Pablo Chacin

Catallaxy-based Grid markets

Grid computing has recently become an important paradigm for managing computationally demanding applications, composed of a collection of services. The dynamic discovery of services, and the selection of a particular service instance providing the best value out of the discovered alternatives, poses a complex multi-attribute n:m allocation decision problem, which is often solved using a centralized resource broker. To manage complexity, this article proposes a two-layer architecture for service discovery in such Application Layer Networks (ALN). The first layer consists of a service market in which complex services are translated to a set of basic services, which are distinguished by price and availability. The second layer provides an allocation of services to appropriate resources in order to enact the specified services. This framework comprises the foundations for a later comparison of centralized and decentralized market mechanisms for allocation of services and resources in ALNs and Grids.

An architecture for incorporating decentralized economic models in application layer networks

Efficient resource discovery and allocation is one of the challenges of any large scale Application Layer Network (ALN) such as computational Grids, Content Distribution Networks and P2P applications. In centralized approaches, the user requests can easily be matched to the most convenient resource. These approaches, however, present scalability limits in the highly dynamic and complex ALN environments. This paper, explores an architecture for incorporating fully decentralized economic mechanisms for resource allocation. These mechanisms are implemented by a set of trading agents that operate on behalf of the clients and service providers, interacting over an overlay network and interfacing with the underlying resources of the platform. A prototype of the proposed architecture is presented and the practical implications of its implementation in a grid scenario are discussed.

Core Services For Grid Markets

Markets Are A Powerful Model For The Coordination Of Distributed Systems And, In Particular, In The Face Of Incomplete Information And Changing Environments. The Application Of Markets For The Resource Allocation In Grid Systems Has Recently Been Researched As An Alternative To Traditional Approaches. However, The Proper Implementation Of Sophisticated Markets Capable Of Handling Diverse Tradingmodels (Various Auctions Types, Bargaining) And Structures (Direct Negotiation, Brokering, Etc.) Requires A Set Of Supporting Services To Provide Participants A Proper Environment To Engage In Negotiations. Gridmarket Middleware (Gmm) Is A Framework That Aims To Ease The Development Of Market Based Grid Systems. In This Paper We Present Its Architecture, The Services It Provides And Describe How They Can Be Used To Implement Diverse Market Models. We Also Discuss Our Experience With The Implementation Of Prototypes For Various Core Services.

Utility driven elastic services

To address the requirements of scalability it has become a common practice to deploy large scale services over infrastructures of non-dedicated servers, multiplexing instances of multiple services at a fine grained level. This tendency has recently been popularized thanks to the utilization of virtualization technologies. As these infrastructures become more complex, large, heterogeneous ad distributed, a manual allocation of resources becomes unfeasible and some form of self-management is required. However, traditional closed loop control mechanisms seems unsuitable for this platforms. The main contribution of this paper is the proposal of an Elastic Utility Driven Overlay Network (eUDON) for dynamically scaling the number of instances of a service to ensure a target QoS objective in highly dynamic large-scale infrastructures of non-dedicated servers. This overlay combines an application provided utility function to express the services QoS, with an epidemic protocol for state information dissemination, and simple local decisions on each instance to adapt to changes in the execution conditions. These elements give the overlay robustness, flexibility, scalability and a low overhead. We show, by means of simulation experiments, that the proposed mechanisms can adapt to a diverse range of situations like flash crowds and massive failures, while maintaining the QoS objectives of the service.

Collectives: a framework for self-adaptive P2P applications

The development of a self-adaptive P2P applications faces many challenges ranging from the proper modeling of the applications behavior to the definition of the distributed algorithms required to support its functionalities and finally to its implementation in a particular platform. Collectives is a framework that addresses this issues by providing the modeling concepts and the implementation architecture required to separate the diverse adaptation concerns at the proper level of abstraction.

Integration of decentralized economic models for resource self-management in application layer networks

Resource allocation is one of the challenges for self-management of large scale distributed applications running in a dynamic and heterogeneous environment. Considering Application Layer Networks (ALN) as a general term for such applications including computational Grids, Content Distribution Networks and P2P applications, the characteristics of the ALNs and the environment preclude an efficient resource allocation by a central instance. The approach we propose integrates ideas from decentralized economic models into the architecture of a resource allocation middleware, which allows the scalability towards the participant number and the robustness in very dynamic environments. At the same time, the pursuit of the participants for their individual goals should benefit the global optimization of the application. In this work, we describe the components of this middleware architecture and introduce an ongoing prototype.

Utility Driven Service Routing over Large Scale Infrastructures

In this paper we present UDON, a novel Utility Driven Overlay Network framework for routing service requests in highly dynamic large scale shared infrastructures. UDON combines an application provided utility function to express the services’s QoS in a compact way, with an epidemic protocol to disseminate this information in a scalable and robust way. Experimental analysis with a simulation model suggests that the proposed overlay allocates requests to service instances that match their QoS requirements with a high probability and low overhead, adapting well to a wide variety of conditions.

Assessing a distributed market infrastructure for economics-based service selection

Service selection is an important issue for market-oriented Grid infrastructures. However, few results have been published on the use and evaluation of market models in deployed prototypes, making it difficult to assess their capabilities. In this paper we study the integration of an extended version of Zero Intelligence Plus (ZIP) agents in a middleware for economics-based selection of Grid services. The advantages of these agents compared to alternatives is their fairly simple messaging protocol and negotiation strategy. By deploying the middleware on several machines and running experiments we observed that services are proportionally assigned to competing traders as should be in a fair market. Furthermore, varying the environmental conditions we show that the agents are able to respond to the varying environmental constraints by adapting their market prices.

Performance measuring framework for grid market middleware

Current implementations of Grid infrastructures provide frameworks which aim at achieve on-demand computing. In such a scenario, contribution and use of resources will be governed by business models. The challenge is to provide multi-level performance information which enables the participation of the different actors in such a system. In this paper we describe the performance measuring framework developed for Grid Market Middleware, a middleware which supports economic-model based selection of service-oriented Grid applications. This middleware is a distributed infrastructure, which we have implemented for providing a market of services and resources to be assigned to Grid applications. The objectives of the performance measuring framework is first to assess the behaviour of the middleware and the used economic models in a deployed system, and secondly allow the provision of metrics for the components of the middleware itself. We describe the design of the performance measuring framework, its implementation and show its capability and usefulness for our objectives by experiments.