An Architecture for Energy Management in
Wireless Sensor Networks
Xiaofan Jiang†, Jay Taneja†, Jorge Ortiz†, Arsalan Tavakoli†, Prabal Dutta†, Jaein Jeong†,
David Culler†?, Philip Levis‡, and Scott Shenker†
†UC Berkeley EECS Dept.
‡Stanford CS Dept.
?Arch Rock Corporation
Berkeley, California 94720 Stanford, California 94305 San Francisco, California 94105
1 Introduction
Sensornets are becoming more widely adopted for com-
mercial and scientific use and, in settings where battery re-
placement or recharging is difficult, it is important that sen-
sornets have long and predictable lifetimes. We thus expect
energy management to play an increasingly important role in
meeting user requirements. Today, system developers seek
a balance between network lifetime and performance, but
recent history shows that unexpected and dynamic environ-
mental conditions often scuttle expected energy budgets.
For example, many nodes in the Great Duck Island de-
ployment were conjectured to have died prematurely be-
cause unexpected overhearing of traffic caused radios to be-
come operational for longer than originally predicted [22].
This pattern was repeated in the Redwoods deployment, but
for a supposedly different reason: some nodes seemingly
died prematurely because they became disconnected from
the wireless network and depleted their batteries trying to re-
connect [24]. Even systems augmented with energy harvest-
ing are still susceptible to this type of problem. In the Trio
Testbed, seasonal and daily variations in solar power, the an-
gle of inclination of the solar cell, the effect of dirt and bird
droppings on the cells, and the inefficiencies in power stor-
age and transfer resulted in node duty cycles ranging from
20% to 100% [5].
The issues with these deployments arise from mistaken
assumptions, unforeseen difficulties, and unpredictable en-
vironmental dynamics. Solutions to these issues take two
extreme approaches. At one extreme, some have proposed
runtime adaptation to meet lifetime requirements [16] or en-
ergy avail