The accelerated development in Peer-to-Peer (P2P) and Grid computing has positioned them as promising next generation computing platforms. They enable the creation of Virtual Enterprises (VE) for sharing resources distributed across the world. However, resource management, application development and usage models in these environments is a complex undertaking. This is due to the geographic distribution of resources that are owned by different organizations or peers. The resource owners of each of these resources have different usage or access policies and cost models, and varying loads and availability. In order to address complex resource management issues, we have proposed a computational economy framework for resource allocation and for regulating supply and demand in Grid computing environments. This framework provides mechanisms for optimizing resource provider and consumer objective functions through trading and brokering services. In a real world market, there exist various economic models for setting the price of services based on supply-and-demand and their value to the user. They include commodity market, posted price, tender and auction models. In this paper, we discuss the use of these models for interaction between Grid components to decide resource service value, and the necessary infrastructure to realize each model. In addition to usual services offered by Grid computing systems, we need an infrastructure to support interaction protocols, allocation mechanisms, currency, secure banking, and enforcement services. We briefly discuss existing technologies that provide some of these services and show their usage in developing the Nimrod-G grid resource broker. Furthermore, we demonstrate the effectiveness of some of the economic models in re...

Computational Grids are a promising platform for executing large-scale resource intensive applications. However, resource management and scheduling in the Grid environment is a complex undertaking as resources are (geographically) distributed, heterogeneous in nature, owned by different individuals or organizations with their own policies, have differen t access and cost models, and have dynamically varying loads and availability. This introduces a number of challenging issues such as site autonomy, heterogeneous interaction, policy extensibility, resource allocation or coallocation, online control, scalability, transparency, resource brokering, and "computational economy". A number of Grid systems (such as Globus and Legion) have addressed many of these issues with exception of a computational economy. We argue that a computational economy is required in order to create a real world scalable Grid because it provides a mechanism for regulating the Grid resources demand and supply....

This chapter identifies challenges in managing resources in a Grid computing environment and proposes computational economy as a metaphor for effective management of resources and application scheduling. It identifies distributed resource management challenges and requirements of economybased Grid systems, and discusses various representative economy-based systems, both historical and emerging, for cooperative and competitive trading of resources such as CPU cycles, storage, and network bandwidth. It presents an extensible, service-oriented Grid architecture driven by Grid economy and an approach for its realization by leveraging various existing Grid technologies. It also presents commodity and auction models for resource allocation. The use of commodity economy model for resource management and application scheduling in both computational and data grids is also presented.

In utility-driven cluster computing, cluster systems need to know the specific needs of different users so as to allocate resources according to their needs. They are also vital in supporting service-oriented Grid computing that harness resources distributed worldwide based on users' objectives. Market-based resource management systems make use of real-world market concepts and behavior to assign resources to users. This paper outlines a taxonomy that describes how market-based resource management systems can support utility-driven cluster computing. The taxonomy is used to survey existing market-based resource management systems to better understand how they can be utilized.

A mobile agent is an executing program that can migrate, at times of its own choosing, from machine to machine in a heterogeneous network. On each machine, the agent interacts with stationary service agents and other resources to accomplish its task. In this chapter, we first make the case for mobile agents, discussing six strengths of mobile agents and the applications that benefit from these strengths. Although none of these strengths are unique to mobile agents, no competing technique shares all six. In other words, a mobile-agent system provides a single general framework in which a wide range of distributed applications can be implemented eciently and easily. We then present a representative cross-section of current mobile-agent systems. 1 Introduction A mobile agent is an executing program that can migrate, at times of its own choosing, from machine to machine in a heterogeneous network. On each machine, the agent interacts with stationary service agents and other resource...

Accessing remote data anywhere and at anytime constitutes an important advantage in many business environments. However, when working with mobile devices, users face many problems related to: (1) device restrictions: mobile devices are resource-constrained, more vulnerable and fragile than stationary devices (devise exposure problems) and, (2) the communication media: wireless communications are often unstable, asymmetric and expensive (media problems). To alleviate these problems, we present a service, the Lockers Rent Service, for keeping the data of mobile users in a secure and safe space in a proxy at the xed network, thus providing a solution to the device exposure problems.

How free are our software agents to take the best possible care of our interests? How free can we make them? In what sense and to what extent do currently proposed mechanisms and agent behaviors consider self-interest? What current research addresses these issues? What needs to be done? We address these issues in the context of electronic markets, such as consumer goods markets and (future, more fine-grained) markets for electric power or communication bandwidth. Electronic markets and self-interested agents The notion of a self-interested software agent is well established in the agent community. Although this notion of agenthood is widely applicable, it is perhaps most obviously useful in the context of electronic markets, where it coincides with the rational, utility maximizing, agent of microeconomic theory (see, e.g., [1]). Through automated trading by software agents, we expect improvements in the quality of existing markets, such as consumer goods markets, and to reap t...

The possibility of accessing and/or receiving local or remote data anywhere and at anytime constitutes an important advantage in many business environments. However, when working with mobile devices, users face many problems, such as: (1) devise exposure problems – mobile devices are more vulnerable and fragile than stationary devices, because they can be easily stolen, lost or damaged, (2) media problems – wireless communications are often unstable, asymmetric and expensive, and (3) availability problems – mobile devices stay disconnected for long periods of time. To alleviate these problems, we present a service, Data Lockers, which offers to its users first, the possibility of keeping their data in a secure and safe space in a proxy, thus alleviating the device exposure problem. Next, data stored in a data locker are available even when the mobile device is disconnected, thus providing a solution to the availability problem. Finally, specific tasks are carried out at the fixed network on behalf of the mobile user, in this way relieving the media problem. The architecture of the Locker Rental Service is based on mobile agents. These agents, and the locker, stay always close to the location of the user, traveling to meet the user wherever the user moves, therefore, allowing users to use anywhere-anytime, ubiquitous persistent storage space located at the fixed network.

Abstract. Peer-to-Peer (P2P) computing is widely recognized as a promising paradigm for building next generation distributed applications. However, the autonomous, heterogeneous, and decentralized nature of participating peers introduces the following challenge for resource sharing: how to make peers profitable in the untrusted P2P environment? To address the problem, we present a self-policing and distributed approach by combining two models: PET, a personalized trust model, and M-CUBE, a multiple-currency based economic model, to lay a foundation for resource sharing in untrusted P2P computing environments. PET is a flexible trust model that can adapt to different requirements, and provides the solid support for the currency management in M-CUBE. M-CUBE provides a novel self-policing and quality-aware framework for the sharing of multiple resources, including both homogeneous and heterogeneous resources. We evaluate the efficacy and performance of this approach in the context of a real application, a peer-to-peer Web server sharing. Our results show that our approach is flexible enough to adapt to different situations and effective to make the system profitable, especially for systems with large scale.

Although mobile computers are becoming more and more powerful, the intrinsic features of wireless communications - poor quality, limited bandwidth, continuous disconnections, expensive communications - still limit the performance delivered to mobile users. In this paper, we present the Locker Rent Service that allows mobile users to rent a dedicated disk space, located in the fixed network, where they can store and access their data. Besides increasing the storage capacity of mobile devices, the Locker Rent Service offers to mobile users data protection, battery power savings and various communications optimizations. The service is supported by a middleware architecture that incorporates this and other services with the general goal of increasing mobile computers capabilities and performance. The architecture is based on mobile agents and offers flexibility and adaptability with a low overhead as shown by our preliminary performance results. 1. Introduction In the past few years, the...