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Sensing the Datacenter

Sensing the Datacenter. Heterogeneous Sensor network for Datacenter Workload and power management Jorge Ortiz CS294-14 Architectures for Internet Datacenters October 10, 2007. Datacenters Consume Lots of Power. Datacenter power consumption increasing

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Sensing the Datacenter

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  1. Sensing the Datacenter Heterogeneous Sensor network for Datacenter Workload and power management Jorge Ortiz CS294-14 Architectures for Internet Datacenters October 10, 2007

  2. Datacenters Consume Lots of Power • Datacenter power consumption increasing • Environmental Protection Agency (EPA) report shows power-consumption has doubled in last 5 years • 1.5% of total U.S. Electricity Consumption in 2006 • Projected to double again in next 5 years • Datacenter under-provisioned for saving power • Sensing and control separate from load balancer • Protocols and applications are energy unaware • What I propose: • Couple the sensing and control with the load balancer/tasking decisions • Dynamic Adjustment • Graceful workload adjustment for saving power

  3. Sensors Facilitate Dynamic Energy Accounting • Include power-related input into the protocol and management loop • Make use of equipment sensors already available to gather information about power consumption • Power meters to attach to server/racks • On-board temperature sensors • In-band network monitors • Wireless sensor network technology to include out-of-band monitoring infrastructures • Single on-board sensors sometimes give wacky readings • Array of sensors adds redundancy and improves accuracy • Wireless motes ease deployment and data collection

  4. Loose Ends • Datacenter-scale workloads unavailable • Monitoring machine room activity not at same scale as internet datacenter, but it’s a good start • Power metering equipment needed • A couple of one-outlet monitors already in use • Access to 420A (Soda Hall Machine room) or the RadLab Machine room • Direct access to specific machines in (either) machine room

  5. Semester Plan • Provision the Soda Hall machine room (420A) or the RadLab machine room with wireless sensors (temperature, humidity, etc.) • Attach power meters to a set of servers in the machine room • Setup process (top), network (netstat), and disk monitors (iostat) to determine distribution of machine activity • Analyze gathered data • Formulate a model that relates temperature and power consumption • Analyze the relationship between component utilization and ambient temperature • Machine-learning techniques for formulation of predictive models for graceful workload degradation

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