Carla Ellis
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      It is hard to imagine that any truly "Grand Challenge" can be
compartmentalized into the relatively narrow domain of distributed systems.
Such problems should drive technological advances across a broad range of
disciplines; just limiting the discussion to computer science and engineering,
these might include new materials, circuit design, computing architecture,
software systems, applications, and HCI. Certainly, distributed computing can
play a role in problems significant enough to science and society to be called
"grand."  It is that spirit that I discuss the contributions that 
distributed systems
can make in addressing the undisputable grand challenge of global climate
change.
      There are two dimensions to this theme: (1) making our future computing
infrastructure safer for the environment and (2) finding ways for computing to
serve the environment.  A "greener" computing infrastructure will entail (1a)
reducing the energy and materials going into manufacture, deployment, and
retirement of computing devices and (1b) reducing the energy (especially from
non-renewable sources) of running and cooling our computing infrastructure.
Computing to serve the environmental goals will entail (2a) computational
support for the sciences studying global climate change and (2b) 
applications of
computing to enhance energy efficiency beyond the traditional computing
infrastructure.
      Distributed computing research can contribute to these goals. Examples
include: (1a) There are estimates that the typical desktop computer 
requires ten
times its weight in fossil fuels and chemicals in its manufacture while there
exists significant unused computing capacity in the Internet. Creating better
incentives (and eliminating disincentives) for sharing can allow more 
efficient
utilization of existing resources.  P2P can be viewed as an analogy to 
carpooling
with private PCs seen as the equivalent of SUVs in every garage. Emerging
technologies offering a "greener" lifecycle may require new forms of software
system support. (1b) The low-hanging fruit of computing device energy
management has been recently harvested.  Further progress in energy efficient
computing requires a more aggressive approach and a broader systems context.
(2a) Grid computing and wireless sensor networks combine to support dynamic
data-driven simulations of the environment. (2b) Distributed applications can
manage energy use and distribution systems in buildings, transportation
systems, homes, utilities, manufacturing processes, etc. Pervasive computing
changes the way people and businesses interact with significant potential for
energy savings (e.g., teleconferencing).
      In making this a focus for distributed systems research, the following
elements are required: development of appropriate metrics and measurement
expertise/tools to assess the environmental impact of any networked computing
solution (e.g., we can't even quantify the energy wasted in the Internet),
interfaces that expose the energy costs of user behaviors and application 
design
decisions, incentive systems to facilitate energy-motivated resource sharing,
energy harvesting and scheduling techniques, pervasive and collaborative
application development, deployment of sensor networks and integration of
dynamic data in scientific simulations or environmental control applications,
and new design methodologies to capture tradeoffs between computer and
external energy use.
      Distributed systems research is only a contributing factor toward 
solving
this grand challenge.  Success can be defined in terms of compelling
demonstrations of feasibility in terms of energy savings (or other 
environmental
metrics) to motivate the complementary technical research in other fields as
well as any social/legal/policy changes necessary.