Conventional load balancing schemes are efficient at increasing the utilization of CPU, memory, and disk I/O resources in a Distributed environment. Most of the existing load-balancing schemes ignore network proximity and heterogeneity of nodes. Load balancing becomes more challenging as load variation is very large and the load on each server may change dramatically over time, by the time when a server is to make the load migration decision, the collected load status from other servers may no longer be valid. This will affect the accuracy, and hence the performance, of the load balancing algorithms. All the existing methods neglect the heterogeneity of nodes and contextual load balancing. In this seminar, context based load balancing and task allocation with network proximity of heterogeneous nodes will be studied.