The Computation and Transmission Rate Based (CTRB) Algorithm for Distributed Applications

In information systems, it is critical to reduce the total electrical power consumption of computers and networks in order to realize the digital ecosystems. In the extended power consumption laxity-based (EPCLB) algorithm, a server is selected in a set of servers so as to not only satisfy deadline constraint but also reduce the total power consumption of servers in general types of applications. However, each time a load balancer receives a new request, the load balancer has to collect the state on traffic and computation and transmission laxities of each server and calculate the estimated power consumption to perform the request. The load balancer spends large computation and communication resources to estimate the power consumption if the number of clients is increased. In addition, since the state of each server might be changed during the estimation process, it is difficult to correctly estimate the power consumption. In this paper, we newly propose a CTRB (computation and transmission rate based) algorithm to select a server in a set of possible servers so that the total power consumption of servers and the overhead of a load balancer can be reduced. We evaluate the CTRB algorithm in terms of the power consumption of servers and the overhead of a load balancer compared with the EPCLB and traditional round-robin (RR) algorithms.