@proceedings {2303,
	title = {Deep learning with edge computing for localization of epileptogenicity using multimodal rs-fmri and eeg big data},
	year = {2017},
	publisher = {IEEE},
	author = {Hosseini, Mohammad-Parsa and Tran, Tuyen X and Pompili, Dario and Elisevich, Kost and Soltanian-Zadeh, Hamid}
}
@proceedings {2300,
	title = {Mobee: Mobility-Aware Energy-Efficient Coded Caching in Cloud Radio Access Networks},
	year = {2017},
	publisher = {IEEE},
	author = {Tran, Tuyen X and Kazemi, Fatemeh and Karimi, Esmaeil and Pompili, Dario}
}
@article {2299,
	title = {Mobile Edge Computing: Recent Efforts and Five Key Research Directions},
	journal = {IEEE COMSOC MMTC Commun.-Frontiers},
	year = {2017},
	month = {7},
	pages = {29-34},
	author = {Tran, Tuyen X and Hosseini, Mohammad-Parsa and Pompili, Dario}
}
@article {2302,
	title = {Optimized Deep Learning for EEG Big Data and Seizure Prediction BCI via Internet of Things},
	journal = {IEEE Transactions on Big Data},
	year = {2017},
	pages = {1{\textendash}1},
	publisher = {IEEE},
	author = {Hosseini, Mohammad-Parsa and Pompili, Dario and Elisevich, Kost and Soltanian-Zadeh, Hamid}
}
@proceedings {2304,
	title = {SSFB: Signal-Space-Frequency Beamforming for Underwater Acoustic Video Transmission},
	year = {2017},
	publisher = {IEEE},
	author = {Rahmati, Mehdi and Pompili, Dario}
}
@proceedings {2301,
	title = {Understanding the Computational Requirements of Virtualized Baseband Units using a Programmable Cloud Radio Access Network Testbed},
	year = {2017},
	publisher = {IEEE},
	author = {Tran, Tuyen X and Younis, Ayman and Pompili, Dario}
}
@article {2305,
	title = {UNISeC: Inspection, Separation, and Classification of Underwater Acoustic Noise Point Sources},
	journal = {IEEE Journal of Oceanic Engineering},
	year = {2017},
	publisher = {IEEE},
	author = {Rahmati, Mehdi and Pompili, Dario}
}
@proceedings {2256,
	title = {BD-ZCS: Multi-cell Interference Coordination via Zadoff-Chu Sequence-based Block Diagonalization},
	year = {2016},
	month = {2016},
	publisher = {IEEE},
	address = {San Francisco, CA, USA},
	author = {Xueyuan Zhao and Dario Pompili}
}
@proceedings {2292,
	title = {Cloud-based Deep Learning of Big EEG Data for Epileptic Seizure Prediction},
	year = {2016},
	month = {December/2016},
	publisher = {IEEE},
	address = {Greater Washington, D.C., USA},
	author = {Mohammad-Parsa Hosseini and Hamid Soltanian-Zadeh and Kost Elisevich and Dario Pompili}
}
@article {2259,
	title = {Comparative Performance Evaluation of Automated Segmentation Methods of Hippocampus from Magnetic Resonance Images of Temporal Lobe Epilepsy Patients},
	journal = {Medical Physics Journal},
	volume = {43},
	year = {2016},
	month = {Jan/2016},
	pages = {538-553},
	author = {Mohammad-Parsa Hosseini and Mohammad R. Nazem-Zadeh and Dario Pompili and Kourosh Jafari-Khouzani and Kost Elisevich and Hamid Soltanian-Zadeh}
}
@proceedings {2262,
	title = {Low-Power All-Analog Circuit for Rectangular-Type Analog Joint Source Channel Coding},
	year = {2016},
	month = {May/2016},
	publisher = {IEEE},
	address = {Montreal, Canada},
	author = {Xueyuan Zhao and Vidyasagar Sadhu and Dario Pompili}
}
@proceedings {2257,
	title = {MobiDiC: Exploiting the Untapped Potential of Mobile Distributed Computing via Approximation},
	year = {2016},
	month = {2016},
	address = {Sydney, Australia},
	author = {Parul Pandey and Dario Pompili}
}
@article {2265,
	title = {Model-based Thermal Anomaly Detection in Cloud Datacenters using Thermal Imaging},
	journal = {IEEE Transaction on Cloud Computing (TCC)},
	year = {2016},
	author = {E.K Lee and Hariharasudhan Viswanathan and Dario Pompili}
}
@article {2266,
	title = {Proactive Thermal-aware Resource Management in Virtualized HPC Cloud Datacenters},
	journal = {IEEE Transaction on Cloud Computing (TCC)},
	year = {2016},
	author = {E. K Lee and Hariharasudhan Viswanathan and Dario Pompili}
}
@proceedings {2291,
	title = {Real-time Epileptic Seizure Detection from EEG Signals via Random Subspace Ensemble Learning},
	year = {2016},
	month = {July/2016},
	publisher = {IEEE},
	address = {Wurzburg, Germany},
	author = {Mohammad-Parsa Hosseini and Abolfazl Hajisami and Dario Pompili}
}
@article {2267,
	title = {RescueNet: Reinforcement-learning-based communication framework for emergency networking},
	journal = {Computer Networks (Elsevier)},
	volume = {98},
	year = {2016},
	month = {April/2016},
	pages = {14-28},
	author = {E. K Lee and Hariharasudhan Viswanathan and Dario Pompili}
}
@proceedings {2273,
	title = {Secure Mobile Technologies for Proactive Critical Infrastructure Situational Awareness},
	year = {2016},
	publisher = {IEEE},
	address = {Waltham, MA},
	author = {G. Salles-Loustau and V. Sadhu and D. Pompili and S. Zonouz and V. Sritapan}
}
@proceedings {2274,
	title = {AMMCA: Acoustic Massive MIMO with Carrier Aggregation for Boosting the Underwater Communication Data Rate},
	year = {2015},
	publisher = {IEEE},
	address = {Washington, DC},
	author = {Xueyuan Zhao and Dario Pompili}
}
@proceedings {2246,
	title = {Cloud-CFFR: Coordinated Fractional Frequency Reuse in Cloud Radio Access Network (C-RAN)},
	year = {2015},
	month = {2015},
	publisher = {IEEE},
	address = {Dallas, Texas, USA},
	author = {Abolfazl Hajisami and Dario Pompili}
}
@article {2271,
	title = {A Distributed Computing Framework for Real-time Detection of Stress and of its Propagation in a Team},
	journal = { IEEE Journal of Biomedical and Health Informatics (JBHI)},
	year = {2015},
	author = {Parul Pandey and E.K Lee and Dario Pompili}
}
@article {2277,
	title = {Distributed Data-centric Adaptive Sampling for Cyber-Physical Systems},
	journal = {ACM Transaction on Autonomous and Adaptive Systems (TAAS)},
	volume = {9},
	year = {2015},
	pages = {1-21},
	author = {E.K Lee and Hariharasudhan Viswanathan and Dario Pompili}
}
@proceedings {2247,
	title = {DJP: Dynamic Joint Processing for Interference Cancellation in Cloud Radio Access Networks},
	year = {2015},
	month = {2015},
	publisher = {IEEE},
	address = {Boston, Massachusetts, USA},
	author = {Abolfazl Hajisami and Dario Pompili}
}
@article {2272,
	title = {Dynamic Collaboration between Networked Robots and Clouds in Resource-constrained Environments},
	journal = {IEEE Transaction on Automation Science and Engineering (T-ASE)},
	volume = {12},
	year = {2015},
	month = {April/ 2015},
	pages = {471-480},
	author = {Parul Pandey and Dario Pompili and Jingang Yi}
}
@article {2249,
	title = {Dynamic provisioning and allocation in Cloud Radio Access Networks (C-RANs)},
	journal = { Ad Hoc Networks (Elsevier)},
	volume = {30},
	year = {2015},
	month = {2015},
	pages = {128{\textendash}143},
	author = {Dario Pompili and Abolfazl Hajisami and Hariharasudhan Viswanathan}
}
@proceedings {2248,
	title = {Dynamic Provisioning for High Energy Efficiency and Resource Utilization in Cloud RANs},
	year = {2015},
	month = {2015},
	publisher = {IEEE},
	address = {Dallas, Texas, USA},
	author = {Abolfazl Hajisami and Tuyen X. Tran and Dario Pompili}
}
@proceedings {2253,
	title = {Dynamic Radio Cooperation for Downlink Cloud-RANs with Computing Resource Sharing},
	year = {2015},
	month = {2015},
	publisher = {IEEE},
	address = {Dallas, Texas, USA},
	author = {Tuyen X. Tran and Dario Pompili}
}
@proceedings {2251,
	title = {Interference Cancellation in Multiuser Acoustic Underwater Networks Using Probabilistic SDMA},
	year = {2015},
	month = {2015},
	publisher = {IEEE},
	address = {Dallas, Texas, USA},
	author = {Mehdi Rahmati and Dario Pompili}
}
@article {2269,
	title = {Modeling Position Uncertainty of Networked Autonomous Underwater Vehicles},
	journal = {Ad Hoc Networks (Elsevier)},
	volume = {34},
	year = {2015},
	month = {Nov/2015},
	pages = {184-195},
	author = {Baozhi Chen and Dario Pompili}
}
@article {2270,
	title = {Uncertainty-aware Autonomic Resource Provisioning for Mobile Cloud Computing},
	journal = {IEEE Transaction on Parallel and Distributed Systems },
	volume = {26},
	year = {2015},
	month = {August/2015},
	pages = {2363-2372},
	author = {Hariharasudhan Viswanathan and E.K Lee and Dario Pompili}
}
@proceedings {2258,
	title = {uwMIMO-HARQ: Reliable Hybrid ARQ Scheme in Underwater Acoustic MIMO Channels},
	year = {2015},
	month = {October/2015},
	publisher = {ACM},
	address = {Washington DC, USA},
	author = {Mehdi Rahmati and Dario Pompili}
}
@proceedings {2245,
	title = {{\textquotedblleft}Cocktail Party in the Cloud{\textquotedblright}: Blind Source Separation for Co-operative Cellular Communication in Cloud RAN},
	year = {2014},
	month = {2014},
	publisher = {IEEE},
	address = {Philadelphia, Pennsylvania, USA},
	author = {Abolfazl Hajisami and Hariharasudhan Viswanathan and Dario Pompili}
}
@article {2123,
	title = {Laboratory Validation of Inertial Body Sensors to Detect Cigarette Smoking Arm Movements},
	journal = {Electronics},
	volume = {3},
	year = {2014},
	month = {2014},
	pages = {87-110},
	author = {B. R. Raiff and C. Karata{\c s} and E. A. McClure and D. Pompili and T. A. Walls}
}
@article {2122,
	title = {A QoS-aware Underwater Optimization Framework for Inter-vehicle Communication using Acoustic Directional Transducers},
	journal = {to appear in IEEE Transactions on Wireless Communications},
	year = {2014},
	author = {Baozhi Chen and Dario Pompili}
}
@article {2109,
	title = {Region of Feasibility of Interference Alignment in Underwater Sensor Networks},
	journal = {IEEE Journal of Oceanic Engineering},
	volume = {39},
	year = {2014},
	month = {01/2014},
	pages = {189 - 202},
	publisher = {IEEE},
	chapter = {189 - 202},
	author = {P. Pandey and M. Hajimirsadeghi and D. Pompili}
}
@article {2275,
	title = {Reliable Geocasting for Random-access Underwater Acoustic Sensor Networks},
	journal = { Ad Hoc Networks (Elsevier)},
	volume = {21},
	year = {2014},
	month = {Oct/2014},
	pages = {134-146},
	author = {Baozhi Chen and Dario Pompili}
}
@proceedings {2252,
	title = {Separation and Classification of Underwater Acoustic Sources},
	year = {2014},
	month = {2014},
	publisher = {IEEE},
	address = {NATO Centre, Sestri Levante (La Spezia), Italy},
	author = {Mehdi Rahmati and Parul Pandey and Dario Pompili}
}
@proceedings {2250,
	title = {Statistical Validation of Automatic Methods for Hippocampus Segmentation in MR Images of Epileptic Patients},
	year = {2014},
	month = {2014},
	publisher = {IEEE},
	author = {Mohammad-Parsa Hosseini and Nazem-Zadeh and R Mohammad and Dario Pompili and Hamid Soltanian-Zadeh}
}
@proceedings {2106,
	title = {Enabling Real-time In-Situ Processing of Ubiquitous Mobile-Application Workflows},
	year = {2013},
	month = {Oct./2013},
	address = {Hangzhou, China},
	author = {H. Viswanathan and E. K. Lee and D. Pompili}
}
@proceedings {2098,
	title = {Learning-based Framework for Policy-aware Cognitive Radio Emergency Networking},
	year = {2013},
	month = {Dec/2013},
	publisher = {Proc. of IEEE Global Telecommunications Conference (GLOBECOM)},
	address = {Atlanta, GA},
	author = {E. K. Lee and H. Viswanathan and D. Pompili}
}
@article {2110,
	title = {Minimizing Position Uncertainty for Under-Ice Autonomous Underwater Vehicles},
	journal = {to appear in Computer Networks (Elsevier)},
	year = {2013},
	author = {B. Chen and D. Pompili}
}
@proceedings {2075,
	title = {Model-based Thermal Anomaly Detection in Cloud Datacenters},
	year = {2013},
	month = {May},
	address = {Cambridge, MA},
	author = {E. K. Lee and H. Viswanathan and D Pompili}
}
@proceedings {2099,
	title = {Real-time Tracking of Stress Propagation using Distributed Granger Causality},
	year = {2013},
	month = {Sept/2013},
	publisher = {Proc. of ACM International Conference on Body Area Networks (BodyNets)},
	address = {Boston, MA},
	author = {E. K. Lee and P. Pandey and D. Pompili}
}
@article {2096,
	title = {Thermal Camera Networks for Large Datacenters using Real-Time Thermal Monitoring Mechanism},
	journal = {Journal of Supercomputing (Springer)},
	volume = {64},
	year = {2013},
	month = {2013},
	pages = {383-408},
	chapter = {383},
	abstract = {Thermal cameras provide fine-grained thermal information that enables
monitoring and autonomic thermal management in large datacenters. The real-time
thermal monitor network employing thermal cameras is proposed to cooperatively
localize hotspots and extract their characteristics (i.e., temperature, size, and shape).
These characteristics are adopted to classify the causes of hotspots and make energy efficient
thermal management decisions such as job migration. Specifically, a sculpturing
algorithm for extracting and reconstructing shape characteristics of hotspots is
proposed to minimize the network overhead. Experimental results show the validity
of all the algorithms proposed in this paper.},
	author = {H. Liu and E. K. Lee and D. Pompili and X. Kong}
}
@proceedings {1973,
	title = {Adaptive Sampling Based on Deterministic Compressive Sensing using Autonomous Underwater Vehicles},
	year = {2012},
	month = {Sept. 2012},
	address = {Arenzano (GE), Italy},
	abstract = {To achieve efficient and cost-effective sensing coverage of the vast under-sampled 3D aquatic volume, intelligent adaptive sampling strategies involving Autonomous Underwater Vehicles (AUVs) endowed with underwater wireless (acoustic) communication capabilities become essential. These AUVs should coordinate and steer through the region of interest, and cooperatively sense, preprocess and transmit measured data to onshore stations for processing and analysis. Given a scalar field, i.e, a phenomenon (e.g, temperature, salinity etc.) to sample, the AUVs should coordinate to take measurements using minimal resources (time or energy) in order to reconstruct the field with admissible error. A novel adaptive sampling solution to minimize the sampling cost is proposed, which requires the AUVs to take small number of samples from the field. We observe via simulations that our proposed solution outperforms existing solutions that are based on Compressive Sensing techniques.},
	author = {B. Chen and P. Pandey and D Pompili}
}
@proceedings {1924,
	title = {An Autonomic Resource Provisioning Framework for Mobile Computing Grids},
	year = {2012},
	month = {September},
	address = {San Jose, CA},
	author = {H. Viswanathan and E. K. Lee and I. Rodero and D Pompili}
}
@inbook {2283,
	title = {A Communication Framework for Networked Autonomous Underwater Vehicles},
	booktitle = {The Art of Wireless Sensor Networks  (Springer)},
	year = {2012},
	publisher = {Habib Ammari, Ed},
	organization = {Habib Ammari, Ed},
	author = {Baozhi Chen and Dario Pompili}
}
@article {1991,
	title = {Coordination-free Safety Messages Dissemination Protocol for Vehicular Networks},
	journal = {IEEE Transaction on Vehicular Technology},
	year = {2012},
	month = {May},
	author = {S. Oh and M. Gruteser and D Pompili}
}
@proceedings {2280,
	title = {A Distributed Adaptive Sampling Solution using Autonomous Underwater Vehicles},
	year = {2012},
	publisher = {ACM},
	address = {Los Angeles, CA},
	author = {Baozhi Chen and Parul Pandey and Dario Pompili}
}
@inbook {2284,
	title = {Emergency Networking in Licensed Spectrum using Cognitive Radios },
	booktitle = {Cognitive Radio for Wireless Cellular and Vehicular Networks},
	year = {2012},
	publisher = {H. Venkataraman and G-M. Muntean, Eds., Springer},
	organization = {H. Venkataraman and G-M. Muntean, Eds., Springer},
	author = {H. Viswanathan and Dario Pompili}
}
@inbook {1906,
	title = {Emergency Networking in Licensed Spectrum using Cognitive Radios - Challenges and Insights},
	booktitle = {Cognitive Radio and its Applications for Next Generation Cellular and Wireless Networks, H. Venkataraman and G-M. Muntean},
	year = {2012},
	publisher = {Springer},
	organization = {Springer},
	chapter = {Emergency Networking in Licensed Spectrum using Cognitive Radios - Challenges and Insights},
	author = {H. Viswanathan and D Pompili}
}
@article {2077,
	title = {Energy-efficient Thermal-aware Autonomic Management of Virtualized HPC Cloud Infrastructure},
	journal = {Journal of Grid Computing (Springer)},
	volume = {10},
	year = {2012},
	month = {Sept},
	pages = {447-473},
	chapter = {447},
	abstract = {Virtualized datacenters and clouds are
being increasingly considered for traditional
High-Performance Computing (HPC) workloads
that have typically targeted Grids and conventional HPC platforms. However, maximizing
energy efficiency and utilization of datacenter resources, and minimizing undesired thermal behavior while ensuring application performance and
other Quality of Service (QoS) guarantees for
HPC applications requires careful consideration
of important and extremely challenging tradeoffs.
Virtual Machine (VM) migration is one of the most common techniques used to alleviate thermal anomalies (i.e., hotspots) in cloud datacenter servers as it reduces load and, hence, the
server utilization. In this article, the benefits of
using other techniques such as voltage scaling and
pinning (traditionally used for reducing energy
consumption) for thermal management over VM
migrations are studied in detail. As no single
technique is the most efficient to meet temperature/performance optimization goals in all situations, an autonomic approach that performs
energy-efficient thermal management while ensuring the QoS delivered to the users is proposed.
To address the problem of VM allocation
that arises during VM migrations, an innovative application-centric energy-aware strategy for
VM allocation is proposed. The proposed strategy ensures high resource utilization and energy efficiency through VM consolidation while
satisfying application QoS by exploiting knowledge obtained through application profiling along
multiple dimensions (CPU, memory, and network bandwidth utilization). To support our
arguments, we present the results obtained
from an experimental evaluation on real hardware using},
	author = {I. Rodero and H. Viswanathan and E. K. Lee and M. Gamell and D Pompili}
}
@proceedings {1922,
	title = {Leveraging Mobile Grid Computing for Interference Alignment and Cancelation},
	year = {2012},
	address = {Orlando, FL},
	author = {Parul Pandey and H. Viswanathan and D Pompili}
}
@inbook {2282,
	title = {Localization in Underwater Acoustic Sensor Networks},
	booktitle = {Computing Handbook Set - Computer Science },
	volume = {1},
	year = {2012},
	publisher = {Teofilo Gonzalez, Ed},
	organization = {Teofilo Gonzalez, Ed},
	author = {Baozhi Chen and Dario Pompili}
}
@proceedings {1893,
	title = {Mobile Grid Computing for Data- and Patient-centric Ubiquitous Healthcare},
	year = {2012},
	month = {June},
	address = {Seoul, Korea},
	abstract = {A new context-aware data- and patient-centric
paradigm for ubiquitous healthcare is central to deliver personalized
healthcare solutions to the elderly and the physically
challenged. However, this new paradigm requires real-time in the-
field processing of wirelessly collected vital signs using inherently
complex physiological models and analysis of the processed
information (derived physiological parameters) under context
(e.g., location, ambient conditions, current physical activity)
to extract knowledge about the health condition of patients.
As the computational capabilities of biomedical sensor nodes
are insufficient to run these models, an innovative resource
provisioning framework that harnesses the computing capabilities
of under-utilized electronic devices in the vicinity (e.g., smart
phones, laptops, tablets, DVRs, medical terminals) to form a
mobile computing grid is presented. The framework is imparted
with self-optimization and self-healing capabilities for efficiency
and robustness under uncertainty, respectively. The proposed
mobile grid management framework serves as a key enabling
technology for Internet-of-Things- (IoT-) based next-generation
ubiquitous healthcare solutions.},
	author = {H. Viswanathan and E. K. Lee and D Pompili}
}
@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}
}
@proceedings {1974,
	title = {On the Region of Feasibility of Interference Alignment in Underwater Sensor Networks},
	year = {2012},
	month = {Sept. 2012},
	address = {NATO Centre, La Spazia, Italy},
	abstract = {To enable underwater applications such as coastal and tactical surveillance, undersea explorations, and pic- ture/video acquisition, there is a need to achieve high data- rate underwater acoustic communications, which translates into attaining high acoustic channel spectral efficiencies. Interference Alignment (IA) technique, which has recently been proposed for radio-frequency MIMO terrestrial communication systems, aims at improving the spectral efficiency by enabling nodes to transmit data simultaneously at a rate equal to half of the interference-free channel capacity. While promising, there are challenges to be solved for the use of IA underwater, i.e., imperfect acoustic channel knowledge, high computational complexity, and high communication delay. In this paper, a feasibility study on the practical employment of IA underwater is presented, and a novel distributed computing framework for sharing processing resources in the network so to parallelize an iterative IA algorithm is proposed.},
	author = {P. Pandey and D Pompili}
}
@article {103,
	title = {Research Challenges in Computation, Communication, and Context Awareness for Ubiquitous Healthcare},
	journal = {IEEE Communications Magazine},
	volume = {50},
	year = {2012},
	month = {May},
	pages = {92{\textendash}99},
	abstract = {A new paradigm for ubiquitous healthcare characterized by pervasive continuous vital sign data collection, real-time processing of monitored data to derive meaningful physiological parameters, and context-aware data- and patient-centric decision making, is central to deliver personalized healthcare solutions to the elderly and the physically challenged. However, this new paradigm requires real-time processing of wirelessly collected vital signs using inherently complex physiological models and analysis of the processed information under context (e.g., location, ambient conditions, current physical activity) to extract knowledge about the health condition of patients. As the computational capabilities of biomedical sensor nodes are insufficient to run these models, this article presents an innovative resource provisioning framework that organizes and harnesses the computing capabilities of under-utilized electronic devices in the vicinity (e.g., laptops, tablets, PDAs, DVRs, medical terminals) in home and hospital settings. Novel wireless communication solutions for reliable vital sign transmission and algorithms for acquiring context awareness to support this framework are also discussed.},
	author = {H. Viswanathan and Chen, Baozhi and Pompili, Dario}
}
@article {1990,
	title = {Team Formation and Steering Algorithms for Underwater Gliders using Acoustic Communications},
	journal = {Computer Communication (Elsevier)},
	volume = {35},
	year = {2012},
	month = {May},
	pages = {1017-1028},
	abstract = {In order to take measurements in space and time from the undersampled vast ocean, it is necessary to
employ multiple autonomous underwater vehicles, such as gliders, that communicate and coordinate
with each other. These vehicles need to form a team in a specific formation, steer through the 3D region
of interest, and take application-dependent measurements such as temperature and salinity. In this article, team formation and steering algorithms relying on underwater acoustic communications are proposed in order to enable glider swarming that is robust against ocean currents and acoustic channel
impairments (e.g., high propagation and transmission delay, and low communication reliability). Performance of the proposed algorithms is evaluated and compared against existing solutions, which do not
rely on underwater communications, using different ocean current models.},
	author = {B. Chen and D Pompili}
}
@proceedings {1894,
	title = {Uncertainty-Aware Localization Solution for Networked Under-Ice Autonomous Underwater Vehicles},
	year = {2012},
	month = {June},
	address = {Seoul, Korea},
	author = {B. Chen and D Pompili}
}
@proceedings {1923,
	title = {VMAP: Proactive Thermal-aware Vitual Machine Allocation in HPC Cloud Datacenters},
	year = {2012},
	address = {Pune, India},
	author = {E. K. Lee and H. Viswanathan and D Pompili}
}
@article {160,
	title = {Data Center Local Thermal Management Based on Thermal Cameras Networks },
	journal = {Chinese Journal of Electronics},
	volume = {20},
	year = {2011},
	month = {April},
	pages = {347-351},
	abstract = {Global data center capacity is growing
rapidly, consuming more financial resources and emitting
more greenhouse gases. A significant portion of typical
data centers energy consumption can be apportioned to
the cooling infrastructure. In this paper, we proposed a
Thermal camera network (TCN) to improve utilization of
the cooling infrastructure. It can cool the hotspots intelligently
instead of the whole data center. A TCN is
composed of multiple thermal cameras and actors, which
can wirelessly communicate with each other. Actors will
cool the region where hotspots appear as soon as thermal
cameras locate the hotspots. In that way, the TCN can
save substantial energy in some meaning. In addition, this
paper addresses the method of cooperatively detection and
formulates the coordinates of the hotspot located by multiple
thermal cameras.},
	author = {H. Liu and E. K. Lee and D Pompili and X. Kong}
}
@article {2276,
	title = {Data Center Local Thermal Management Based on Thermal Cameras Networks},
	journal = {Chinese J. of Electronics},
	volume = {20},
	year = {2011},
	month = {April/ 2011},
	pages = {347-351},
	author = {H. Liu and E.K Lee and Dario Pompili}
}
@article {162,
	title = {Human Motion Recognition Using a Wireless Sensor-based Wearable System},
	journal = {Personal and Ubiquitous Computing (Springer)},
	year = {2011},
	month = {September},
	pages = {1-14},
	abstract = {The future of human computer interaction
systems lies in how intelligently these systems can take
into account the user{\textquoteright}s context. Research on recognizing
the daily activities of people has progressed steadily, but
little focus has been devoted to recognizing jointly activities
as well as movements in a specific activity. For many
applications such as rehabilitation, sports medicine, geriatric
care, and health/fitness monitoring the importance of
combined recognition of activity and movements can drive
health care outcomes. A novel algorithm is proposed that
can be tuned to recognize on-the-fly range of activities and
fine movements within a specific activity. Performance of
the algorithm and a case study on obtaining optimal features
from sensor and parameter values for the algorithm to
detect fine motor movements are presented.},
	author = {J. P. Varkey and D Pompili and T. Walls}
}
@conference {120,
	title = {On the Impact of Neighborhood Discovery on Geographical Routing in Wireless Sensor Networks},
	booktitle = {Proc. of IEEE Sarnoff Symposium},
	year = {2011},
	month = {May},
	address = {Princeton, NJ, USA},
	abstract = {In Wireless Sensor Networks (WSNs), sensing nodes
operate in dynamic environments resulting in neighboring nodes
being discovered or lost at any moment causing the network
topology to change constantly. Hence, routing schemes especially
geographical ones (which use node positions to route data
packets) require periodic exchange of control packets to discover
neighboring nodes. Even though it is intuitive that the overhead
caused by their periodic broadcasts may affect the end-to-end
performance of the routing scheme, previous works have not
thoroughly studied the impact of transmission power and frequency
of control packets in static as well as mobile environments.
Hence, based on our study, Distributed Neighborhood Discovery
Protocol (DNDP) is proposed that can make online decisions to
find the best transmit power and frequency for sending discovery
packets so to minimize the effect on routing.},
	author = {E. K. Lee and J. P. Varkey and D Pompili}
}
@conference {122,
	title = {QUO VADIS: QoS-aware Underwater Optimization Framework for Inter-vehicle Communication using Acoustic Directional Transducers},
	booktitle = {Proc. of IEEE Conference on Sensor, Mesh and Ad Hoc Communications and Networks (SECON)},
	year = {2011},
	month = {June},
	address = {Salt Lake City, UT, USA},
	abstract = {Underwater acoustic communications consume a sig- nificant amount of energy due to the high transmission power (10 - 50 W) and long data packet transmission times (0.1 - 1 s). Mobile Autonomous Underwater Vehicles (AUVs) can conserve energy by waiting for the {\textquoteleft}best{\textquoteright} network topology configuration, e.g., a favorable alignment, before starting to communicate. Due to the frequency-selective underwater acoustic ambient noise and high medium power absorption {\textendash} which increases exponentially with distance {\textendash} a shorter distance between AUVs translates into a lower transmission loss and a higher available bandwidth. By leveraging the predictability of AUV trajectories, a novel solution is proposed that optimizes communications by delaying packet transmissions in order to wait for a favorable network topology (thus trading end-to-end delay for energy and/or throughput). In addition, the solution proposed {\textendash} which is implemented and compared with other solutions using an emulator that inte- grates underwater acoustic WHOI Micro-Modems {\textendash} exploits the frequency-dependent radiation pattern of underwater acoustic transducers to reduce communication energy consumption by adjusting the transducer directivity on-the-fly.},
	author = {B. Chen and D Pompili}
}
@conference {118,
	title = {A Reliable Geocasting Solution for Underwater Acoustic Sensor Networks},
	booktitle = {Proc. of IEEE MILCOM},
	year = {2011},
	month = {November},
	address = {Baltimore, MD, USA},
	abstract = {Reliable data delivery for underwater acoustic sensor
networks is a major concern in applications such as surveillance,
data collection, navigation, and ocean monitoring. Geocasting {\textendash}
which is the transmission of data packet(s) to nodes located in a
certain geographic region {\textendash} is becoming a crucial communication
primitive. In this work, two versions of a distributed, reliable,
and efficient underwater geocasting protocol, which are based
on different degrees of neighbor information, are proposed for
underwater networks whose acoustic modems use random-access
Medium Access Control (MAC) protocols. By jointly considering
the position uncertainty of nodes, MAC, and routing functionalities,
packet transmissions are prioritized and scheduled in order
to maximize link reliability while limiting end-to-end geocasting
delay. Moreover, a mechanism is designed to save the number of
transmissions by selecting only a subset of neighbors for packet
forwarding. Performance of the proposed protocol is evaluated
and compared via simulations against existing geocasting solutions
tailored for terrestrial wireless networks.},
	author = {B. Chen and D Pompili}
}
@article {161,
	title = {Self-organizing Sensing Infrastructure for Autonomic Management of Green Datacenters},
	journal = { IEEE Network},
	volume = {25},
	year = {2011},
	month = {July},
	pages = {34-40},
	abstract = {The scale and complexity of modern datacenters are growing at an alarming rate
due to the rising popularity of the cloud computing paradigm as an effective
means to cater to the ever increasing demand for computing and storage. The
management of modern datacenters is rapidly exceeding human ability, making
autonomic approaches essential. In this article, methods for acquiring thermal
awareness using real-time measurements and heat and air circulation models as
well as solutions for proactive autonomic datacenter management that exploit this
awareness are discussed. Novel communication and coordination schemes that
enable self-organization of a network of external heterogeneous sensors (e.g., thermal
cameras, scalar temperature and humidity sensors, airflow meters) into a multitier
sensing infrastructure capable of real-time datacenter monitoring are also
presented.},
	author = {H. Viswanathan and E. K. Lee and D Pompili}
}
@proceedings {1925,
	title = {SILENCE: Distributed Adaptive Sampling for Sensor-based Autonomic Systems},
	year = {2011},
	month = {June},
	address = {Karlsruhe, Germany},
	author = {E. K. Lee and H. Viswanathan and D Pompili}
}
@article {1927,
	title = {Thermal Anomaly Detection in Datacenters},
	journal = {Journal of Mechanical Engineering Science (SAGE)},
	volume = {1},
	year = {2011},
	month = {December},
	pages = {1-14},
	author = {Yang Yuan and E. K. Lee and Pompili, Dario and Junbi Liao}
}
@proceedings {166,
	title = {Uncertainty-Based Localization Solution for Under-Ice Autonomous Underwater Vehicles},
	year = {2011},
	month = {December },
	address = {Seattle, WA, USA},
	author = {B. Chen and D Pompili}
}
@inbook {1935,
	title = {Advanced MAC Protocols for ZigBee Networks},
	booktitle = {ZigBee Network Protocols and Applications, C. Wang, T. Jiang, and Q. Zhang, Eds.},
	year = {2010},
	publisher = {CRC press},
	organization = {CRC press},
	author = {B. Chen and D Pompili}
}
@inbook {2286,
	title = {Advanced MAC Protocols for ZigBee Networks},
	booktitle = {ZigBee Network Protocols and Applications},
	year = {2010},
	publisher = {C. Wang, T. Jiang, and Q. Zhang, Eds., Auerbach Publications, CRC press},
	organization = {C. Wang, T. Jiang, and Q. Zhang, Eds., Auerbach Publications, CRC press},
	author = {Baozhi Chen and Dario Pompili}
}
@proceedings {2281,
	title = {Demo Abstract: Performance Evaluation of Underwater Vehicle Coordination Algorithms through Emulation},
	year = {2010},
	publisher = {ACM},
	address = {Woods Hole, MA},
	author = {Baozhi Chen and Dario Pompili}
}
@conference {123,
	title = {Patient Vital Signs Monitoring using Wireless Sensor Networks},
	booktitle = {Proc. of IEEE Northeast Bioengineering Conference},
	year = {2010},
	month = {March},
	address = {New York, NY, USA},
	abstract = {Today hospitals are equipped with many electronic trans- mitting devices, which results in electromagnetic interference that may impair wireless transmissions between medical devices. On the other hand, reliable and continuous collection via wireless communications of patient vital signs such as blood pressure and flow, core temperature, ECG, carbon dioxide (CO2) concentration is crucial for making real-time triage decisions. Hence, a novel wireless communication solution that seamlessly supports patient mobility and that prioritizes vital signs transmission using Wireless Body Area Networks (WBANs) is developed, implemented in TinyOS, and tested on Shimmer biomedical wireless sensor motes.},
	author = {B. Chen and J. P. Varkey and D Pompili and J. K. Li and I. Marsic}
}
@conference {171,
	title = {Performance Evaluation of Underwater Vehicle Coordination Algorithms through Emulation},
	booktitle = {ACM International Workshop on UnderWater Networks (WUWNet)},
	year = {2010},
	month = {September},
	address = {Woods Hole, MA, USA},
	author = {B. Chen and D Pompili}
}
@inbook {1936,
	title = {Prioritization of Patient Vital Signs Transmission Using Wireless Body Area Networks},
	booktitle = {E-Healthcare Systems and Wireless Communications: Current and Future Challenges, Mohamed K. Watfa, Ed.},
	year = {2010},
	author = {B. Chen and D Pompili}
}
@inbook {2285,
	title = {Prioritization of Patient Vital Signs Transmission Using Wireless Body Area Networks},
	booktitle = {E-Healthcare Systems and Wireless Communications: Current and Future Challenges},
	year = {2010},
	publisher = {Mohamed K. Watfa, Ed},
	organization = {Mohamed K. Watfa, Ed},
	author = {Baozhi Chen and Dario Pompili}
}
@proceedings {1932,
	title = {Reliable Geocasting for Underwater Acoustic Sensor Networks},
	year = {2010},
	month = {September},
	address = {Woods Hole, MA},
	author = {B. Chen 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 {143,
	title = {A Testbed for Performance Evaluation of Underwater Vehicle Team Formation and Steering Algorithms},
	year = {2010},
	month = {June},
	address = {Boston, MA},
	author = {B. Chen and D Pompili}
}
@proceedings {2278,
	title = {Towards Energy-Efficient Reactive Thermal Management in Instrumented Datacenters},
	year = {2010},
	publisher = {IEEE},
	address = {Brussels, Belgium},
	author = {I. Rodero and E.K Lee and Dario Pompili and Manish Parashar and M. Gamell and R. J. Figueiredo}
}
@conference {124,
	title = {A Trajectory-aware Communication Solution for Underwater Gliders using WHOI Micro-Modems},
	booktitle = {Proc. of IEEE Conference on Sensor, Mesh and Ad Hoc Communications and Networks (SECON)},
	year = {2010},
	month = {June},
	address = {Boston, MA, USA},
	abstract = {The predictable trajectory of underwater gliders can be used in geographic routing protocols. Factors such as drifting and localization errors cause uncertainty when estimating a glider{\textquoteright}s trajectory. Existing geographic routing protocols in underwater networks generally assume the positions of the nodes are accurately determined by neglecting position uncertainty. In this paper, a paradigm-changing geographic routing protocol that relies on a statistical approach to model position uncertainty is proposed. Our routing protocol is combined with practical cross-layer optimization to minimize energy consumption. Our solution{\textquoteright}s performance is tested and compared with existing solutions using a real-time testbed emulation that uses underwater acoustic modems.},
	author = {B. Chen and P. C. Hickey and D Pompili}
}
@article {163,
	title = {Transmission of Patient Vital Signs using Wireless Body Area Networks},
	journal = {Mobile Networks and Applications (Springer)},
	year = {2010},
	month = {July},
	abstract = {Triage is the process of prioritizing patients
based on the severity of their condition when resources
are insufficient. Hospitals today are equipped with
more and more electronic medical devices. This results
in possibly high level of electromagnetic interference
that may lead to the failure of medical monitoring
devices. Moreover, a patient is usually moved between
different hospital settings during triage. Accurate and
quick prioritization of patient vital signs under such
environment is crucial for making efficient and realtime
decisions. In this article, a novel in-network solution
to prioritize the transmission of patient vital
signs using wireless body area networks is proposed;
the solution relies on a distributed priority scheduling
strategy based on the current patient condition and on
the vital sign end-to-end delay/reliability requirement.
The proposed solution was implemented in TinyOS and
its performance was tested in a real scenario.},
	author = {B. Chen and D Pompili}
}
@proceedings {2279,
	title = {Learning-based Framework for Policy-aware Cognitive Radio Emergency Networking},
	year = {2009},
	publisher = {IEEE},
	address = {Atlanta, GA},
	author = {E. K Lee and Hariharasudhan Viswanathan and Dario Pompili}
}
@conference {127,
	title = {Movement Recognition Using Body Area Networks},
	booktitle = {Proc. of IEEE Global Telecommunications Conference (GLOBECOM)},
	year = {2009},
	month = {November},
	address = {Honolulu, HW, USA},
	author = {J. Varkey and D Pompili}
}
@proceedings {1933,
	title = {Continuous Vital Sign Monitoring via Wireless Sensor Network},
	year = {2008},
	month = {November},
	address = {Poly-NYU, NY},
	author = {B. Chen and D Pompili and I. Marsic}
}
@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}
}
@proceedings {169,
	title = {Reliability in Underwater Inter-Vehicle Communications},
	year = {2008},
	month = { September },
	address = {San Francisco, CA, USA},
	abstract = {Underwater networks are envisioned to enable several applications
for oceanographic data collection, environmental monitoring, navigation,
and tactical surveillance. Underwater acoustic networking
is the enabling technology for these applications. Most of these
applications make use of underwater vehicles and rely on intervehicle
communication capabilities for information exchange and
coordination purposes. Reliable data delivery, especially in the
case of mobile underwater vehicles, is therefore a major concern
in many of these applications. In this paper, three versions of a reliable
unicast protocol are proposed, which integrate MAC and routing
functionalities and leverage different levels of neighbor knowledge
for making optimum decisions for reliable data delivery. The
different levels of neighbor knowledge used by the protocols are:
(i) no neighbor knowledge, (ii) one-hop neighbor knowledge, and
(iii) two-hop neighbor knowledge. The three versions of the protocol
have been devised by considering the peculiar characteristics
of underwater channel, in design as well as in performance simulation.
The protocols have been compared in static as well as mobile
scenarios in terms of different end-to-end networking metrics.},
	author = {A. A. Nimbalkar and D Pompili}
}
