ◽  
Computing Systems ◽  
Load Balancing Algorithm

Many computer problems that arise from real-world circumstances are NP-hard, while, in the worst case, these problems are generally assumed to be intractable. Existing distributed computing systems are commonly used for a range of large-scale complex problems, adding advantages to many areas of research. Dynamic load balancing is feasible in distributed computing systems since it is a significant key to maintaining stability of heterogeneous distributed computing systems (HDCS). The challenge of load balancing is an objective function of optimization with exponential complexity of solutions. The problem of dynamic load balancing raises with the scale of the HDCS and it is hard to tackle effectively. The solution to this unsolvable issue is being explored under a particular algorithm paradigm. A new codification strategy, namely hybrid nearest-neighbor ant colony optimization (ACO-NN), which, based on the metaheuristic ant colony optimization (ACO) and an approximate nearest-neighbor (NN) approaches, has been developed to establish a dynamic load balancing algorithm for distributed systems. Several experiments have been conducted to explore the efficiency of this stochastic iterative load balancing algorithm; it is tested with task and nodes accessibility and proved to be effective with diverse performance metrics.

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