HANDBOOK OF ENERGY-AWARE AND GREEN COMPUTING PDF

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Request PDF on ResearchGate | On Jan 1, , S.S. Gupta and others published Handbook of energy-aware and green computing. Edited by the co-chairs of the International Green Computing Conference, this science and engineering, Handbook of Energy-Aware and Green Computing, Chapter Energy Efficiency of Voice-over-IP Systems · Download PDF. Handbook on Energy-Aware and Green Computing. Abstract. Cloud computing 11(2)–, ftp://ciofreedopadkin.ga ciofreedopadkin.ga


Handbook Of Energy-aware And Green Computing Pdf

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Cellular Memetic Algorithms for Energy-Aware. Computation and Communications Optimization in. Computing Clusters. 4. Benjamin C. Lee. Ebook Pdf Handbook Of Energy Aware And Green Computing Two Volume Set Chapman. Hallcrc Computer And Information Science contains important. Handbook of Energy-Aware and Green Computing. Volume 2. Edited by. Ishfaq Ahmad. Sanjay Ranka. CRC Press. Taylor & Francis Croup. Boca Raton.

Several avenues for energy optimization are identified in section III. Section IV describes green strategies for software developers. Section VI gives details of green scheduler. Finally, Section VII concludes this research. Related work A. After register and code selection, backend converts the intermediate code by applying optimization techniques including common sub expressions, dead code elimination, register pipelining, instruction scheduling, jump optimization and mapping of program object to different type of memory.

Assembler and linker execute this code to form a binary executable. Profiler take gathered information from simulator and database. These statistics are summed up and the performance statistic of complete program is generated [ 8 ]. Coffee compiler for C language is combination of software and customized hardware to achieve energy conservation at compile time [ 9 ]. A major weakness of coffee compiler and encc is hardware dependency since they are designed for embedded systems.

Furthermore, green strategies implementation increases compile time especially for large projects, which causes performance degradation. It does preprocessing of an input source file, which include placement of header files on source files. It is a good approach towards distributed compilers but does not give energy conservative executable.

Proposed DGC is a hardware independent compiler that does not require any special hardware. It optimizes and reshapes source code in energy conservative executable by implementing software level green strategies.

Several compilation problems are very large and cannot be compiled efficiently on a single machine. Thus a distributed environment can be a good solution for these problems, but hard for small compilation problems. DGC is able to perform program compilation with both approaches.

A program contains several green aspects; some of them cannot be handled by energy aware compilers for example recursion elimination etc. Therefore, these aspects are skipped during energy aware executable generation process, and hence cause inefficiency. DGC facilitates its programmers by highlighting sensitive areas of program which consume extra energy and cannot be reshaped by compiler.

Scheduler literature Grid computing provides the efficiency in terms of availability of number of distributed resources that perform the computation. In [ 11 ] a scheduling system for grid is introduced which encompasses three phases: resource discovery that lists all the available resources, system selection based on gathered information, and file staging and cleanup done by job execution.

The proposed strategy has disadvantage in term of involvement of users in scheduling decision. In [ 12 ], Chameleon scheduler is proposed that is designed for computational as well as data grid. This scheduler works well for large data applications and replicated data in grid environment.

Handbook of Energy-Aware and Green Computing

In [ 13 ] a scheduler is proposed that not only dynamically allocates the resources but also define the mechanism for inter component communication. In [ 14 ], stealth scheduler is introduced which is specifically designed for Workstation-based Distributed system WDS.

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WDS refers to the distributed workstations that provide large computing capacity but WDS software system does not efficiently share the computing capacity among workstations. Moreover, the foreign processes are preempted when owner process of workstation is initiated thus causing the foreign process to wait till the end of owner process or some idle node is available.

To overcome this barrier stealth scheduler does not preempt the foreign process on initiation of owner process. This avoids the unnecessary preemptive transfers thus increasing the efficiency to fully utilize the computing capacity. StealthLS shields the effect of foreign process on owner process and it does not allow preemptive transfers thus enhancing the performance. Whereas, StealthGS allow the preemptive transfers only when required to avoid the starvation, provides transparency by automating the transfer process, and implements decentralized global scheduling thus avoiding the bottleneck that incurs in centralized environment.

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Form the above description it is clear that the above mentioned schedulers lack green aspects. In [ 15 ], a green scheduler for cloud infrastructure is reported, which comprises of four algorithms.

Task scheduling algorithm schedules the tasks on number of machines on the basis of earliest deadline first strategy and largest capacity first strategy. Earliest deadline first strategy queue the coming tasks whereas the largest capacity strategy is used to allocate the tasks to virtual machines.

Finally, the evaluation algorithm is used to monitor the performance when the load changes. In [ 16 ], DVFS enabled scheduling is proposed. This scheduling algorithm was originally designed for clusters then adapted in cloud with some modifications.

The virtual machine request arrives at scheduler, which according to the requirement allocates the VM to the processing element PE.

PE is allocated based on voltage level. If in case no PE is found that satisfy the requirement then PE that operates at higher voltage is selected.

Moreover, with the finish in job by any VM the supply voltage o-f PE is reduced. The effort to reduce the energy consumption is not confined to the servers only but efforts are also laid to reduce the power that is used to operate cooling systems.

For this thermal aware scheduling [ 17 ] is used that schedules the job such that it reduces the overall power consumption of datacenter. Moreover, to reduce the power consumption by server, power aware scheduler [ 18 ] is designed. This scheduling approach aims at using all the processing cores in a node, which according to research, reduces the power consumption.

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The algorithm used in power aware scheduling is greedy-based algorithm. It has been observed that most of the energy efficient schedulers do not take into account the network and traffic [ 19 ]. Deals with the selection of appropriate path for traffic, for this purpose tree routing topology and multi-path protocol are used. When hash function is applied by protocol then collision might occur.

Wonfor, H. Wang, R. Penty, I.

White, X. Dong, T.

El-Gorashi, and J. Evans, Sandeep Gupta, Karen L. As computers increase in speed and power, their energy issues become more and more prevalent. The need to develop and promote environmentally friendly computer technologies and systems has also come to the forefront in computing research. A pioneering publication for researchers in computer science and engineering, Handbook of Energy-Aware and Green Computing is one of the first to present a comprehensive account of recent research in energy-aware and green computing.Butt, Guanying Wang, Chris Gniady.

Get Citation. It also discusses up-to-date research on many aspects of power-aware computing at the component, software, and system levels.

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Implementing energy-efficient CPUs and peripherals as well as reducing resource consumption have become emerging trends in computing.

Implementing energy-efficient CPUs and peripherals as well as reducing resource consumption have become emerging trends in computing. Several compilation problems are very large and cannot be compiled efficiently on a single machine. This research also presents a review of various schedulers reported in literature and scheduling in DIET is modified to introduce the green aspect in scheduling. SPEC: Standard performance evaluation corporation, power and performance methodology.

It does preprocessing of an input source file, which include placement of header files on source files.