Toward using software metrics as indicator to measure power consumption of mobile application: A case study

Abstract

Battery capacity of mobile devices is a critical issue for developing green mobile applications. Therefore, energy efficiency has become a major concern nowadays for energy restricted embedded system such as smartphones and tablets. In industry, it is a challenge for them to develop an energy efficient product while meeting customer expectation. In previous study, there is lack of method that uses software metrics to measure power consumption of mobile applications. In this paper we have identified several software metrics that can be used as indicator to measure mobile application power consumption. The objective of this study is to which identify software metrics is suitable act as indicators to measure power consumption of mobile applications. This can help mobile software designer to measure power used for their mobile applications in the early design phase. In order to prove this concept, we randomly select two open source mobile applications as our case study. The power used of a mobile application is collected by using Trepn Profiler (Power profiling tool for Qualcomm processor CPU). We capture the actual power consumption and estimated power consumption (without calculate Android OS and profiling tool power) with the profiler. There are overall 18 available metrics based on Object-Oriented Metrics. We map the 18 metrics with the power consumption captured by Trepn Profiler. The results shown that McCabe cyclomatic complexity, number of parameters, nested block depth, weighted methods per class, number of overridden method, number of methods, total lines of code and method lines have significant relationship with power consumption of mobile application. Therefore, these eight metrics can be used as the indicator to measure mobile applications' power consumption.

Dynamics of Research into Modeling the Power Consumption of Virtual Entities Used in the Telco Cloud

“…We note several experiments, e.g., [ 55 , 56 , 68 , 71 , 103 , 104 , 105 ], that target power consumption but less than 12% of the RUs in our corpus approach the problem in terms of some energy efficiency metric [ 49 , 50 , 65 , 85 ]. It is necessary to move beyond measurements of how much power was consumed, to measurements of how much power was consumed to carry out a specific task.…”

A Categorization of Power Measurement and Power Consumption Models in the Telco Cloud

“…We note several experiments, e.g. [59,60,81,83,[114][115][116] that target power consumption but less than 12% of the RUs in our corpus approach the problem in terms of some energy efficiency metric [57,58,78,97]. It is necessary to move beyond measurements of how much power was consumed, to measurements of how much power was consumed to carry out a specific task.…”

InnoMetrics Dashboard: The Design, and Implementation of the Adaptable Dashboard for Energy-Efficient Applications Using Open Source Tools

“…By working closely with the industry representatives, as well as consulting the literature in this field (data and findings revealed in [22][23][24][25][26]), we have come up with the list of metrics that the potential users would find most valuable [27][28][29] (Table 1).…”

“…It can be followed by better development estimates and more qualified product that can maintain the customers expectations. As it was stated in the paper [25], developers need a set of valid indicators in assisting the developers for better applications. Thus, the study results showed that Cyclomatic complexity, Number of classes, LOC, number of parameters, nested block depth, number of methods, weighted methods per class and method lines have direct relationship with power consumption of mobile applications.…”