@article {2078,
	title = {Proactive Thermal Management in Green Datacenters},
	journal = {Journal of Supercomputing (Springer)},
	volume = {60},
	year = {2012},
	month = {May},
	pages = {165-195},
	chapter = {165},
	abstract = {The increasing demand for faster computing and high storage capacity has
resulted in an increase in energy consumption and heat generation in datacenters. Because of the increase in heat generation, cooling requirements have become a critical
concern, both in terms of growing operating costs as well as their environmental and
societal impacts. Presently, thermal management techniques make an effort to thermally profile and control datacenters{\textquoteright} cooling equipment to increase their efficiency.
In conventional thermal management techniques, cooling systems are triggered by
the temperature crossing predefined thresholds. Such reactive approaches result in
delayed response as the temperature may already be too high, which can result in
performance degradation of hardware.
In this work, a proactive control approach is proposed that jointly optimizes the
air conditioner compressor duty cycle and fan speed to prevent heat imbalance{\textemdash}the
difference between the heat generated and extracted from a machine{\textemdash}thus minimizing the cost of cooling. The proposed proactive optimization framework has two
objectives: (i) minimize the energy consumption of the cooling system, and (ii) minimize the risk of equipment damage due to overheating. Through thorough simulations
comparing the proposed proactive heat-imbalance estimation-based approach against
conventional reactive temperature-based schemes, the superiority of the proposed approach is highlighted in terms of cooling energy, response time, and equipment failure
risk.},
	author = {E. K. Lee and I. S. Kulkarni and D Pompili}
}
@article {164,
	title = {Task Allocation for Networked Underwater Vehicles in Critical Missions},
	journal = {IEEE Journal of Selected Areas in Communications},
	volume = {28},
	year = {2010},
	month = {June},
	pages = {716-727},
	abstract = {Underwater Acoustic Sensor Networks (UW-ASNs)
consist of stationary or mobile nodes such as Autonomous Underwater
Vehicles (AUVs), which may be classified as propellerdriven
vehicles and gliders, that are equipped with a variety of
sensors for performing collaborative monitoring tasks. The missions
entrusted to the AUVs in this work are critical to human life
and property, are bound by severe time and energy constraints,
and involve a high degree of inter-vehicular communication. In
this work, a task allocation framework for networked AUVs that
participate as a team to accomplish critical missions is developed.
The team formed as a result of this task allocation framework is
the subset of all deployed AUVs that is best suited to accomplish
the mission while adhering to the mission constraints. Research
specific to this area has been limited, hence a task allocation
framework for networked AUVs to accomplish critical missions
is proposed.},
	author = {I. S. Kulkarni and D Pompili}
}
@proceedings {170,
	title = {Coordination of Autonomous Underwater Vehicles for Acoustic Image Acquisition},
	year = {2008},
	month = {September},
	address = {San Francisco, CA, USA},
	abstract = {Underwater Acoustic Sensor Networks (UW-ASNs) consist of stationary
sensors or Autonomous Underwater Vehicles (AUVs) like
propeller-driven vehicles and gliders that are equipped with sensors
for performing collaborative monitoring tasks. In this paper,
a task optimization framework for image acquisition using a fleet
of underwater gliders and AUVs is proposed. The objective of the
framework is to form the best possible team and to find the optimal
trajectory to reach the selected target object. In this paper, the use
of a team of underwater gliders and AUVs for acquiring still images
of underwater objects is envisaged. Research specific to this
area has been limited. Hence, a framework based on energy minimization
for a team of gliders to complete the mission in given
time bound is proposed. Further, performance of propeller-driven
AUVs and gliders is compared to prove the energy efficiency of the
gliders over AUVs for missions with large time bound.},
	author = {I. S. Kulkarni and D Pompili}
}
