J.F. Kurose and R. Simha, "A Microeconomic Approach to Optimal Resource Allocation in Distributed Computer Systems," IEEE Trans. Computers, vol. 38, no. 5, pp. 705-717, May 1989.  Home/Search   Document Not in Database   Summary   Related Articles   Check

....attention in the multi agent community was auctions. Algorithms for holding and deciding auctions have been proposed and analyzed [21, 19] both from the perspective of resource allocation [3, 20] and task allocation [30] and applied to task domains such as allocating operating system resources [15], providing library services [17] scheduling jobs on networks of workstations [8] and maintaining optimal o#ce climate [33] The most substantial di#erence between auctions and our game dynamics approach is that auction require a central authority, an auctioneer, to determine winners. In our ....

J. F. Kurose and R. Simha. A microeconomic approach to optimal resource allocation in distributed computer systems. IEEE Transactions on Computers, 38(5):705--717, 1989.

....problems often exhibit complementarities and nonconvexities, which violate the ideal conditions for the welfare theorems or for particular market protocols. Prior work applying market inspired mechanisms to scheduling [2, 13, 18, 34, 35] and other distributed resource allocation problems [8, 16, 32, 43] has produced promising empirical results. Understanding the scope of these methods, and developing a general design methodology for computational markets, however, requires an analytical characterization of their properties. In our own MOP work, wehave adopted the framework of general equilibrium ....

James F. Kurose and Rahul Simha. A microeconomic approach to optimal resource allocation in distributed computer systems. IEEE Transactions on Computers, 38:705{ 717, 1989.

....describe the main ingredients local strategyproof mechanisms and an open market for mechanisms and outline three core architectural components. In distinguishing SPC from the many earlier proposals for economically motivated mechanisms for decentralized resource allocation in systems (e.g. [2, 26, 6, 16, 7, 23]) we emphasize that this is an infrastructure effort. We contend that no single mechanism can possibly be appropriate for all requirements in a heterogeneous system. Instead, we seek to provide the equivalent of the dial tone for the development and deployment of computing services that explicitly ....

J. Kurose and R. Simha. A microeconomic approach to optimal resource allocation in distributed computer systems. IEEE Trans. on Computers, 38:705--717, 1989.

.... decentralized resource allocation aspects of traditional price based market models (e.g. 31 ] with the generality and robustness of mechanismbased approaches (e.g. 9] A vast number of economically motivated mechanisms have been proposed for decentralized resource allocation problems (e.g. [3, 29, 12, 11, 19, 12, 26]) Yet, we contend that no single mechanism can possibly be appropriate for all requirements in a heterogeneous system. We seek to provide the equivalent of the dialtone for the development and deployment of computing services that explicitly handle incentive considerations. The theory of ....

J. Kurose and R. Simha. A microeconomic approach to optimal resource allocation in distributed computer systems. IEEE Trans. on Computers, 38:705 717, 1989.

....the computer science literature traditionally did the opposite. The emergence of the Internet as a standard platform for distributed computation has changed this state of a#airs. Incentives have become an increasingly important consideration in network protocol design (see, for example, [FNY89, FS97, HA88, KLO95, KS89, S88, S90, S95]) More recently, the work of Nisan and Ronen [NR01] has inspired the design of algorithmic mechanisms for, e.g. scheduling, load balancing, lowest cost paths, and combinatorial auctions that satisfy both the traditional economic definitions of incentive compatibility and the traditional TCS ....

Kurose, J. F. and Simha, R. (1989). "A microeconomic approach to optimal resource allocation in distributed computer systems," IEEE Transactions on Computers 38, 705--717.

....this reason, a method to manage these limited resources in a fair and e#cient manner is needed. Recently, pricing has been promoted as a method for allocating network resources. Under these techniques, users are charged for their consumption and resources are priced to reflect supply and demand [1, 8, 9, 11, 16, 18, 19]. Benefits of pricing network resources include: flexible, precise, and distributed control of congestion; the ability to accomplish economic goals such as revenue generation; and provably fair resource allocations. When pricing is used for network resource allocation, fairness definitions can be ....

....and variable bit rate sources) However, most pricing methods lack these attributes. For example, many pricing techniques are not intended to adapt to changing tra#c demands that occur on various time scales, nor have they been validated using realistic network topologies or actual tra#c [1, 18]. In addition, the transient behavior and the method of distributing prices and allocations during convergence is generally ignored [9, 19] Other limitations include the reliance on well defined statistical models of source tra#c and restrictions on the shape of the utility curve [8, 16, 18] In ....

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J. F. Kurose and R. Simha. A Microeconomic Approach to Optimal Resource Allocation in Distributed Computer Systems. IEEE Transactions on Computers, 38(5):705 -- 717, May 1989.

....is important to address these issues simultaneously. However, previous microeconomic based research has only investigated these issues in isolation. It has been demonstrated that pricing is an effective method for achieving fair allocations as well as revenue generation [7] 8] 9] 10] 11] [12], 13] However, these methods are not based on a market hierarchy, and do not consider how to provision resources. Other work has investigated resource provisioning [14] 15] 3] 16] where bandwidth contracts (SLA) are bought and sold among bandwidth brokers or Internet service providers. ....

J. F. Kurose and R. Simha, "A Microeconomic Approach to Optimal Resource Allocation in Distributed Computer Systems," IEEE Transactions on Computers, vol. 38, pp. 705 -- 717, May 1989.

....di erent bandwidth market systems with each other, and with other allocation schemes. Since the mid 80 s, arti cial markets for resource allocation has been suggested for for a variety of di erent allocation tasks in distributed computer systems, ranging over markets for storage capacity [Kurose89], CPU time [Ferguson88] Waldspurger92] and network capacity [Kurose85] Sairamesh95] The emphasis has been on evaluating the e ciency of the resource allocation, rather than understanding the resulting price dynamics. More recent work has stressed the agent aspect, i.e. that the trading parties ....

James F. Kurose, and Rahul Simha, A Microeconomic Approach to Optimal Resource Allocation in Distributed Computer Systems, IEEE Trans. on Computers, (38) no. 5, May 1989.

....the optimal allocation amount. This is undesirable because the economy relies on one entity, which is not reliable or fault tolerant. Another microeconomic approach, congestion pricing, charges users for their consumption of resources and resources are priced to reflect supply and demand [1, 4, 5, 11, 20]. Alternatively, prices can be set with respect to marginal costs [15] With such a model, prices can be set to encourage high utilization of network resources as well as a fair distribution. Users act independently, attempting to maximize their own utility and prices are set based on local ....

J. F. Kurose and R. Simha. A microeconomic approach to optimal resource allocation in distributed computer systems. IEEE Transactions on Computers, 38(5):705 -- 717, May 1989.

....time. The class of problems dealing with the assignment of files to processing nodes to optimize performance is commonly known as the file allocation problem (FAP) This class of problems with different objectives and constraints has been addressed in the literature [1] 2] 3] 5] 7] [10], 12] 14] 15] 17] 18] 19] Since FAPs are complex integer programming problems with no known efficient solutions [4] heuristics are used to find optimal solutions. In this paper, we address FAP in a virtual circuit network environment. A virtual circuit enables bandwidth to be ....

J.F. Kurose and R. Simha, " Microeconomic Approach to Optimal Resource Allocation in Distributed Computer Systems,"IEEE Trans. Computers, vol. 38, no. 5, pp. 705-717, May 1989.

....the computer science literature traditionally did the opposite. The emergence of the Internet as a standard platform for distributed computation has changed this state of a airs. Incentives have become an increasingly important consideration in network protocol design (see, for example, [FNY89, FS97, HA88, KLO95, KS89, S88, S90, S95]) More recently, the work of Nisan and Ronen [NR01] has inspired the design of algorithmic mechanisms for, e.g. scheduling, load balancing, lowest cost paths, and combinatorial auctions that satisfy both the traditional economic de nitions of incentive compatibility and the traditional TCS de ....

Kurose, J. F. and Simha, R. (1989). \A microeconomic approach to optimal resource allocation in distributed computer systems," IEEE Transactions on Computers 38, 705-717.

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J.F. Kurose and R. Simha, "A Microeconomic Approach to Optimal Resource Allocation in Distributed Computer Systems," IEEE Trans. Computers, vol. 38, no. 5, pp. 705-717, May 1989.

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J. Kurose and R. Simha. A microeconomic approach to optimal resource allocation in distributed computer systems. IEEE Trans. on Computers, 38(5):705-717, 1989.

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Kurose J,Simha R. A microeconomic approach to optimal resource allocation in distributed computer systems. IEEE Transactions on Computers 1989;38(5):705--17.

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J. Kurose and R. Simha. A microeconomic approach to optimal resource allocation in distributed computer systems. IEEE Trans. on Computers, 38(5):705717, 1989.

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J. Kurose and R. Simha. A microeconomic approach to optimal resource allocation in distributed computer systems. IEEE Trans. on Computers, 38(5):705717, 1989.

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J Kurose and R Simha. A microeconomic approach to optimal resource allocation in distributed computer systems. IEEE Trans. on Computers, 38:705--717, 1989.

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Kurose, J. F. and R. Simha (1989). A microeconomic approach to optimal resource allocation in distributed computer systems, IEEE Transactions on Computers 38, 705--717.

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J. F. Kurose. A microeconomic approach to optimal resource allocation in distributed computer systems. IEEE Transactions on Computers, 38(5):705--717, 1989.

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J. Kurose and R. Simha, "A Microeconomic Approach to Optimal Resource Allocation in Distributed Computer Systems," IEEE Transactions on Computers, vol. 38, no. 5, pp. 705--717, May 1989.

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J.F. Kurose and R. Simha, "A Microeconomic Approach to Optimal Resource Allocation in Distributed Computer Systems," IEEE Trans. Computers, vol. 38, no. 5, pp. 705-717, May 1989.

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J. Kurose and R. Simha. A microeconomic approach to optimal resource allocation in distributed computer systems. IEEE Trans. on Computers, 38(5):705-717, 1989.

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J. Kurose and R. Simha. A microeconomic approach to optimal resource allocation in distributed computer systems. IEEE Transactions on Computers, 38(5), 1989.

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James F. Kurose, and Rahul Simha, A Microeconomic Approach to Optimal Resource Allocation in Distributed Computer Systems, IEEE Trans. on Computers, (38) no. 5, May (1989).

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J. Kurose and R. Simha, "A Microeconomic Approach to Optimal Resource Allocation in Distributed Computer Systems," IEEE Transactions on Computers 38 (1989), pages 705--717.

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