Cisco Cisco Energy Management Optimization Service Weißbuch
© 2014 Cisco and/or its affiliates. All rights reserved. This document is Cisco Public Information.
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Automated asset discovery is the first step in energy management for the distributed office. A network-based
solution will use remote network monitoring to build a device database and perform initial measurement. The initial
monitoring period provides a baseline for energy consumption and utilization.
An analytics engine within the solution can then analyze energy consumption, costs, and carbon emissions by
business unit, cost center, department, device, and location down to the application and virtual machine. The
analytics engine can also perform “what if” energy management scenarios to test various cost-saving strategies
analytics engine can also perform “what if” energy management scenarios to test various cost-saving strategies
and make sure that SLAs and productivity remain intact.
The solution should also include a rules engine, which is used to create and automatically execute energy
management policies based on time, event, or location. These automated policies control the power state of each
device or system connected to the network and enable flexible load-adaptive computing. Reporting and decision
support give organizations the tracking, statistics, and useful comparisons they need to specifically
determineenergy-saving opportunities and track energy/carbon reduction goals.
Using Policy to Create Energy Savings
With a network-based, comprehensive solution, enterprises will gain the ability to optimize and reduce
energy consumption across distributed office environments. They will also be able to create policies to
automatically and remotely manage power for distributed office equipment, powering systems down when
idle/not needed. When energy follows productive users, enforced by automated policies, capacity aligns with
demand across the distributed office environment, and savings are achieved. This shifts thinking and practice from
consuming maximum power at all times by default to dynamically consuming the amount of power needed.
Organizations that have already adopted an enterprise energy management solution are making some interesting
discoveries about employee work habits and power drawn by various office equipment. For example, one company
learned that its video teleconferencing system was drawing as much energy overnight as an entire floor’s worth of
learned that its video teleconferencing system was drawing as much energy overnight as an entire floor’s worth of
devices and equipment. By automating a time-based policy to power down this system during idle hours, the
company achieved significant, immediate savings.
Another organization learned that many of its supposedly mobile computing devices never left the building.
Furthermore, many of these devices were often left on overnight while not in use. Automated policies that power
down idle, unproductive office equipment can save 30 to 60 percent in energy costs. An ideal solution will provide
opt-in/opt-out policies for end users to preserve productivity.
Event-based policies designed to support energy following the productive user can power up/down campus
devices when employees enter and exit a facility. Time-based policies power down PCs, monitors, access points,
printers, copiers, and lights after hours and on weekends. Additionally, another capability, load-adaptive computing,
adds even more granular flexibility to managing energy consumption in the distributed office environment.