Proposal Outline and approximate page budget (total = 15 pages)
Introduction (1 page)
Applications
Energy (2 pages)
Disaster (2 pages)
SIS design
Sensor-net level design (1 page)
Service level design (1 page)
Data Handling (1 page)
Human-Centered-Computing (UCB) (.5 page)
Visualization (UCD) (.5 page)
Foundations:
Reliability (2-3 pages)
Availability (2-3 pages)
Security and Policy (1 page)
Outreach (.25 pages)1. Introduction (Target: 1 page)
Information technology (IT) is transforming all aspects of society at an accelerating pace, from business systems and social and political infrastructure to many aspects of our personal lives. But the current path for developing IT will, at best, severely underutilize its potential and, at worst, yield a fragile IT infrastructure which is not of high enough confidence to meet many of society’s most vital needs, such as emergency preparedness and response and energy usage monitoring and controll.
We propose to establish the Center for Information Technology Research in the Interest of Society (CITRIS) to sponsor collaborative, IT-focused research to find solutions to grand-challenge social and commercial problems affecting the quality of life of individuals and organizations. CITRIS will be a multicampus center, including UC Berkeley (UCB), UC Davis (UCD) and UC Merced (UCM). a new campus being constructed in the Central Valley of California with the specific purpose of giving the minority and economically challenged populations access to a University of California education. This proposal is to support the key underpinning long term, high risk scientific and technological research endeavors within CITRIS. The NSF-ITR award will have the potential of high leverage from other CITRIS activities paid for by other means, such as the State of California and industry (See Appendix A.)
CITRIS is mainly aimed at IT development to save lives, property, and establish emergency response IT infrastructure in the wake of disasters (such as earthquakes and floods or biochemical contamination) and boost energy efficiency. The solutions to these driving applications have the common feature that at their core they depend on highly-distributed, reliable, and secure (briefly: high-confidence) information systems that can evolve and adapt to radical changes in their environment, delivering networked information services and up-to-date sensor network data stores over ad-hoc, flexible and fault tolerant networks that adapt to the people and organizations that need them.
We believe that the solution of these problems at their core depends on highly-distributed, reliable, and secure information systems that can evolve and adapt to radical changes in their environment, delivering information services that adapt to the people and organizations that need them. We call such high-confidence systems Societal-scale Information Systems (SISs). The web, telephone network, and some military and intelligence systems are limited, albeit highly successful, SISs. Yet none satisfies the needs of the societal problems. An SIS must easily and naturally integrate devices, ranging from distributed ad-hoc sensors and actuators, to hand-held information appliances (such as those evolving from today’s PDAs), workstations, and room-sized cluster supercomputers at Network Operations Centers (NOCs). Such devices must be connected by ad-hoc sensor nets, extranets, short-range wireless networks as well as by very high-bandwidth, long-haul optical backbones. Distributed data and services must be secure, reliable, and high-performance, even if part of the system is down, disconnected, under repair, or under (information) attack. The SIS must configure, install, diagnose, maintain, and improve its quality of service features — this applies especially to the vast numbers of sensors that will be cheap, widely dispersed, and even disposable. Finally, the SIS must allow vast quantities of data to be easily and reliably accessed, manipulated, interactively explored, disseminated, and used in a customized fashion by users, from expert to novice.
No current system satisfies these needs. In CITRIS we will solve a variety of underlying engineering and science problems and then demonstrate systems that do. We will target two driving applications: an Energy Monitoring and Regulation SIS and a Disaster Risk Reduction and Emergency Response SIS (for emergency and disaster response such as to earthquakes).
We believe that the solution of these problems at their core depends on highly-distributed, reliable, and secure information systems that can evolve and adapt to radical changes in their environment, delivering information services that adapt to the people and organizations that need them. We call such systems Societal-scale Information Systems (SISs). The web, telephone network, and some military and intelligence systems are limited, albeit highly successful, SISs. Yet none satisfies the needs of the societal problems. A SIS must easily and naturally integrate devices, ranging from tiny sensors and actuators to hand-held information appliances, workstations, and room-sized cluster supercomputers. Such devices must be connected by short-range wireless networks as well as by very high-bandwidth, long-haul optical backbones. Data and services must be secure, reliable, and high-performance, even if part of the system is down, disconnected, under repair, or under attack. The SIS must configure, install, diagnose, maintain, and improve itself — this applies especially to the vast numbers of sensors that will be cheap, widely dispersed, and even disposable. Finally, the SIS must allow vast quantities of data to be easily and reliably accessed, manipulated, disseminated, and used in a customized fashion by users.
CITRIS will have 3 tiers of activity: Driving Applications (Energy Management and Disaster Response), SIS Design (Sensor level, Service level, Data Handling, Human-computer Interaction), and Foundations (Reliability, Availability, Security, Policy). We discuss each in turn. For the two driving applications, we will use and leverage ubiquitous wireless sensor devices, called SmartMotes which are about one inch cube in size and include an embedded (StrongArm) processor, a radio, a sensor board with microsensors for measuring acceleration, strain, temperature, light, relative humidity and a battery. We have had around 500 (and expect to have at least 1000 more) of these made for us by Crossbow, Inc.(not priced on this grant, see Section 2.3). Each of these with a 1 % duty cycle and 2 AA batteries will last about a year. The next generation of these devices called SmartDust will have this functionality integrated into a single chip with on board solar power, (2mm cube) with ultra-high–bandwidth radio (the size of the sensor will be dominated by the antenna size), and will provide the distributed, adaptive self-organizing ubiquitous sensing and computational fabric.
[Some words about Smart Dust: its properties, likely future development, that we will assume it is available by leveraging related CITRIS activities: Motes incorporate communications, processing, sensors, sensor fusion, and power source into a package about a cubic inch in size - essentially a self-organizing and adaptive information utility. Motes monitor physically measurable quantities, such as acceleration, strain, microseismics, temperature, relative humidity, and barometric pressure, throughout buildings, bridges, industrial plants, and other critical structures.]
2. Driving Applications
2.1 Energy Management (Target: 2 pages) (Faculty: Rabaey, Pister, Arens, Sastry)
[Point out that this is a summary of a conclusions of a CITRIS working group, citing their white paper.]
A recent CITRIS working group of the core faculty above along with key researchers in energy and resources groups at Lawrence Berkeley Laboratories have established in a whitepaper [Rabaey01] thatWe establish that SISs can go a long way in addressing and resolving issues that hamper the effective generation, distribution and utilization of energy. The quantifiable benefits of these systems to the public and the economy turn out to be enormous. While no SIS exists today that meets all of the requirements formulated above, a time-line is established detailing how a roll-out of energy-conscious information technology systems can have an impact in the short, medium and long-term.
Two-thirds of the primary energy use is in the form of electricity and about two-thirds of all electricity generated nationally is used in buildings (Interlaboratory Working Group, 2000]. This is the sector that we will target for SISs Advances in IT, applied to energy use in buildings, hold the promise of making the system considerably more efficient. Societal-scale information systems consisting of wireless sensors/actuators enable the energy conscious (including reducing both total energy as well as peak power demanded) control of buildings with information from a much higher density network of sensors: than is currently economical.
· High-density sensor networks will allow existing environmental control technologies to operate in more sophisticated and energy-efficient ways, and the redundancy of sensors in such networks will improve the reliability of control by detecting faulty signals.
· High-density sensor networks will also allow new energy-efficient environmental control technologies to become feasible for the first time.
The term 'energy efficiency' above includes both the total energy required for a given building service over time, and to the peak power demanded at any instant within that time.
Imagine, for example, the following scenario. All significant energy-consuming devices in buildings are equipped with a multifunctional metering, communications, and control devices. These devices provide real-time information to building owners and occupants on rate of energy use (e.g., kW), cost associated with energy use rate ($ per hour), cumulative energy usage and associated costs for past 24 h, month, and year. By itself, this information would greatly enhance the ability of energy users in buildings to make rational decisions such as when to take inefficient devices out of service that should improve efficiency and reduce total usage. Such decisions could include how much and when to use certain devices. The information would also be useful in deciding when to replace an inefficient device, such as an old refrigerator, with a new, more efficient model. Currently, such decisions must be made blindly with regard to operation cost.
The devices could also incorporate important energy management controls. In addition to reducing total energy use, it is of central importance in electricity system management to limit peak demand. One mechanism for doing this is through mechanisms like real-time pricing. Real-time pricing will require more sophisticated electricity meters than are currently in common use. However, for optimal performance, devices that are moderate to heavy electricity users should also be equipped with controls that would permit rational response to real-time price signals. So, for example, a smart refrigerator could know that it should avoid firing the compressor when electricity costs are high. With the right combination of distributed ubiquitous sensing and processing software and hardware, it smart appliances could use its electricity mostly at off-peak periods.
Thus, In summary, by making the end-users of the energy-supply chain part of an integrated network of monitoring, information processing, controlling, and actuating devices, we enable a wide range of techniques that will both help to spread the consumption of energy over time reducing peak demand, as well as help to reduce the average demand of energy through efficiency increase. While the process of designing, constructing, starting up, controlling, and maintaining building systems is very complex, and changing the building and appliance industry overnight is not possible, we believe that a gradual roll-out plan can show impact in the very near future.[We will demonstrate this on campus buildings during the current project.on campus in the very near term as follows (Pister) …] We envision a triple-tiered research program for the introduction of societal-scale information systems into the demand side of the electrical energy equation.
Phase 1: Passive monitoring
The availability of cheap, connected (wired or wireless) sensors makes it possible for the end-user to monitor energy-usage of buildings as well as the health ofnd individual appliances and act there-on. It has been estimated that the cost of the operation of “broken systems” in energy usage of commercial buildings is a whopping 30 % of their operational budget ($ 45B annually in the US) This information feedback plays the a dual role:
· primary feedback to the user on energy-consumption statistics
· monitoring the health of the equipment and the environment – detect problems at the source. It has been estimated that the operation of “broken systems” may cost at least 30% of the commercial building energy use (more than $45 billion).[Is $45B the total energy use or 30% of it?]
Phase 2: Devloping Mechansims forQuasi-Active Monitoring and Control
By combining the monitoring information with instantaneous feedback on the cost of usage (augmented by an hourly pricing system that reflects wholesale market prices) helps to close the feedback loop between end-user and supplier. Key challenges here are to develop a pricing scheme which does not in itself cause instabilities in the bidding and consumption process by hierarchical verification,
Phase 3: Active Energy-Management through Feedback and Control¾Smart Buildings and Intelligent Appliances
The addition of instantaneous and distributed control functionality to the sensory and monitoring functions (measuring the operation of systems such as climate conditioning and lighting) increases the energy-efficiency of these functions dramatically, while at the same time improving the comfort of the users. [Is the difference between Phases 2 and 3 that in Phase 2 control decisions are “by hand” whereas in Phase 3 they are automatic?]
· 2.2 Disaster Risk Reduction and Emergency Response (Target: 2 pages) (Faculty: Fenves, Glaser, Kanafani, Demmel)
[Cite NRC report “Reducing Disaster Losses Through Better Information” for underlying motivation, though we will go way beyond what they have via sensor nets; cite TRINET.]
Each year large natural disasters cost the U.S. hundreds of lives, many critical structures, and billions of dollars in disruption to the economy. In particular, earthquakes present a substantial risk to the residents and economies of the large urban regions in the Western U.S., with probabilities exceeding 60% that a major earthquake will strike northern or southern California in the next 30-years. Estimates of casualties number in the thousands, direct damage losses are on the order of $100 to $200 billion and indirect losses due to disruptions in the economic base could be several times greater. Seismic hazard is not confined to California; with equally significant risks to the central and eastern U.S. from the New Madrid , Boston, and Charleston earthquake zones.
We contend that radically new information technologies can be used to protect lives and speed the economic recovery of a city after a large earthquake. The same set of IT scales across a wide range of societal problems. It will become apparent that tThese same technologies will be equally effective in response to tornadoes, hurricanes, fires, and floods. Here we describe SIS In this section, the IT applications are described for three applications: (1) structural health prognosis of individual buildings and other structures, (2) real-time evaluation of inventories of buildings and lifeline networks, and (3) adaptive coordination of emergency response and recovery. We will develop a set of tools which allow integration of sensing, information acquisition, evaluation, and modeling that will be basically independent of the detailed algorithm used to prognosticate and evaluate. The test case will be (1) structural health prognosis of a structure, which will involve a particular evaluation module (detailed models of structural behavior). The new science will be in the self-assembling distribution of the sensing and computation at the many layers envisioned in Culler's Experimental Networked Sensor System Architecture. However, by replacing the evaluation module with (2) real-time evaluation of inventories of buildings and lifeline networks, or (3) adaptive coordination of emergency response and recovery modules, the same IT can be used – a "fractal" approach to problems of similar form occurring on several scales.