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The current techniques and tools for collecting, aggregating, and reporting verifiable sustainability data are vulnerable to cyberattacks and misuse, requiring new security and privacy-preserving solutions. This article outlines security challenges and research directions for addressing these requirements. 

Despite several calls from the community for improving the sustainability of computing, sufficient progress is yet to be made on one of the key prerequisites of sustainable computing---the ability to define and measure computing sustainability holistically. This position paper proposes metrics that aim to measure the end-to-end sustainability footprint in data centers. To enable useful sustainable computing efforts, these metrics can track the sustainability footprint at various granularities---from a single request to an entire data center. The proposed metrics can also broadly influence sustainable computing practices by incentivizing end-users and developers to participate in sustainable computing efforts in data centers. 

Sustainability is crucial for combating climate change and protecting our planet. While there are various systems that can pose a threat to sustainability, data centers are particularly significant due to their substantial energy consumption and environmental impact. Although data centers are becoming increasingly accountable to be sustainable, the current practice of reporting sustainability data is often mired with simple green-washing. To improve this status quo, users as well as regulators need to verify the data on the sustainability impact reported by data center operators. To do so, data centers must have appropriate infrastructures in place that provide the guarantee that the data on sustainability is collected, stored, aggregated, and converted to metrics in a secure, unforgeable, and privacy-preserving manner. Therefore, this paper first introduces the new security challenges related to such infrastructure, how it affects operators and users, and potential solutions and research directions for addressing the challenges for data centers and other industry segments. 

Data center operators generally overprovision IT and cooling capacities to address unexpected utilization increases that can violate service quality commitments. This results in energy wastage. To reduce this wastage, we introduce HCP (Holistic Capacity Provisioner), a service latency aware management system for dynamically provisioning the server and cooling capacity. Short-term load prediction is used to adjust the online server capacity to concentrate the workload onto the smallest possible set of online servers. Idling servers are completely turned off based on a separate long-term utilization predictor. HCP targets data centers that use chilled air cooling and varies the cooling provided commensurately, using adjustable aperture tiles and speed control of the blower fans in the air handler. An HCP prototype supporting a server heterogeneity is evaluated with real-world workload traces/requests and realizes up to 32% total energy savings while limiting the 99th-percentile and average latency increases to at most 6.67% and 3.24%, respectively, against a baseline system where all servers are kept online. 

Proponents of AC-powered data centers have implicitly assumed that the electrical load presented to all three phases of an AC data center are balanced. To assure this, servers are connected to the AC power phases to present identical loads, assuming an uniform expected utilization level for each server. We present an experimental study that demonstrates that with the inevitable temporal changes in server workloads or with dynamic sever capacity management based on known daily load patterns, balanced electrical loading across all power phases cannot be maintained. Such imbalances introduce a reactive power component that represents an effective power loss and brings down the overall energy efficiency of the data center, thereby resulting in a handicap against DC-powered data centers where such a loss is absent. 

The recent availability of water cooling systems that can be easily retrofitted to stock servers by replacing the heatsinks with coldplates has made it possible to use such systems for non-HPC cloud/data center servers. These cooling systems use pumps to circulate water and the pumps are likely to fail in the long run. We present a technique to handle flow disruptions caused by the pump failures in a virtualized environment. The solution uses an estimation of the residual cooling capacity left in the failed cooling system to adaptively adjust the CPU clock frequency as virtual machines are migrated off the racks affected by the failure. This minimizes the degradation of the tail latencies of the served requests during the migration interval for all servers affected by the failure, as seen in the experimental results 

Recent availability of warm water cooling systems that can be easily retrofitted to stock server by replacing the heatsinks with coldplates have made it possible to use such cooling for non-HPC cloud/data center servers. These cooling systems use internal pumps in rack-level heat exchangers as well as external pumps that can fail. We present a systematic study of the pump failures that disrupt flow in the cooling system, propose and experimentally evaluate techniques for reducing service disruptions during failures while avoiding damage to the servers where water cooling has failed.