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17
A microeconomic approach to optimal resource allocation in distributed computer systems
 IEEE Trans. on Computers
, 1989
"... AbstractDecentralized algorithms are examined for optimally distributing a divisible resource in a distributed computer system. In order to study this problem in a specific context, we consider the problem of optimal file allocation. In this case, the optimization criteria include both the communi ..."
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Cited by 128 (1 self)
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AbstractDecentralized algorithms are examined for optimally distributing a divisible resource in a distributed computer system. In order to study this problem in a specific context, we consider the problem of optimal file allocation. In this case, the optimization criteria include both the communication cost and average processing delay associated with a file access. Our algorithms have their origins in the field of mathematical economics. They are shown to have several attractive properties, including their simplicity and distributed nature, the computation of feasible and increasingly better resource allocations as the result of each iteration, and in the case of file allocation, rapid convergence. Conditions are formally derived under which the algorithms are guaranteed to converge and their convergence behavior is additionally examined through simulation. Index TermsDistributed algorithms, distributed systems, file allocation, resource allocation, optimization I.
Mathematical decomposition techniques for distributed crosslayer optimization of data networks
 IEEE J. SEL. AREAS COMMUN
, 2006
"... Network performance can be increased if the traditionally separated network layers are jointly optimized. Recently, network utility maximization has emerged as a powerful framework for studying such crosslayer issues. In this paper, we review and explain three distinct techniques that can be used ..."
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Cited by 29 (3 self)
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Network performance can be increased if the traditionally separated network layers are jointly optimized. Recently, network utility maximization has emerged as a powerful framework for studying such crosslayer issues. In this paper, we review and explain three distinct techniques that can be used to engineer utilitymaximizing protocols: primal, dual, and cross decomposition. The techniques suggest layered, but loosely coupled, network architectures and protocols where different resource allocation updates should be run at different timescales. The decomposition methods are applied to the design of fully distributed protocols for two wireless network technologies: networks with orthogonal channels and networkwide resource constraints, as well as wireless networks where the physical layer uses spatialreuse timedivision multiple access. Numerical examples are included to demonstrate the power of the approach.
The Application of Microeconomics to the Design of Resource Allocation and Control Algorithms
, 1989
"... In this thesis, we present a new methodology for resource sharing algorithms in distributed systems. We propose that a distributed computing system should be composed of a decentralized community of microeconomic agents. We show that this approach decreases complexity and can substantially improve ..."
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Cited by 22 (4 self)
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In this thesis, we present a new methodology for resource sharing algorithms in distributed systems. We propose that a distributed computing system should be composed of a decentralized community of microeconomic agents. We show that this approach decreases complexity and can substantially improve performance. We compare the performance, generality and complexity of our algorithms with noneconomic algorithms. To validate the usefulness of our approach, we present economies that solve three distinct resource management problems encountered in large, distributed systems. The first economy performs CPU load balancing and demonstrates how our approach limits complexity and effectively allocates resources when compared to noneconomic algorithms. We show that the economy achieves better performance than a representative noneconomic algorithm. The load balancing economy spa...
Optimal scaling of a gradient method for distributed resource allocation
 Journal of Optimization Theory and Applications
, 2006
"... Abstract. We consider a class of weighted gradient methods for distributed resource allocation over a network. Each node of the network is associated with a local variable and a convex cost function; the sum of the variables (resources) across the network is fixed. Starting with a feasible allocatio ..."
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Cited by 22 (3 self)
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Abstract. We consider a class of weighted gradient methods for distributed resource allocation over a network. Each node of the network is associated with a local variable and a convex cost function; the sum of the variables (resources) across the network is fixed. Starting with a feasible allocation, each node updates its local variable in proportion to the differences between the marginal costs of itself and its neighbors. We focus on how to choose the proportional weights on the edges (scaling factors for the gradient method) to make this distributed algorithm converge and on how to make the convergence as fast as possible. We give sufficient conditions on the edge weights for the algorithm to converge monotonically to the optimal solution; these conditions have the form of a linear matrix inequality. We give some simple, explicit methods to choose the weights that satisfy these conditions. We derive a guaranteed convergence rate for the algorithm and find the weights that minimize this rate by solving a semidefinite program. Finally, we extend the main results to problems with general equality constraints and problems with block separable objective function. Key Words. Distributed optimization, resource allocations, weighted gradient methods, convergence rates, semidefinite programming. 1.
Primal and dual approaches to distributed crosslayer optimization
 in Proc. 16th IFAC World Congress
, 2005
"... Abstract: Several approaches for crosslayer design, e.g., coordinating the traditionally separated layers in wireless networks, have been proposed. However, protocols that are close to achieving the performance bounds are still lacking. We propose three distributed algorithms for joint congestion c ..."
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Cited by 10 (2 self)
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Abstract: Several approaches for crosslayer design, e.g., coordinating the traditionally separated layers in wireless networks, have been proposed. However, protocols that are close to achieving the performance bounds are still lacking. We propose three distributed algorithms for joint congestion control and resource allocation in networks with variable capacities subject to a global resource constraint. Examples include spectrum assignment in wireless networks and wavelength allocation in optical networks. For scalability, we impose the additional constraint that nodes can only negotiate and exchange resources with their neighbors. The proposed algorithms consist of two complementary approaches based on decomposition techniques, in which congestion control and resource allocations are performed on different timescales. Two of the algorithms can be shown to converge without network delays. Copyright c ○ 2005 IFAC
On Market Mechanisms as a Software Technique
, 1996
"... Market mechanisms are drawing more attention in computer science as a possible approach to difficult resource allocation problems. We broadly consider the feasibility of such an approach, with the focus on optimization, at a level accessible to a general computer science audience. The nature of mark ..."
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Cited by 9 (2 self)
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Market mechanisms are drawing more attention in computer science as a possible approach to difficult resource allocation problems. We broadly consider the feasibility of such an approach, with the focus on optimization, at a level accessible to a general computer science audience. The nature of market mechanisms is discussed from both computer science and economic perspectives Classifying definitions are motivated, then applied to marketinspired software designs reported in the literature. Potential advantages and disadvantages of the market approach are identified and explained. Supported in part by a National Science Foundation Graduate Fellowship. y Supported in part by NSF grant ASC9301788. 1 Introduction The catchphrase "market mechanism" is increasingly encountered within computer science, particularly in connection with the problems of distributed resource allocation. Recently, faced with such a problem of our own, we thought to investigate whether a market approach co...
Market Mechanisms in a Programmed System
, 1998
"... Market mechanisms evolved in a human social context where they are part of a highly effective and robust practice of distributed decision making concerning the allocation of resources and coordination of economic activity. Recently there has been more interest in applying market organization to comp ..."
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Cited by 4 (0 self)
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Market mechanisms evolved in a human social context where they are part of a highly effective and robust practice of distributed decision making concerning the allocation of resources and coordination of economic activity. Recently there has been more interest in applying market organization to computational systems. This paper defines and discusses some concepts related to the operation of markets, focusing on the role of mechanisms. A distinction is introduced between natural and programmed markets. The differences are discussed, with examples drawn from recent computer science literature. Keywords: Market Mechanism, Programmed Market, Resource Allocation, Equilibration 1. INTRODUCTION Markets have long been a feature of human culture. A farmer's produce market, a used car lot, an art auction house and a stock exchange are all familiar examples of market institutions. As information technology improves our ability to communicate rapidly and easily across great distances and make s...
1 A Decentralized SelfAdaptation Mechanism For ServiceBased Applications in The Cloud
"... Abstract—Cloud computing, with its promise of (almost) unlimited computation, storage and bandwidth, is increasingly becoming the infrastructure of choice for many organizations. As cloud offerings mature, servicebased applications need to dynamically recompose themselves, to selfadapt to changing ..."
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Cited by 3 (1 self)
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Abstract—Cloud computing, with its promise of (almost) unlimited computation, storage and bandwidth, is increasingly becoming the infrastructure of choice for many organizations. As cloud offerings mature, servicebased applications need to dynamically recompose themselves, to selfadapt to changing QoS requirements. In this paper, we present a decentralized mechanism for such selfadaptation, using marketbased heuristics. We use a continuous doubleauction to allow applications to decide which services to choose, amongst the many on offer. We view an application as a multiagent system, and the cloud as a marketplace where many such applications selfadapt. We show through a simulation study that our mechanism is effective, for the individual application as well as from the collective perspective of all applications adapting at the same time.
Multidimensional NewtonRaphson consensus for distributed convex optimization
"... Abstract — In this work we consider a multidimensional distributed optimization technique that is suitable for multiagents systems subject to limited communication connectivity. In particular, we consider a convex unconstrained additive problem, i.e. a case where the global convex unconstrained mult ..."
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Cited by 3 (2 self)
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Abstract — In this work we consider a multidimensional distributed optimization technique that is suitable for multiagents systems subject to limited communication connectivity. In particular, we consider a convex unconstrained additive problem, i.e. a case where the global convex unconstrained multidimensional cost function is given by the sum of local cost functions available only to the specific owning agents. We show how, by exploiting the separation of timescales principle, the multidimensional consensusbased strategy approximates a NewtonRaphson descent algorithm. We propose two alternative optimization strategies corresponding to approximations of the main procedure. These approximations introduce tradeoffs between the required communication bandwidth and the convergence speed/accuracy of the results. We provide analytical proofs of convergence and numerical simulations supporting the intuitions developed through the paper. Index Terms — multidimensional distributed optimization, multidimensional convex optimization, consensus algorithms, multiagent systems, NewtonRaphson methods I.
Optimal Resource Allocation in Random Networks with Transportation Bandwidths
, 808
"... Abstract. We apply statistical physics to study the task of resource allocation in random sparse networks with limited bandwidths for the transportation of resources along the links. Recursive relations from the Bethe approximation are converted into useful algorithms. Bottlenecks emerge when the ba ..."
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Cited by 1 (1 self)
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Abstract. We apply statistical physics to study the task of resource allocation in random sparse networks with limited bandwidths for the transportation of resources along the links. Recursive relations from the Bethe approximation are converted into useful algorithms. Bottlenecks emerge when the bandwidths are small, causing an increase in the fraction of idle links. For a given total bandwidth per node, the efficiency of allocation increases with the network connectivity. In the high connectivity limit, we find a phase transition at a critical bandwidth, above which clusters of balanced nodes appear, characterised by a profile of homogenized resource allocation similar to the Maxwell’s construction. Optimal Resource Allocation with Transportation Bandwidths 2 1.