In this paper we introduce Challenger, a multiagent system that performs completely distributed resource allocation. Challenger consists of agents which individually manage local resources; these agents communicate with one another to share their resources (in this particular instance, CPU time

this article, we first confine our attention to this particular problem and develop a suite of efficient and fault-tolerant algorithms for it. Later, we consider other process synchronization problems in distributed systems and solve them through transformations based on the these algorithms. Some

In distributed resource allocation a set of agents must assign their resources to a set of dynamic tasks. This problem arises in many real-world domains like the one described in this paper: distributed sensor networks. Despite the variety of approaches proposed for distributed resource

this paper, we discuss a resource allocation problem in distributed systems. Consider a distributed system consisting of a set of processes and a set of resources of identical type

and efficiency of pure Nash equilibria. In this paper we explore the relationship between the Shapley value utility design and the resulting efficiency of both pure Nash equilibria and coarse correlated equilibria. To study this relationship we introduce a simple class of resource allocation problems. Within

In this paper, we present a simple distributed algorithm for resource allocation which simul-taneously approximates the optimum value for a large class of objective functions. In particular, we consider the class of canonical utility functions U that are symmetric, non-decreasing, con

Abstract — We investigate the resource allocation problem for large-scale server clusters with quality-of-service objectives, where key functions are decentralized. Specifically, the optimal service selection is posed as a discrete utility maximization problem that reflects management objectives

In distributed resource allocation a set of agents must assign their resources to a set of dynamic tasks. This problem arises in many real-world domains like the one described in this paper: distributed sensor networks. Despite the variety of approaches proposed for distributed resource allocation

possibilities whereas many applicationsarebasedonthem. For instance, inpeer-to-peer networks,apeercanonly communicate with a small subset of the systems. In this thesis, we focus on distributed methods to solve resource allocationproblems. Initial allocation evolves step by step thanks to local agent

such a system after processing at multiple processing units. Based on this framework, we develop distributed algorithms for finding the best resource allocation schemes in such data stream processing networks. Performance analysis on the optimality and complexity of these algo-rithms are also provided.