Improving Performance of Algorithms in Distributed Computing with Perspective of Green Information Technology
25 Feb 2010-International Journal of Computer Applications (Foundation of Computer Science FCS)-Vol. 1, Iss: 18, pp 75-78
TL;DR: This paper provides algorithms to green compute by calculating a threshold and sending systems to power saving modes if the processor is idle and in order to minimize energy consumption by processor allocation.
Abstract: In Distributed Computing approach, it is followed to assign a job to a processor if it is idle. The focus is now on how to optimize resources to decrease the energy consumption by volumes of computing equipments to deal with green and sustainability issues. So that to save environment from Global Warming and utilizing the resources efficiently. This process is twofold One hand providing green and power efficient algorithms and on the other supporting companies green investments. In order to minimize energy consumption by processor allocation we are providing some algorithms to generalize distributed computing. In this paper we provide algorithms to green compute by calculating a threshold and sending systems to power saving modes if the processor is idle.
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25 Feb 2011
TL;DR: An algorithm has been developed that will calculate the processor utilization by different machines according to the Load Distribution in a network and propose a strategy to utilize minimum possible energy by optimal resource utilization.
Abstract: This paper is focused on calculating the processor utilization of various machines having different types of processor configurations employed in data centers by providing solutions to reduce the energy cost component of companies total IT budget. In this paper different parameters like CPU Utilization and Power Utilization on different machines installed in data centers have been analyzed. Also calculation of power required by different machines of different configurations in different modes of operations like active mode, hibernation mode and standby mode is been performed. Here an algorithm has been developed that will calculate the processor utilization by different machines according to the Load Distribution in a network and propose a strategy to utilize minimum possible energy by optimal resource utilization.
5 citations
Cites methods from "Improving Performance of Algorithms..."
...Assigns the tasks performed by PUmin to the processor which has PUn% <= 100% - PUmin ----------------------(2) and puts the computer with PUmin in any of the power modes discussed above, making its processor's utilization PUn% approximately equal to zero....
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01 Jan 2011
TL;DR: A concept in the model which creates slave objects dynamically to fulfill the master/slave parallel computing pattern ensures easy distribution of the software components, files and resources along the participating computers.
Abstract: Data conversion is one of the major task in computerization and the data mining process. Thousands of private and the governmental organizations are trying to convert the entire paper document to soft documents. In another example many old format wave files need to be keep safe in very low space and there are thousands of historical wave file need to be convert in to lower size file format. Considering such conditions there is a need to employee the system which will transfer processing over the network system and save output on the server or main system, we are proposing a parallel computing model for the distributed computing platforms. This model ensures easy distribution of the software components, files and resources along the participating computers. We are using a concept in the model which creates slave objects dynamically to fulfill the master/slave parallel computing pattern. When compared with the other similar models results show that our model is not only a feasible model for distributed environment but also an efficient approach of data conversion in distributed parallel computing environment.
Cites background from "Improving Performance of Algorithms..."
...The focus is now on how to optimize resources to decrease the energy consumption by volumes of computing equipments to deal with green and sustainability issues.[9]There are many different types of distributed computing systems and many challenges to overcome in successfully designing one....
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References
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Book•
01 Jan 2001TL;DR: Intended for use in a senior/graduate level distributed systems course or by professionals, this text systematically shows how distributed systems are designed and implemented in real systems.
Abstract: From the Publisher:
Andrew Tanenbaum and Maarten van Steen cover the principles, advanced concepts, and technologies of distributed systems in detail, including: communication, replication, fault tolerance, and security. Intended for use in a senior/graduate level distributed systems course or by professionals, this text systematically shows how distributed systems are designed and implemented in real systems. Written in the superb writing style of other Tanenbaum books, the material also features unique accessibility and a wide variety of real-world examples and case studies, such as NFS v4, CORBA, DOM, Jini, and the World Wide Web.
FEATURES
Detailed coverage of seven key principles.
An introductory chapter followed by a chapter devoted to each key principle: communication, processes, naming, synchronization, consistency and replication, fault tolerance, and security, including unique comprehensive coverage of middleware models.
Four chapters devoted to state-of-the-art real-world examples of middleware. Covers object-based systems, document-based systems, distributed file systems, and coordination-based systems including CORBA, DCOM, Globe, NFS v4, Coda, the World Wide Web, and Jini.
Excellent coverage of timely, advanced, distributed systems topics: Security, payment systems, recent Internet and Web protocols, scalability, and caching and replication.
NEW-The Prentice Hall Companion Website for this book contains PowerPoint slides, figures in various file formats, and other teaching aids, and a link to the author's Web site.
2,011 citations
TL;DR: The problem of judiciously and transparently redistributing the load of the system among its nodes so that overall performance is maximized is discussed and conclusions about which algorithm might help in realizing the most benefits of load distributing are drawn.
Abstract: The problem of judiciously and transparently redistributing the load of the system among its nodes so that overall performance is maximized is discussed. Several key issues in load distributing for general-purpose systems, including the motivations and design trade-offs for load-distributing algorithms, are reviewed. In addition, several load-distributing algorithms are described and their performances are compared. These algorithms are sender-initiated algorithms, receiver-initiated algorithms, symmetrically initiated algorithms, and adaptive algorithms. Load-distributing policies used in existing systems are examined, and conclusions about which algorithm might help in realizing the most benefits of load distributing are drawn. >
583 citations
"Improving Performance of Algorithms..." refers methods in this paper
...In order to minimize energy consumption by processor allocation we are providing some algorithms to generalize distributed computing....
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01 Jan 1987
TL;DR: In this article, a dynamic load balancing method is proposed for a class of large-diameter multiprocessor systems based on the "gradient model", which entails transferring backlogged tasks to nearby idle processors according to a pressure gradient indirectly established by requests from idle processors.
Abstract: A dynamic load balancing method is proposed for a class of large-diameter multiprocessor systems. The method is based on the "gradient model," which entails transferring backlogged tasks to nearby idle processors according to a pressure gradient indirectly established by requests from idle processors. The algorithm is fully distributed and asynchronous. Global balance is achieved by successive refinements of many localized balances. The gradient model is formulated so as to be independent of system topology.
296 citations
TL;DR: A dynamic load balancing method is proposed for a class of large-diameter multiprocessor systems based on the "gradient model," which entails transferring backlogged tasks to nearby idle processors according to a pressure gradient indirectly established by requests from idle processors.
Abstract: A dynamic load balancing method is proposed for a class of large-diameter multiprocessor systems. The method is based on the "gradient model," which entails transferring backlogged tasks to nearby idle processors according to a pressure gradient indirectly established by requests from idle processors. The algorithm is fully distributed and asynchronous. Global balance is achieved by successive refinements of many localized balances. The gradient model is formulated so as to be independent of system topology.
274 citations
Book•
01 Jan 1998
TL;DR: java Distributed Computing provides a broad introduction to the problems you'll face and the solutions you'll find as you write distributed computing applications, paying special attention to distributed data systems, collaboration, and applications that have high bandwidth requirements.
Abstract: From the Publisher:
Distributed computing and Java go together naturally. As the first language designed from the bottom up with networking in mind, Java makes it very easy for computers to cooperate. Even the simplest applet running in a browser is a distributed application, if you think about it. The client running the browser downloads and executes code that is delivered by some other system. But even this simple applet wouldn't be possible without Java's guarantees of portability and security: the applet can run on any platform, and can't sabotage its host.
Of course, when we think of distributed computing, we usually think of applications more complex than a client and server communicating with the same protocol. We usually think in terms of programs that make remote procedure calls, access remote databases, and collaborate with others to produce a single result. Java Distributed Computing discusses how to design and write such applications. It covers Java's RMI (Remote Method Invocation) facility and CORBA, but it doesn't stop there; it tells you how to design your own protocols to build message passing systems and discusses how to use Java's security facilities, how to write multithreaded servers, and more. It pays special attention to distributed data systems, collaboration, and applications that have high bandwidth requirements.
In the future, distributed computing can only become more important. Java Distributed Computing provides a broad introduction to the problems you'll face and the solutions you'll find as you write distributed computing applications.
Topics covered in Java Distributed Computing:
Introduction to Distributed Computing Networking Basics Distributed Objects (Overview of CORBA and RMI) Threads Security Message Passing Systems Distributed Data Systems (Databases) Bandwidth Limited Applications Collaborative Systems
110 citations