Dynamic Load Balancing and Distribution Algorithm in Distributed Cloud Computing

Abstract

This article proposes an algorithm for dynamic load distribution and balancing in distributed cloud computing. A mathematical model and algorithm of a two-level load management system for virtual clusters of a data center have been developed. At the first management level, virtual machines (VMs) are assigned to physical servers. At the same time, a greedy algorithm is used with time restrictions in searching for acceptable load distribution alternatives. The second level of management is implemented considering the chaotic structure of network traffic between the data center and users. Checking for the chaotic nature of a time series of information traffic is conducted using the Lyapunov exponents. The predictive model of the load intensity is implemented using the method of phase space reconstruction based on a set of values of a one-dimensional time series. When building a reconstructed phase space attractor, the time delay value is selected from the condition of reaching the zero value of the autocorrelation function, and the dimension of the embedding is determined by the angle of inclination of the straight line approximating the dependence of the value of the correlation integral on the radius of a given threshold point. The Tayler window is used to exclude correlated points in the numerical series. The criterion for evaluating the effectiveness of the developed algorithm is an integral indicator of the deviation of the load of each server from a given level.