Get Energy-Efficient Distributed Computing Systems PDF

By Albert Y. Zomaya

ISBN-10: 0470908750

ISBN-13: 9780470908754

ISBN-10: 1118342011

ISBN-13: 9781118342015

The power intake factor in disbursed computing structures increases a number of financial, environmental and process functionality concerns. Electricity intake within the US doubled from 2000 to 2005.  From a monetary and environmental viewpoint, decreasing the intake of electrical energy is critical, but those reforms mustn't ever bring about functionality degradation of the computing systems.  those contradicting constraints create a collection of advanced difficulties that have to be resolved that allows you to bring about 'greener' disbursed computing systems.  This booklet brings jointly a gaggle of remarkable researchers that examine the several points of eco-friendly and effort effective disbursed computing.

Key features:

  • One of the 1st books of its variety
  • Features most modern learn findings on rising subject matters by way of recognized scientists
  • Valuable study for grad scholars, postdocs, and researchers
  • Research will vastly feed into different applied sciences and alertness domain names

Content:
Chapter 1 energy Allocation and job Scheduling on Multiprocessor pcs with power and Time Constraints (pages 1–37): Keqin Li
Chapter 2 Power?Aware excessive functionality Computing (pages 39–79): Rong Ge and Kirk W. Cameron
Chapter three strength potency in HPC structures (pages 81–108): Ivan Rodero and Manish Parashar
Chapter four A Stochastic Framework for Hierarchical System?Level energy administration (pages 109–131): Peng Rong and Massoud Pedram
Chapter five Energy?Efficient Reservation Infrastructure for Grids, Clouds, and Networks (pages 133–161): Anne?Cecile Orgerie and Laurent Lefevre
Chapter 6 Energy?Efficient activity Placement on Clusters, Grids, and Clouds (pages 163–187): Damien Borgetto, Henri Casanova, Georges Da Costa and Jean?Marc Pierson
Chapter 7 comparability and research of grasping Energy?Efficient Scheduling Algorithms for Computational Grids (pages 189–214): Peder Lindberg, James Leingang, Daniel Lysaker, Kashif Bilal, Samee Ullah Khan, Pascal Bouvry, Nasir Ghani, Nasro Min?Allah and Juan Li
Chapter eight towards Energy?Aware Scheduling utilizing computer studying (pages 215–244): Josep Ll. Berral, Inigo Goiri, Ramon Nou, Ferran Julia, Josep O. Fito, Jordi Guitart, Ricard Gavalda and Jordi Torres
Chapter nine strength potency Metrics for info facilities (pages 245–269): Javid Taheri and Albert Y. Zomaya
Chapter 10 Autonomic eco-friendly Computing in Large?Scale information facilities (pages 271–299): Haoting Luo, Bithika Khargharia, Salim Hariri and Youssif Al?Nashif
Chapter eleven power and Thermal acutely aware Scheduling in info facilities (pages 301–337): Gaurav Dhiman, Raid Ayoub and Tajana S. Rosing
Chapter 12 QOS?Aware strength administration in info facilities (pages 339–360): Jiayu Gong and Cheng?Zhong Xu
Chapter thirteen Energy?Efficient garage structures for facts facilities (pages 361–376): Sudhanva Gurumurthi and Anand Sivasubramaniam
Chapter 14 Autonomic Energy/Performance Optimizations for reminiscence in Servers (pages 377–394): Bithika Khargharia and Mazin Yousif
Chapter 15 ROD: a realistic method of enhancing Reliability of Energy?Efficient Parallel Disk structures (pages 395–415): Shu Yin, Xiaojun Ruan, Adam Manzanares and Xiao Qin
Chapter sixteen Embracing the reminiscence and I/O partitions for Energy?Efficient medical Computing (pages 417–441): Chung?Hsing Hsu and Wu?Chun Feng
Chapter 17 a number of Frequency choice in DVFS?Enabled Processors to lessen power intake (pages 443–463): Nikzad Babaii Rizvandi, Albert Y. Zomaya, younger Choon Lee, Ali Javadzadeh Boloori and Javid Taheri
Chapter 18 The Paramountcy of Reconfigurable Computing (pages 465–547): Reiner Hartenstein
Chapter 19 Workload Clustering for expanding strength reductions on Embedded MPSOCS (pages 549–565): Ozcan Ozturk, Mahmut Kandemir and Sri Hari Krishna Narayanan
Chapter 20 Energy?Efficient net Infrastructure (pages 567–592): Weirong Jiang and Viktor ok. Prasanna
Chapter 21 call for reaction within the shrewdpermanent Grid: A disbursed Computing standpoint (pages 593–613): Chen Wang and Martin De Groot
Chapter 22 source administration for disbursed cellular Computing (pages 615–651): Jong?Kook Kim
Chapter 23 An Energy?Aware Framework for cellular info Mining (pages 653–671): Carmela Comito, Domenico Talia and Paolo Trunfio
Chapter 24 power knowledge and potency in instant Sensor Networks: From actual units to the conversation hyperlink (pages 673–707): Flavia C. Delicato and Paulo F. Pires
Chapter 25 Network?Wide recommendations for strength potency in instant Sensor Networks (pages 709–750): Flavia C. Delicato and Paulo F. Pires
Chapter 26 power administration in Heterogeneous instant healthiness Care Networks (pages 751–785): Nima Nikzad, Priti Aghera, Piero Zappi and Tajana S. Rosing

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Additional resources for Energy-Efficient Distributed Computing Systems

Example text

PRE-POWER-DETERMINATION ALGORITHMS 19 The performance ratio is βET-LS ≤ BET-LS , where the performance bound is n m BET-LS = m r1α + r2α + · · · + rnα (r1 + r2 + · · · + rn )α 1/(α−1) . 2 Energy consumption minimization. To solve the problem of minimizing energy consumption with schedule length constraint T by using the equal-time algorithm ET-LS, we notice that enough energy EET-LS should be given such that TET-LS = T , that is, n m r1α + r2α + · · · + rnα EET-LS 1/(α−1) = T. The above equation implies that the energy consumed by algorithm ET-LS is EET-LS = n 1 m T α−1 r1α + r2α + · · · + rnα .

Assume that we are given n independent sequential tasks to be executed on m identical processors. , the number of CPU cycles or the number of instructions) of task i , where 1 ≤ i ≤ n. We use pi (Vi , fi , respectively) to represent the power (supply voltage, clock frequency, respectively) allocated to execute task i . For ease of discussion, we will assume 1/α that pi is simply siα , where si = pi is the execution speed of task i . The 1/α execution time of task i is ti = ri /si = ri /pi . The energy consumed to execute 1−1/α α−1 = ri si .

Min-Allah, Nasro, Department of Computer Science, COMSATS Institute of Information Technology, Pakistan. Narayanan, Sri Hari Krishna, Argonne National Laboratory, IL, USA. Nikzad, Nima, University of California, San Diego, CA, USA. Nou, Ramon, Computer Architecture Dept. , Catalonia, Spain. Orgerie, Anne-Cecile, Ecole Normale Superieure de Lyon, Lyon, France. Ozturk, Ozcan, Bilkent University, Turkey. Parashar, Manish, NSF Cloud and Autonomic Computing Center and Rutgers Discovery Informatics Institute, Rutgers University, NJ, USA.

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Energy-Efficient Distributed Computing Systems by Albert Y. Zomaya


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