• Corpus ID: 49573818

oney bee behavior inspired load balancing of tasks in cloud omputing environments

  title={oney bee behavior inspired load balancing of tasks in cloud omputing environments},
  author={P. Venkata Krishnab},
Scheduling of tasks in cloud computing is an NP-hard optimization problem. Load balancing of nonpreemptive independent tasks on virtual machines (VMs) is an important aspect of task scheduling in clouds. Whenever certain VMs are overloaded and remaining VMs are under loaded with tasks for processing, the load has to be balanced to achieve optimal machine utilization. In this paper, we propose an algorithm named honey bee behavior inspired load balancing (HBB-LB), which aims to achieve well… 

Figures and Tables from this paper


A Comparative Study into Distributed Load Balancing Algorithms for Cloud Computing
This paper investigates three possible distributed solutions proposed for load balancing; approaches inspired by Honeybee Foraging Behaviour, Biased Random Sampling and Active Clustering.
Load Balancing in Grid Environment using Machine Learning - Innovative Approach
Focus of this paper is on analyzing Load Balancing requirements in a Grid environment and proposing an algorithm with machine learning concepts to find more efficient algorithm.
Dynamic Load Balancing Strategy for Grid Computing
This paper proposes a layered algorithm which achieve dynamic load balancing in grid computing using a tree model and presents the following main features: it is layered; it supports heterogeneity and scalability; and it is totally independent from any physical architecture of a grid.
Task Load Balancing Strategy for Grid Computing
A dynamic tree-based model to represent Grid architecture in order to manage workload is proposed and a hierarchical load balancing strategy and associated algorithms based on neighbourhood propriety are developed to decrease the amount of messages exchanged between Grid resources.
CloudSim: a toolkit for modeling and simulation of cloud computing environments and evaluation of resource provisioning algorithms
The result of this case study proves that the federated Cloud computing model significantly improves the application QoS requirements under fluctuating resource and service demand patterns.
Optimization of Distribution Network Configuration for Loss Reduction Using Artificial Bee Colony Algorithm
A new method which applies an artificial bee colony algorithm for determining the sectionalizing switch to be operated in order to solve the distribution system loss minimization problem is presented.
Adaptive load sharing in homogeneous distributed systems
It is shown that extremely simple adaptive load sharing policies, which collect very small amounts of system state information and which use this information in very simple ways, yield dramatic performance improvements.
Artificial bee colony algorithm
The main topic of this paper is to give an extensive literature survey of the algorithm and its application areas and to present a bibliographical base to the researchers and enlighten them with ABC algorithm.
Modelling collective foraging by means of individual behaviour rules in honey-bees
The significance of the following issues is discussed: the role of internal and external information, source profitability, the spatial precision of the dance communication, the ability to search for a source after the source position has been transmitted, the tendency to abandon a deteriorated source, and the concepts of scout, recruit, (un)employed forager, and foraging history.