This survey characterizes an emerging research area, sometimes called coordination theory, that focuses on the interdisciplinary study of coordination. Research in this area uses and extends ideas about coordination from disciplines such as computer science, organization theory, operations research, economics, linguistics, and psychology. A key insight of the framework presented here is that coordination can be seen as the process of managing dependencies among activities. Further progress, therefore, should be possible by characterizing different kinds of dependencies and identifying the coordination processes that can be used to manage them. A variety of processes are analyzed from this perspective, and commonalities across disciplines are identified. Processes analyzed include those for managing shared resources, producer/consumer relationships, simultaneity constraints, and tank/subtask dependencies. Section 3 summarizes ways of applying a coordination perspective in three different domains: (1) understanding the effects of information technology on human organizations and markets, (2) designing cooperative work tools, and (3) designing distributed and parallel computer systems. In the final section, elements of a research

Market price systems constitute a well-understood class of mechanisms that under certain conditions provide effective decentralization of decision making with minimal communication overhead. In a market-oriented programming approach to distributed problem solving, we derive the activities and resource allocations for a set of computational agents by computing the competitive equilibrium of an artificial economy. Walras provides basic constructs for defining computational market structures, and protocols for deriving their corresponding price equilibria. In a particular realization of this approach for a form of multicommodity flow problem, we see that careful construction of the decision process according to economic principles can lead to efficient distributed resource allocation, and that the behavior of the system can be meaningfully analyzed in economic terms. 1. Distributed Planning and Economics In a distributed or multiagent planning system, the plan for the system as a whole i...

We investigate cost-sharing algorithms for multicast transmission. Economic considerations point to two distinct mechanisms, marginal cost and Shapley value, as the two solutions most appropriate in this context. We prove that the former has a natural algorithm that uses only two messages per link of the multicast tree, while we give evidence that the latter requires a quadratic total number of messages. We also show that the welfare value achieved by an optimal multicast tree is NP-hard to approximate within any constant factor, even for bounded-degree networks. The lower-bound proof for the Shapley value uses a novel algebraic technique for bounding from below the number of messages exchanged in a distributed computation; this technique may prove useful in other contexts as well. 1

Distributed Algorithmic Mechanism Design (DAMD) combines theoretical computer science's traditional focus on computational tractability with its more recent interest in incentive compatibility and distributed computing. The Internet's decentralized nature, in which distributed computation and autonomous agents prevail, makes DAMD a very natural approach for many Internet problems. This paper first outlines the basics of DAMD and then reviews previous DAMD results on multicast cost sharing and interdomain routing. The remainder of the paper describes several promising research directions and poses some specific open problems.

With the advances in computer and networking technology, thousands of heterogeneous com-puters can be interconnected to provide a large collection of computing and communication resources. These systems are used by agrowing and increasingly heterogeneous set of users.

Many new database applications require very large volumes of data. Mariposa is a data base system under construction at Berkeley responding to this need. Mariposa objects can be stored over thousands of autonomous sites and on memory hierarchies with very large capacity. This scale of the system leads to complex query execution and storage management issues, unsolvable in practice with traditional techniques. We propose an economic paradigm as the solution. A query receives a budget which itspends to obtain the answers. Each site attempts to maximize income by buying and selling storage objects, and processing queries for locally stored objects. We present the protocols which underlie the Mariposa economy. 1.

We formulate and solve a problem of allocating resources among competing services differentiated by user traffic characteristics and maximum end-to-end delay. The solution leads to an alternative approach to service provisioning in an ATM network, in which the network offers directly for rent its bandwidth and buffers and users purchase freely resources to meet their desired quality. Users make their decisions based on their own traffic parameters and delay requirements and the network sets prices for those resources. The procedure is iterative in that the network periodically adjusts prices based on monitored user demand, and is decentralized in that only local information is needed for individual users to determine resource requests. We derive network's adjustment scheme and users' decision rule and establish their optimality. Since our approach does not require the network to know user traffic and delay parameters, it does not require traffic policing on the part of the network. 1 I...

This paper focuses on load management in looselycoupled federated distributed systems. We present a distributed mechanism for moving load between autonomous participants using bilateral contracts that are negotiated offline and that set bounded prices for moving load. We show that our mechanism has good incentive properties, efficiently redistributes excess load, and has a low overhead in practice.

In this paper, we propose a new methodology based on economic models to provide Quality of Service (QoS) guarantees to competing traffic classes (classes of sessions) in packet networks. We consider an economic model of a packet network where resources are priced. Traffic classes compete for network resources and they purchase them to satisfy their QoS needs. Our contributions are the following: 1) We provide a new definition for QoS provisioning based on economic models (Pareto efficiency). 2) We obtain the set of optimal resource allocations (Pareto optimal) which provide QoS guarantees to competing traffic classes. 3) We show the impact on equilibrium prices and optimal allocations due to traffic load and variability, and QoS requirements. 4) We propose packet scheduling and admission policies to provide QoS guarantees to traffic classes based on available QoS and prices in the network.

This paper presents a precise market model for a well-defined class of distributed configuration design problems. Given a design problem, the model defines a computational economy to allocate basic resources to agents participating in the design. The result of running these "design economies" constitutes the market solution to the original problem. After defining the configuration design framework, I describe the mapping to computational economies and our results to date. For some simple examples, the system can produce good designs relatively quickly. However, analysis shows that the design economies are not guaranteed to find optimal designs, and we identify and discuss some of the major pitfalls. Despite known shortcomings and limited explorations thus far, the market model offers a useful conceptual viewpoint for analyzing distributed design problems.