Optimal energy consumption and throughput for workflow applications on distributed architectures

Abstract

In this article we study both the throughput and the energy optimization problem for a distributed system subject to failures that executes a workflow at different speed levels. The application is modeled as a directed acyclic graph composed of typed tasks linked by dependency constraints. A continuous flow, or a great number of application instances, has to be processed. Optimizing the collaborative system performance implies to increase the throughput-the number of application instances processed by time unit-or to decrease the period-the time needed to output one instance of the system. The system is designed as a collaborative platform of distributed machines. Each machine collaborates with others by performing all the instances of at least one task of the DAG. The problem we tackle is to optimize the configuration of the platform. In this paper we propose two polynomial algorithms that optimize the two objectives of period (i.e., throughput) minimization and energy minimization. We prove that the proposed algorithms give optimal results. Our optimization approach is hierarchic in that we either minimize the energy consumption for the optimal period or minimize the period for the optimal energy consumption. Moreover a minor modification of our algorithms allows to compute the Pareto front between the two optimal solutions.

Modeling and simulation of time and value throughputs of data-aware workflow processes

“…As we discussed above, the time and value throughputs proposed in this paper are more accurate and efficient than the traditional throughputs. Activity based approach (Sriram et al 2013;Liu et al 2008;Pacini et al 2015;Othman et al 2012;Zhang et al 2015) and completion time based approach (Liu et al 2013(Liu et al , 2014 cannot directly be applied In order to show the advantages of our approach, we compare it with activity based approach and completion time based approach based on the motivation case. For the execution of instances and the length of time durations, we use the same settings in "Analysis of results" section.…”

“…Throughput of workflow processes (Sriram et al 2013;Liu et al 2008;Pacini et al 2015;Othman et al 2012;Zhang et al 2015) is usually used to measure the number of activities completed in a time duration contributing to the completion of the entire batch of processes. It is critical for the schedule and optimization of workflow processes, especially for a realtime application with dynamic workloads.…”

“…There exists some research works related to the problem of analyzing throughput of workflow processes, and they can be classified into analysis of throughputs (Sriram et al 2013;Liu et al 2008;Pacini et al 2015;Othman et al 2012;Zhang et al 2015;Liu et al 2013Liu et al , 2014 and simulation of workflow processes (Pla et al 2014;Siller et al 2008;Liu et al 2012;Cheng et al 2011;Catalano et al 2009;Xia et al 2012;Cheng et al 2013).…”

“…Pacini et al (2015) consider the number of serviced users in a time duration as throughput. Othman et al (2012) propose a method to optimize the throughput which is the number of activities executed in a time duration for workflows. Zhang et al (2015) propose a new iterative ordinal optimization (IOO) method which aims at generating more efficient schedules from a global perspective over a long period based on the throughput of workflow.…”

“…This kind of research works can be further divided into two aspects: activity based approach (Sriram et al 2013;Liu et al 2008;Pacini et al 2015;Othman et al 2012;Zhang et al 2015) and completion time based approach (Liu et al 2013(Liu et al , 2014. The former is not reliable for the analysis workflow processes, since the throughputs in activity based approach are used to measure the number of activities or workflows completed in a time duration.…”