Energy Distribution Through Lifetime Estimation and Smartphone Usage Patterns
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Today, smartphones have become an important part of our day to day life. Every day, practically every one of us wakes up in the morning hearing the sound of an alarm coming from our smartphone. First thing in the morning, we see the LED flashing on the phone and we have the urge to check all the notifications we got during the night. We unplug our phone from the charger. We read some notifications, we ignore some, we reply to some. Finally, we get out of the bed. We use it all day for everything: replying to emails, text messages and social networking. Finally, we go to bed, plug it back into the charger cable. We touch it until our eyelids close for the night's sleep. We have this routine usage of our smartphone almost every day. Every user uses his/her phone in his/her own way. Not all the people are the same. Not all the people have the same routine of life. But our smartphone is not really smart enough to learn our routine and adapt to us. Our smartphone does not understand our needs. Either it just performs on its own or it performs only after we ask. There is a lot of areas that need automatic adaptation. Smartphones are the devices that perform tasks equal to a laptop or a desktop machine but with limited resources like battery, memory, screen size, etc. Unlike laptop users, smartphone users do not carry chargers with them all the time. Considering smartphone's limited battery as a serious concern, the battery would be the main area that needs automatic adaptation. Smartphones should know the user's recharge cycle and use the available energy efficiently by spending when it is in excess and reserving when it is in shortage. Computation complexity has been doubling every couple of years. But, the battery capacity has been doubling every 10 years. So, it is our responsibility to use the energy efficiently without a compromise in user experience. We propose ENDLESS (Energy Distribution Through Lifetime Estimation and Smartphone Usage Patterns) to determine if energy is to be saved for future use or if it can be consumed for present use according to the estimations of the next recharge time, applications and services that might be used in the near future and how much battery would be needed.