Doron Chen

New relaxation-based algorithms for the optimal solution of the continuous and discrete p-center problems

We present new relaxation algorithms for the uncapacitated continuous and discrete p-center problems. We have conducted an experimental study that demonstrated that these new algorithms are extremely efficient.

Usage centric green performance indicators

Energy effciency of data centers is gaining importance as energy consumption and carbon footprint awareness are rising. Green Performance Indicators (GPIs) provide measurable means to assess the energy effciency of a resource or system. Most of the metrics commonly used today measure the energy effciency potential of a resource, system or application usage, rather than the energy effciency of the actual usage. In this paper, we argue that the way that the resources and systems are actually used in a given data center configuration is at least as important as the effciency potential of the raw resources or systems. Hence, for data center energy effciency, we suggest to both select energy effcient components (as done today), as well as optimize the actual usage of the components and systems in the data center. To achieve the latter, optimization of usage centric GPI metrics should be employed and targeted as a primary green goal. In this paper we identify and present usage centric metrics, which should be monitored and optimized for improving energy effciency, and hence, reduce the data center carbon footprint.

Leveraging disk drive acoustic modes for power management

Reduction of disk drive power consumption is a challenging task, particularly since the most prevalent way of achieving it, powering down idle disks, has many undesirable side-effects. Some hard disk drives support acoustic modes, meaning they can be configured to reduce the acceleration and velocity of the disk head. This reduces instantaneous power consumption but sacrifices performance. As a result, input/output (I/O) operations run longer at reduced power. This is useful for power capping since it causes significant reduction in peak power consumption of the disks. We conducted experiments on several disk drives that support acoustic management. Most of these disk drives support only two modes — quiet and normal. We ran different I/O workloads, including SPC-1 to simulate a real-world online transaction processing workload. We found that the reduction in peak power can reach up to 23% when using quiet mode. We show that for some workloads this translates into a reduction of 12.5% in overall energy consumption. In other workloads we encountered the opposite phenomenon-an increase of more than 6% in the overall energy consumption.

A relaxation-based algorithm for solving the conditional p-center problem

We present a new relaxation algorithm for solving the conditional continuous and discrete p-center problems.

Setting energy efficiency goals in data centers: the GAMES approach

Energy-aware service centers take into account energy consumption of infrastructures, machines, applications, storage systems, and their distributed computing architecture. The approach to energy efficiency in data centers in the GAMES (Green Active Management of Energy in IT Service centers) project is presented: Green Performance Indicators (GPIs), i.e., properties that, continuously monitored, evidence the level of consumed energy by the centers IT resources, can be the basis of a systematic approach to increase energy efficiency. The GPIs are the basis for improving energy efficiency with adaptive actions and to achieve a higher level of green maturity, as prescribed, for instance, in the GreenGrid Data Center Maturity Model (DCMM), based on a usage-centric perspective in GPIs. The paper briefly describes monitoring of GPIs and the adaptation actions adopted to reach the green goals. Preliminary experimental results are discussed.

Combinatorial Preconditioners for Scalar Elliptic Finite-Element Problems

We present a new preconditioner for linear systems arising from finite-element discretizations of scalar elliptic partial differential equations (PDEs). The solver splits the collection

Optimal algorithms for the α-neighbor p-center problem

\{K_{e}\}

Too Big to Eat: Boosting Analytics Data Ingestion from Object Stores with Scoop

of element matrices into a subset of matrices that are approximable by diagonally dominant matrices and a subset of matrices that are not approximable. The approximable

QoS differentiation in an advanced object store

K_{e}

Accelerating convergence in the Fermat-Weber location problem

s are approximated by diagonally dominant matrices