SRC/SFI/NSF Forum on Integrated Sensors for Cybersystems - FISC 2030 (by invitation)
- Thursday, March 22, 2012, 8 a.m. — Friday, March 23, 2012, 2 p.m. Local
- Carton House, Maynooth, Co. Kildare, Ireland
- Event ID:
The goal of FISC-2030 is to identify future research directions for highly functional space-limited (e.g. portable) sensor systems that operate with extremely low energy consumption.
FORUM FINAL REPORT: SRC/SFI/NSF Forum on Integrated Sensors for Cybersystems (FISC 2030)
|Thursday, March 22, 2012 (Carton Suite)|
|7:00||Breakfast (The Linden Tree) / Registration (Carton Suites)|
|8:00 - 8:10||Welcome Remarks: Fionn Murtagh & Paul Dodd / Science Foundation Ireland - Ireland|
|8:10 - 8:15||Forum Theme: Ralph Cavin / SRC - USA|
|8:15 - 8:45||Plenary: Martin Curley / Intel - Ireland||The World is Flat. Towards the Next Evolutionary Leap!|
|Session I: Emerging Physics & Technology Opportunities for Integrated Sensor (Chair: Paul Dodd, SFI- Ireland)|
|8:45 - 9:15||Keynote: Michael Roukes / CalTech - USA||Realism in Nanosensing: Hard-won Insights from the Trenches|
|9:15 - 10:15||Paolo Lugli / Techische Universitat Munchen - Germany||Spray Deposition for Sensor Applications|
|Julian Gardner / Univ. of Warwick - UK||Microsensors for Electronic Noses and Tongues|
|Paulo Freitas / INESC-MN - Portugal||Challenges for Integrated Magnetoresistive Sensors|
|Sebastian Bartsch / EPF Lausanne - Switzerland||Resonant-Body Transistors|
|Alan O’Riordan / Tyndall Inst., Cork - Ireland||Fabrication & Characterization of Gold Nanowire Electrodes for Electroanalysis|
|10:15 - 10:45||Open Mic Interactions||All|
|10:45 - 11:00||Break|
|Session II: Biosensors (Chair: Dale Edwards, SRC & GLOBALFOUNDRIES - USA)|
|11:00 - 11:30||Keynote: Dermot Diamond / Dublin City University - Ireland||Materials Chemistry and Stimuli Responsive Polymers - The Key to Future Large-scale Networks of Chemical and Biological Sensors|
|11:30 - 12:30||Robert Dutton / Stanford University - USA||Technology CAD for Modeling and Design of Bio-Devices|
|Michael Goryll / Arizona State University - USA||Silicon Pore Systems for Single Molecule Detection|
|Martin Hegner / Trinity College Dublin - Ireland||Quantitative Nanomechaical Diagnostics|
|Richard Brown / Univ. of Utah - USA||Biosensors for the Brain|
|Arjang Hassibi / UT Austin – USA||Biosensor Systems in Standard CMOS: Fact or Fiction?|
|12:30 - 13:00||Open Mic Interactions||All|
|13:00 - 13:45||Lunch (The Linden Tree)|
|Session III: Integration and Circuit Structures for Integrated Sensor Cybersystems (Chair: David Yeh, SRC & TI - USA)|
|13:45 - 14:15||Keynote: Simon Deleonibus / LETI – France||Prospects for Nanoelectronics CMOS Scaling and Functional Diversification|
|14:15 - 15:15||Ajith Amerasekera / Texas Instruments - USA||Making Sensors Happen|
|Glenn Daves / Freescale - USA||MEMs Research Needs - A Packaging Perspective|
|Eric Vogel / Georgia Tech - USA||Integration, Models, and Circuits for Silicon-based Chemical/Biological Sensors|
|Manos Tentzeris / Georgia Tech - USA/Ireland||Inkjet-Printed Paper/Polymer-Based "Green" RFID and Wireless Sensor Nodes: The Final Step to Bridge Cognitive Intelligence, Nanotechnology and RF?|
|Naveen Verma / Princeton - USA||Circuit Architectures for Inference: Sensing and Analyzing Complex Physiological Signals in Low-power Devices|
|15:15 - 15:45||Open Mic Interactions||All|
|15:45 - 16:00||Break|
|Session IV: Sensors to Support Ubiquitous / Pervasive Autonomic Networks (Chair: William Joyner, SRC - USA)|
|16:00 - 16:30||Keynote: Brett Warneke / Dust Networks - USA||Synchronization, Localization, and Reputation for Networked Sensors|
|16:30 - 17:30||P R Kumar / Texas A&M Univ. - USA||Cyberphysical Systems|
|Joshua Smith / Univ. of Washington - USA||RFID Sensor Networks|
|Gregory O’Hare /Univ. College Dublin - Ireland||Autonomic Sensing Infrastructure|
|Dominic O’Brien / Univ. of Oxford - UK||Optically Powered ‘Smart Dust’ Motes|
|Gu-Yeon Wei / Harvard University - USA||RoboBees: A Convergence of Body, Brain, and Colony|
|17:30 - 18:00||Open Mic Interactions||All|
|19:00 - 20:00||Drinks Reception||Carton Suites|
|20:00||Dinner - Speaker: Fred Schneider / Cornell University - USA, "Security and Information Assurance"|
|Friday, March 23, 2012 (Carton Suite)|
|7:00||Breakfast (The Linden Tree) / Registration (Carton Suites)|
|Session V: Sensors for Physical World Interfaces: Application Landscape for Future Integrated Sensors (Chair: Betsy Weitzman, SRC - USA)|
|8:00 - 8:30||Keynote: Jan Rabaey / UC Berkeley - USA||Swarm Visions|
|8:30 - 9:30||Anuj Batra / Texas Instruments - USA||Application-optimized Wireless Sensor Network Interfaces|
|Pol Mac Aonghusa / IBM Dublin - Ireland||Smarter Cities Perspective|
|Joseph Paradiso / MIT - USA||Connecting to the Emerging Nervous System of Ubiquitous Sensing|
|William Kaiser / UCLA - USA||Future Integrated Sensors in Wireless Health|
|Kevin Fu / U Massachusetts - USA||Security and Privacy for Implantable Medical Devices|
|9:30 - 10:00||Open Mic Interactions||All|
|10:00 - 10:15||Break|
|Session VI: Roundtable Discussion - FISC Perspectives: Research Needs and Potential Responses (Chair: Ralph Cavin, SRC - USA)|
|10:15 - 12:00||Steve Hillenius / SRC - USA|
|Fionn Murtagh / SFI - Ireland|
|John Cozzens / NSF - USA|
|Juan Rey / Mentor Graphics - USA|
|Paul Franzon / North Carolina State Univ. - USA|
|12:00 - 12:30||Open Mic Interactions|
|12:30 - 13:30||Lunch (The Linden Tree)|
Co. Kildare, Ireland
PH: +353 1 5052000
Room Block: Science Foundation Ireland
A beautifully restored historic mansion on a 1,100 acre private parkland estate, Carton House is the first of its kind in Ireland. It is ideally situated just 30 minutes from Dublin's City Centre and within close proximity to the Dublin Airport.
NOTE: You must call the Carton House directly to receive the block rate. Room bookings cannot be made online as the hotel is sold out.
Attire for the event is business casual.
It is recommended that you take a taxi from the airport to Carton House. Carton House has preferred agreement with Maynooth Express Cabs: +353 1 628 9999 (approx. 60 Euros one way)
From Dublin, take the main M4 motorway westbound. From the motorway, take the "Leixlip West" exit (Junction 6) and follow the signs to Carton House Hotel. Carton House Hotel is approximately a five minute drive from the M4 motorway exit.
From the west, take the M4 motorway to Dublin and approximately 20km from Dublin city, take the "Leixlip west" exit (Junction 6) and follow the signs to Carton House.Carton House is approximately a five minute drive from the M4 motoroway exit.
The goal of FISC-2030 is to identify future research directions for highly functional space-limited (e.g. portable) sensor systems that operate with extremely low energy consumption. To help provide focus for the discussions a portable life-enhancement system is envisioned that supports its user in virtually every aspect of his/her life.
The Forum is designed to explore both fundamental physics of sensors and the application landscapes of future integrated sensor systems. Scaling-performance projections will be analyzed as tradeoffs between physical variables needed to achieve maximum performance at minimum energy and limited size. A global energy-space-time metric could provide insights into sensor system design based on fundamental physics. Applications for future integrated sensor systems include energy technologies, environment, smart meters, smart cities, biomedical monitoring etc.
The technological challenges that must be addressed to develop new generations of sensor systems are daunting and encompass almost every facet of integrated system technology including information processing, energetics, communication and packaging. In this forum, we expect to examine these essential technologies from the point of view of what may be ultimately achievable, given our present comprehension of the projected future capabilities of science and integrated circuit technology.
This is an invitation-only forum and all attendees are expected to participate. The forum will be constructed to include selected overview presentations and panel discussions on the ultimate performance of the various functional elements required to realize new generations of sensor systems. It will encourage and enable interactions by allotting sufficient time for in-depth panel-participant interactions after each session. Participation by university researchers and technologists from major information technology providers will be enlisted and discussions will be directed toward comprehending the most feasible approaches to enabling future integrated sensor applications.
The agenda is designed to foster interaction between panel specialists and forum attendees on novel integrated sensors and their applications. A technical report will be generated resulting from the inputs gathered at the forum that will be useful in describing promising research directions for future integrated sensor systems.
Session 1: Emerging Physics and Technology Opportunities for Integrated Sensors
A sensor is a device, which converts an external physical stimulus into a distinguishable, information-bearing and processable signal, usually in electrical form. Sensors are sometimes defined as an entire system, comprised e.g. of a (i) transducer, which generates an electrical signal in response to an external stimulus, (ii) electronic amplifier, which increases the intensity of the signal, (iii) signal processor, (iv) display, etc. In this session, a narrower definition of a sensor is used: a device directly responding to external stimuli, i.e. a transducer. Examples of external physical stimuli are mechanical (e.g. pressure, motion, vibration), electrical (e.g. voltage), thermal (e.g. temperature difference), electromagnetic (e. g. light), chemical (e.g. presence/absence of particular chemical species), etc. In response to the external stimulus, the sensor generates an electrical signal, which is further processed by a control unit and eventually provides a basis for further actions by the system. In its simplest form, a sensor generates a binary YES/NO response by distinguishing between the presence and absence of a particular external stimulus. In other words, a sensor must have at least two distinguishable states. As can be argued, creation of the distinguishable states requires energy barriers within the sensing device. Indeed, in many cases, a sensor can be regarded as a switch, whose barrier is deformed by different stimuli, e.g. pressure, light, temperature, presence of ions in a solution, etc. Note that the FET is indeed an electrical sensor, whose stimulus is the presence/absence of an electrical charge on the gate electrode. Due to the intrinsic similarity between a sensor and the FET, the fundamental scaling limits of sensors are, in principle, the same for the FET. However, there are additional constraints for sensors arising from requirements of sensitivity, selectivity, and response time. Also, while sensors can be used in a digital (i.e. binary) mode, in most cases they are used as analog devices.
Session II: Biosensors
This session, by its nature, is an integration of concepts from both biological and physical sciences. The primary function of sensors for bio-applications is to receive and transform biological signals into an electrical form for subsequent processing and analysis to provide a basis for further actions. The state of a living system can be monitored by sensing different physical parameters e.g. chemical, electrical, optical, thermal, magnetic etc. It appears that the 1D nanostructures, such as semiconductor nanowires and carbon nanotubes, might be essential for biosensing, as they have better sensitivity than planar devices and allow for the picomolar detection of biomolecules. In addition, 1D nanostructures with very small diameters, such as carbon nanotubes, could be used as (quasi)non-invasive probes to contact or even puncture the cell’s membrane or be ‘ingested’ by a cell. This suggests an intriguing possibility of electrically monitoring processes inside the cell.
Session III: Integration and Circuit Structures for Integrated Sensor cybersystems
This session will address essential circuit components of sensing systems, including (i) pre-sensing steps: extraction, separation, amplification, and (ii) post-sensing steps: read-out, signal conditioning, and data processing and transmission. Across different application spaces, the challenges of the system design may be more difficult in different steps due to specific constraints, including areas of packaging, expected lifetime, power/energy, calibration and reliability. This session looks at several application spaces and investigates the challenges associated with integrating essential circuit components to realize a wide set of integrated sensor systems.
Session IV: Sensors to Support Ubiquitous / Pervasive Autonomic Networks
An autonomic system has many of the characteristics of the autonomic nervous system that controls breathing, heart rate, etc., e.g. it must be user-transparent, self-healing, self-configuring, self-optimizing, and self-protecting. Autonomic systems are data-driven rather than compute-focused and therefore sensors and sensor networks play a vital role in their implementation. This session examines the requisite sensor properties needed to support the widespread application of autonomic systems for society and the potential contributions of sensor networks as building blocks for the concept of "the internet of things".
Session V: Sensors for Physical World Interfaces: Application Landscape for Future Integrated Sensors
Sensors are to be potentially everywhere - from small to large - from inside chips or human body to outer space; and they will be in very large numbers. This latter aspect represents a third dimension of FISC, which is managing a large number of sensors talking to one another; sleeping and waking on demand etc., all that makes the technology functional and after all useful. Thus algorithms are essential components and for maximum hardware productivity sensor technology should keep in contact with algorithmic developments. Example applications include: energy, environment, smart meters, smart cities, security, biomedical monitoring etc.
Session VI: FISC Perspectives: Research Needs and Potential Responses
Session I: Emerging Physics & Technology Opportunities for Integrated Sensor (Paul Dodd, Session Chair)
Sensors are transducers converting a physical stimulus into a distinguishable signal, and can be based on different physical principles, such as optical, acoustic, electrical, or mechanical effects. Example of optical transducers are plasmonic nanostructures that allow for ultrasensitive surface enhanced Raman spectroscopy. Electrical transducers are represented by a family of semiconductor charge-sensitive structures, including FET-type devices and various nanowire based structures. Also, mechanical transducers in the form of nanoelectromechanical structures (NEMS) offer an amazingly broad range of sensing capabilities. Interesting sensing functions can be achieved from quantum phenomena – such as for example magnetic sensors using quantum junctions. Are there other physical principles or structures that can be exploited for improved sensor performance or for a broader application space?
A sensor utilizing several physical principles may be advantageous in many cases. For example highly localized nanoheaters/hot spot engineering can dramatically increase the response and recovery time as well as the selectivity of chemical sensors. As another example NEMS and FET structures integrated in a single device could allow for more scalable sensors.
What trade-offs are required for sensors performance as feature sizes are scaled? For example, a global energy-space-time metric could provide insights into sensor system design based on fundamental physics.
Is it possible to conceive of a Universal Sensor, based on a generic structure, that can be customized for different stimuli and different applications? For example, NEMS, in principle allows for sensing force/acceleration, chemicals, magnetic field, light etc. To what extent can a general NEMS sensor be designed that can be adapted to different modalities, integrated on CMOS and support mass applications? If sensor systems could benefit from scaling and integration, their impact might be as transformative as that of the transistors and integrated circuits.
As a single stand-alone sensor is unlikely to be cover all range of applications, arrays of sensors can often give enhanced performance over individual devices. However, achieving the full benefits of array organization may require exceptionally careful attention to device variances. Also, careful choices of platform materials are essential to insure a rapid transition into large-scale integration and mass production.
Although these sobering considerations may potentially force initial downselection from amongst the exciting possibilities in the emerging panoply of nanosensors; learning from the past, and considering real-world (not academic laboratory) conditions, should accelerate realization of practical nanosensor systems.
A wide range of promising applications for electronic sensing have emerged, for example: chemical hazard detection, food storage/processing control and safety, seismic geo-imaging, agriculture, defense and security, etc.
- What are ultimate performance projections for different sensor devices?
- e.g. Selectivity, sensitivity, response time
- Can an expanded application space for new sensor devices be defined?
- What are needs which are not adequately addressed by known sensor technologies?
- What is the potential and the barriers for scaling of different sensor devices?
- Is the space-time-energy metric appropriate for sensor trade-offs?
- Is there the possibility of a general sensor structure that can be readily adapted to different modalities? Or a small set of generic sensor structures?
- What are other physical phenomena that can be explored as a basis for sensing elements beyond the current FET/nanowires, NEMS, SAWs, MTJs, etc.?
- "Zero energy" sensing?
Session II: Biosensors (Dale Edwards, Session Chair)
The purpose of many biosensors is to monitor biological processes by detecting the reagents or products of biochemical reactions. Examples are DNA fragments, proteins, pH, and poisonous/hazardous substances. Direct detection of present viruses and single-cellular organizations such as bacteria is also an important task.
A typical approach to detecting biomolecules is affinity-based detection/receptor-based sensing. The affinity-based sensors have an active surface functionalized with biomolecule receptors, pre-designed to bind with specific target species. In practical applications the affinity-based sensors must be regularly cleaned and calibrated, and this makes them more difficult to use in autonomous integrated sensor nodes. In principle, alternative “receptor-less” concepts could allow for more effective and diverse applications. Immobilization of target molecules is also essential for this class of biosensors.
Many of the biosensors currently implemented in lab-on-chip systems require additional external instrumentation: valves, injectors, positioners, alignment systems, fluidic manifolds, separate detectors and microscopes, etc. To what extent is it possible to miniaturize and integrate the external instrumentation onto a single chip with the sensing devices?
Three kinds of platforms are currently receiving considerable attention for biosensing: carbon nanotubes, nanowires and NEMs devices. A detailed comparative study of these approaches including fundamental limits (e.g. for scalability), integration issues and identification of application domains would be helpful. One application for biosensors is in the area of human health monitoring. Other important emerging applications include food quality control, environmental monitoring, and safety.
- Breakthrough technologies for biosensors?
- Are there promising concepts beyond nanowires, CNT, and NEMs?
- Can nanopores, nanowires and CNT be combined for sensing applications?
- What is the whole set of possible signals detected by biosensors?
- What are the opportunities of receptor-based vs. receptor-less biosensors?
- What are the limits of miniaturization of biosensors and the ability to integrate them in cips
- What ranges of biosensor applications are suitable for monolithic integration on a silicon chip?
- How is biosesor sensitivity and selectivity impacted by feature size scaling?
- What are the energy and power limits for biosensor operation?
- What biosensor applications can be envisioned that will be attractive as high-demand ICs?
- What are the shorter-term prospective targets for biosensors?
- What is the size of the application space for known biosensor applications?
- Is there a sensing principle that could be exploited in a variety of other application fields (e.g. universal sensor)?
Session III: Integration and Circuit Structures for Integrated Sensor Cybersystems (David Yeh, Session Chair)
An integrated sensor chip can be comprised of a digital unit, an analogue unit, an RF unit or/and an optical unit, in addition to the sensing unit. The integration of these units on a chip represents significant design and technology challenges, such as how to develop scalable plug and play design approaches.
It is desired for integrated sensor chips to be small which imposes new restrictions for their stand-alone operation. In principle, the sensor chip could be small but the energy it stores will decrease proportionally with the volume which would limit its resources for processing and communication. Unfortunately alternative chip power sources other than batteries that are based on energy scavenging methods typically offer no more than hundreds of microwatts.
In many applications, the energy, communication-bandwidth, and real-time constraints faced by sensing systems raise the need for on-node analytics. To enable platform technologies, it is preferable to be able to scale the local analytics in response to the constraints in a given application. This requires architectures that provide outputs ranging from raw data to high-value inferences. Scalable approaches for embedded computation could thus play a valuable role. Once embedded, these could potentially be exploited towards assistive functions within the platform itself.
The integration of all the units in one sensor chip also implies incorporating heterogeneous structures (incorporation of NEMs and NWs, bio receptors etc.), new materials (polymers, conductive inks, etc.) and CMOS processes that would require process compatibility evaluation. Technologies that address compatibility issues, allowing flexibility of a possible modular processing flow, would increase the spectrum of sensor chips applications. An example of ongoing research on technologies is fabrication using inkjet patterning on paper substrates.
The research on sensor chip packaging is strongly dependent on the application. As the spectrum for sensing applications expands and the possibilities of multiple parameters sensing emerge, new packaging alternatives to integrate micro fluidic and NEMs devices should be explored.
- Are standard libraries for integrated sensors feasible?
- Vertical integration challenges? Materials to system design (including MEMS, board, packaging, and enclosure)
- Challenges of standardized methodologies, e.g. MEMS
- In a multi-modal, integrated sensor system, to what extent is shared interface circuitry feasible?
- How do we approach the challenges of analyzing and modeling increasingly complex signals from increasingly diverse sources of interest?
- Are there frameworks for platform design that can serve a multitude of application domains?
- Node architectures for energy minimization?
- What are the major obstacles for the realization of the first “Internet of Things” applications”?
- To what extent can microfluidics be integrated in present packaging technologies? What other environmental challenges are there besides fluids? e.g. air, vacuum?
- What roles can 3-D packaging play in realizing sensor application solutions?
- What are the roles of different packaging technologies such as SOC, SOP, SIP, etc. for integrated sensor chips?
- Are there any environmentally friendly solutions for large number of disposable sensors?
- Data processing and communication?
- In biomedical detection how can algorithms support real time inference from multisensory inputs, e.g. to detect correlations of interest?
- Trade-offs between inference time and accuracy on one hand and data density and energy utilization on the other?
- How could multi-hopping algorithms enhance the sensing range in an energy-efficient way?
- How is the optimal data processing location determined?
- What is the potential for alternative technologies to CMOS processes? e.g.
- Polymer electronics
- Inkjet printing, etc.
- What are the tradeoffs for the realization of sensors on low-cost materials (paper, plastic...)?
- Wireless power transfer vs. Power Scavenging: Pros and Cons?
- Integration of alternative technologies with CMOS?
- Multiscale challenges?
Session IV: Sens0rs to Support Ubiquitous / Pervasive Autonomic Networks (William Joyner, Session Chair)
The continuous proliferation of IC devices including sensors and actuators, has enabled their integration into communicating nodes and their organization into networks for monitoring and tracking different physical parameters. The desired capabilities of a sensor node include sensing, processing communication, and sometimes self-powering. The networks are expected to be energy efficient, scalable and resilient.
Networked sensor nodes permit the monitoring and tracking of detectable signals at the interface between the physical world and the world of electronic devices. Sensor networks have greatly benefited from the addition of communication, processing and node scalability, allowing applications to be friendlier, smarter, and more adaptable to the change in their target environment. Although the promising target of millions of nodes connected has not yet been achieved, current systems can accommodate thousands of nodes. On-going progress in home monitoring such as home energy usage and water metering will support scaling up these efforts.
In order to fully realize the benefits of sensor networks for multiple applications, a number of challenges have to be overcome: managing node power and communication capabilities, node architectures, multiple sensing modalities and scalability. Aiming at universal connectivity, “the internet of things” can be envisioned and perhaps the large network communication protocols should be inspired by the collective behaviors as observed in ant and bee colonies depending on their mobility capacities.
Currently sensor nodes are not yet at the mass production level of the massive semiconductor industry but the strategies to understand the fundamental limits for the network metrics could provide the insight to assess their potential.
- Intelligent Power Management for Wireless Sensor Networks (O'Hare)
- How does one design an effective operation strategy for WSN?
- Since communication is regarded as a costly task for WSN, how should nodes balance processing and transmission?
- Information-theoretical Limits Considerations of Sensor Networks (Kumar)
- How much information can be carried out over a wireless network with multiplicity of nodes and what are the constrictions on the nodes to achieve maximum communication rates?
- How does node density affect information transfer rates?
- How should the nodes in a WSN cooperate to transfer information and what is the optimum cooperation paradigm for WSN nodes?
- What are the factors governing node cooperation decisions to support communication?
- RFID Sensor Net (Smith)
- What are the opportunities for battery-free and battery powered sensor nodes and WSN?
- What constraints do battery-free and/or battery power introduce to network design?
- What are the major constraints on transmitting power wirelessly to the nodes?
- To what extent can the network be used to power the sensor nodes?
- Optically Powered "Smart Dust" Modes (O'Brien)
- What limits the scaling of optical wireless sensor networks?
- What would be the benefits and constraints to have multimode optical communication for WSN?
- RoboBees: A Convergence of Body, Brain, and Colony (Wei)
- What are the most energy and data transfer efficient interconnectivity for communication in colonies?
- What the the potential applications and challenges for micro robots?
Session V: Sensors for Physical World Interfaces: Application Landscape for Future Integrated Sensors (Betsy Weitzman, Session Chair)
Large-scale intelligent sensor networks are currently envisioned as applied in, for example, “smart cities”, “smart homes”, “smart hospitals”, “the internet of things”, etc. Designers and users must be aware of the vulnerabilities of the application as a whole, and the threats that could compromise its components. Practical materialization of such concepts requires a through system analysis of network behavior. Essential aspects for such analysis are: connectivity, synchronization, coverage, scalability, security and computation (processing the sensed data to obtain a decision to act on).
Although large networks are attractive for their use in multiple applications to achieve intelligence or connectivity between available objects, metrics for evaluating their performance have not yet been developed. Approaches borrow from small networks based on data throughput as a performance criterion and seek to maximize the amount of data processed in a given unit time and to minimize the time it takes to complete a given task. With larger networks, throughput can be high but at a cost of higher network latency. Other potential factors for these metrics could explore energy-efficient algorithms, data-efficient management, sensor location, the network operation (centralized or decentralized) and network power resources.
To date, sensor networks have been successfully implemented for monitoring and tracking objects in the environment, in manufacturing plants and for health monitoring purposes. Managing a large number of heterogeneous sensors imposes challenges on establishing the level of interaction and interconnectivity between all devices involved through definition of the possible communication protocols. Many examples of sensor nodes exchanging information within existing infrastructure exist, e. g, smartphones.
Fundamental studies on the behavior of sensor networks with a very large number of nodes (VLNN) could provide an insight on the benefits of these networks. Models must include the stochastic nature of the node detection process, the optimum data packet size, and the dynamism of environmental conditions. Preserving energy resources and optimizing energy consumption are key challenges for self-powered wireless sensor networks. Energy resources are affected by consumed power per node and network mode operation. For autonomous nodes, standby mode energy demands could be higher than for the active modes, as the node does not continuously sense and communicate. In the context of wearable node applications, a critical design parameter is the power dissipation of a large number of nodes. Node power that is not converted to a useful signal would be dissipated as heat, which could be a limiting factor in a particular application, and must be comprehended as a factor in the system design.
Security and privacy controls are a priority issue. Analysis of the trade-offs between the security, privacy, safety, and utility goals will limit the applicability and usability of sensor networks in security-sensitive scenarios. Sensor networks must also be designed to be resilient. Encryption for sensor node communications and access control schemes need to be evaluated based on network resources availability. Other solutions for data protection could include multipath routing, although network resources might be compromised.
- What applications require a large scale network implementation?
- What are the critical specification parameters for these applications?
- Where should the processing and storage be assigned? To the node sensors, the network of sensors; ‘outsourced’ to the cloud, etc.
- What metrics best describe the performance of a large sensor network?
- Wearable Sesor for Patient Monitoring (Kaiser)
- Since wearable applications involve interaction between the nodes and the user, what system design rules can be involved to minimize interference between sensor nodes?
- Smarter Cities from Sensor Networks (Mac Aonghusa)
- Are there applications where it makes sense to expand the sensor network capabilities of sensing and communicating to include control of the environment? If so, what are the most suitable actuators that could be adapted for multiple control tasks?
- What are the critical design factors/parameters for a sensor network?
- What are the different criteria to determine the network operation protocol?
- How does the network data load vary in the case of the “smart city” applications?
- Body Area Sensor Platform (Paradiso)
- What are the constraints on sensor locations for the on-body network operation?
- Application-optimized Wireless Sesor network Interfaces (Batra)
- How does etwork scale affect design choices?
- Security and Privacy for Implantable Medical Devices (Fu)
- What are the differences/similarities between security and privacy managemet in networks vs computers?
- How can you quantify the cost/benefit tradeoffs to achieve privacy and security in sensor networks?
There are a number of activities in and around the Carton House as well as places of interest in the surrounding areas and in Dublin City.
|Amerasekera, E. Ajith||Texas Instruments Incorporated|
|Avila, Alba||Universidad de los Andes|
|Bartsch, Sebastian T.||EPFL - EPF Lausanne|
|Basu, Sankar||National Science Foundation|
|Batra, Anuj||Texas Instruments Incorporated|
|Blake, John||ON Semiconductor|
|Boubekeur, Menouer||United Technologies Corporation|
|Brown, Richard B.||University of Utah|
|Byrne, Lorraine M||HP Inc.|
|Cavanagh, Leon M.||Silicon Laboratories|
|Cavin, Ralph K.||Semiconductor Research Corporation|
|Cheshire, Roisin||Science Foundation Ireland|
|Cozzens, John||National Science Foundation|
|Cunningham, Patrick||Office of the Chief Scientific Adviser|
|Curley, Martin||Intel Corporation|
|Daves, Glenn||Freescale Semiconductor, Inc.|
|Diamond, Dermot||Dublin City University|
|Dodd, Paul||Science Foundation Ireland|
|Duesberg, Georg S.||University of Dublin, Trinity College|
|Dutton, Robert W.||Stanford University|
|Edwards, W. Dale||Semiconductor Research Corporation|
|Faiers, Leslie||Semiconductor Research Corporation|
|Franzon, Paul D.||North Carolina State University|
|Freeman, Ruth||Science Foundation Ireland|
|Freitas, Paulo||INESC MN|
|Fu, Kevin||University of Massachusetts at Amherst|
|Gardner, Julian||University of Warwick|
|Goryll, Michael||Arizona State University|
|Hassibi, Arjang||University of Texas at Austin|
|Hegarty, John||University of Dublin, Trinity College|
|Hegner, Martin U.||University of Dublin, Trinity College|
|Hillenius, Steven||Semiconductor Research Corporation|
|Hobbs, Leonard P.||Intel Corporation|
|Howlin, Pat||IDA Ireland|
|Hurley, Paul||Tyndall National Institute|
|Jordan, Rory||Science Foundation Ireland|
|Joyner, William H.||Semiconductor Research Corporation|
|Kaiser, William||University of California, Los Angeles|
|Koester, Steven||University of Minnesota|
|Kumar, Panganamala R||Texas A&M University - College Station|
|Lewis, Elfed||University of Limerick|
|List, R. Scott||Intel Corporation|
|Lowry, John P.||National University of Ireland, Maynooth|
|Lugli, Paolo||Technische UniversitÃ¤t MÃ¼nchen|
|Mac Aonghusa, Pol||IBM Corporation|
|Matheus, Christopher J.||Alcatel-Lucent|
|McEvoy, Aisling||Science Foundation Ireland|
|Merzbacher, Celia I.||Semiconductor Research Corporation|
|Mitchell, Neil||The Queen's University Belfast|
|Morris, Michael||University College Cork|
|Morrison, Alan P.||University College Cork|
|Murphy, Niamh||Science Foundation Ireland|
|Murtagh, Fionn||Science Foundation Ireland|
|Naik, Rajesh||U.S. Air Force Research Laboratory|
|O'Brien, Dominic C.||University of Oxford|
|O'Hare, Gregory M.||University College Dublin|
|O'Mathuna, Sean Cian||Tyndall National Institute|
|O'Neill, Ray||National University of Ireland, Maynooth|
|O'Riordan, Alan J.||University College Cork|
|Paradiso, Joseph||Massachusetts Institute of Technology|
|Quinn, Aidan J.||Tyndall National Institute|
|Rabaey, Jan||University of California, Berkeley|
|Rey, Juan C.||Siemens EDA|
|Roche, Jason A.||IDA Ireland|
|Roukes, Michael||California Institute of Technology|
|Schneider, Fred B||Cornell University|
|Sheridan, Charlie G.||Intel Corporation|
|Smith, Joshua R.||University of Washington|
|Speer, Ray||Silicon Laboratories|
|Tentzeris, Emmanouil||Georgia Institute of Technology|
|Varshney, Usha||National Science Foundation|
|Verma, Naveen||Princeton University|
|Vogel, Eric M.||Georgia Institute of Technology|
|Warneke, Brett A.||Linear Technology Corporation|
|Wei, Gu-Yeon||Harvard University|
|Weitzman, Elizabeth||Semiconductor Research Corporation|
|Yeh, David C.||Semiconductor Research Corporation|
|Yeom, Geun-Young||Sungkyunkwan University|
|Zhirnov, Victor V.||Semiconductor Research Corporation|