@article {73358, title = {Comparative Study Load Balance Algorithms for Map Reduce Environment}, journal = {International Journal of Applied Information Systems (IJAIS) }, volume = {7}, year = {2014}, abstract = {

MapReduce is a famous model for data-intensive parallel computing in shared-nothing clusters. One of the main issues in MapReduce is the fact of depending its performance mainly on data distribution. MapReduce contains simple load balance technique based on FIFO job scheduler that serves the jobs in their submission order but unfortunately it is insufficient in real world cases as it missed many factors that impact the performance
such as heterogeneity factor and data skewness, so Load
balancing is important to make all resources utilized evenly
and more efficiently. There are two main schemes in load balancing
a- Static Load Balancing Schemes b- Dynamic load
balancing. The main aim of this work is to study and compare
existing Load Balance algorithms also to illustrate the features
of Load Balance algorithms

}, author = {Hesham A. Hefny and Mohamed Helmy Khafagy and Ahmed M Wahdan} }