2,499 research outputs found
Cluster-Based Load Balancing Algorithms for Grids
E-science applications may require huge amounts of data and high processing
power where grid infrastructures are very suitable for meeting these
requirements. The load distribution in a grid may vary leading to the
bottlenecks and overloaded sites. We describe a hierarchical dynamic load
balancing protocol for Grids. The Grid consists of clusters and each cluster is
represented by a coordinator. Each coordinator first attempts to balance the
load in its cluster and if this fails, communicates with the other coordinators
to perform transfer or reception of load. This process is repeated
periodically. We analyze the correctness, performance and scalability of the
proposed protocol and show from the simulation results that our algorithm
balances the load by decreasing the number of high loaded nodes in a grid
environment.Comment: 17 pages, 11 figures; International Journal of Computer Networks,
volume3, number 5, 201
Coalition Formation and Combinatorial Auctions; Applications to Self-organization and Self-management in Utility Computing
In this paper we propose a two-stage protocol for resource management in a
hierarchically organized cloud. The first stage exploits spatial locality for
the formation of coalitions of supply agents; the second stage, a combinatorial
auction, is based on a modified proxy-based clock algorithm and has two phases,
a clock phase and a proxy phase. The clock phase supports price discovery; in
the second phase a proxy conducts multiple rounds of a combinatorial auction
for the package of services requested by each client. The protocol strikes a
balance between low-cost services for cloud clients and a decent profit for the
service providers. We also report the results of an empirical investigation of
the combinatorial auction stage of the protocol.Comment: 14 page
Integrating Energy Storage into the Smart Grid: A Prospect Theoretic Approach
In this paper, the interactions and energy exchange decisions of a number of
geographically distributed storage units are studied under decision-making
involving end-users. In particular, a noncooperative game is formulated between
customer-owned storage units where each storage unit's owner can decide on
whether to charge or discharge energy with a given probability so as to
maximize a utility that reflects the tradeoff between the monetary transactions
from charging/discharging and the penalty from power regulation. Unlike
existing game-theoretic works which assume that players make their decisions
rationally and objectively, we use the new framework of prospect theory (PT) to
explicitly incorporate the users' subjective perceptions of their expected
utilities. For the two-player game, we show the existence of a proper mixed
Nash equilibrium for both the standard game-theoretic case and the case with PT
considerations. Simulation results show that incorporating user behavior via PT
reveals several important insights into load management as well as economics of
energy storage usage. For instance, the results show that deviations from
conventional game theory, as predicted by PT, can lead to undesirable grid
loads and revenues thus requiring the power company to revisit its pricing
schemes and the customers to reassess their energy storage usage choices.Comment: 5 pages, 4 figures, conferenc
Cost Based Optimization of Job Allocation in Computational Grids
Computational grids are distributed systems composed of heterogeneous computing resources which are distributed geographically and administratively. These highly scalable
systems are designed to meet the large computational demands of many users from scientific and business orientations. Grid computing is a powerful concept, its chief appeal being the ability to make sure all
of a resource’s computing power is used. In a grid world, the idle time of hundreds or thousands of resources could be harnessed and rented out to anyone who needed a massive infusion of processing power.
First, the architecture of a grid system is presented. The design gives a mathematical model of the grid system for efficiently allocating the grids resources. The challenges faced for optimal job allocation motivate the exploration in optimizing grid resource allocations. We have
extensively surveyed the current state of art in this area. A grid server coordinates the job allocation for the grid users and helps to select the best resources for a job among different possible resource offers with the best prices offered. Interaction between grid users and the resources require a mediator that uses different paradigm to communicate the needs of the two parties in terms of performance requirements, timing constraints, price charged etc. A game theoretic bargaining approach is studied to agree upon standard prices. We have implemented various job allocation schemes in computational grids based on the mathematical modeling of the grid system and bargaining protocol with the objective function of optimizing the cost. The performance of the schemes have been analyzed and compared. A new model for job allocation in computational grids has been proposed, for job allocation based on the clustering of resources
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