The catallaxy approach for decentralized economic-based allocation in Grid resource and service markets

Abstract

Efficient resource allocation in dynamic large-scale environments is one of the cha llenges of Grids. In centralized economic-based allocation approaches, the user requests can be matched to the fastest, cheapest or most available resource. This approach, however, shows limitations in scalability and in dynamic environments. In this paper, we explore a decentralized economic approach for resource allocation in Grid markets based on the Catallaxy paradigm. Catallactic agents discover selling nodes in the resource and service Grid markets, and negotiate with each other maximizing their utility by following a strategy. By means of simulations, we evaluate the behavior of the approach, its resource allocation efficiency and its performance with different demand loads in a number of Grid density and dynamic environments. Our results indicate that while the decentralized economic approach based on Catallaxy applied to Grid markets shows similar efficiency to a centralized system, its decentralized operation provides greater advantages: scalability to demand and offer, and robustness in dynamic environments.

Socio-economic vision graph generation and handover in distributed smart camera networks

“…This approach is realised in the AVALANCHE [Eymann 2001], and CATNET [Ardaiz et al 2006] systems, and takes inspiration from Agent-based Computational Economics (ACE) [Tesfatsion and Judd 2006], an agent-based modelling technique which attempts to replicate the dynamics of human markets with complex cognitive agents. Bargaining agents are the subject of continuing research (e.g., [Gerding and La Poutré 2006;Lopes et al 2008;Chandra et al 2010]).…”

Resource allocation in decentralised computational systems: an evolutionary market-based approach

“…-the requirement that the environment remain static while the central coordinator is calculating the optimal resource allocation, -that the coordinator has global knowledge of the system and all nodes within it, -that all coordination messages must route through the central point, counteracting the benefit from having resources distributed about the network, reducing scalability [1] and creating a fundamentally brittle system [3]. This brittleness may be mitigated against to a certain degree, with backup coordinator nodes, however even in these cases the wider system is reliant upon the existence and performance of a small number of key nodes.…”

“…This approach is taken in the AVALANCHE [21], and CATNET [3,[22][23][24] systems. These take inspiration from Agent-based Computational Economics (ACE) [53] in attempting to replicate the dynamics of human markets with complex cognitive agents.…”

“…A further important question concerning the scalability of the approach, and one that is shared with many other market-based mechanisms such as CATNET [3], is that of how knowledge of offers is disseminated around the system. In some embodiments of the model, such as networks making use of wireless technology, broadcasting may indeed be achievable.…”

“…In peer-to-peer networks, the broadcast facility may be emulated through algorithms such as flooding [47], distributed hash tables [46] or epidemic algorithms [20]. However, Ardaiz et al [3] argue quite correctly that decentralised and self-interested resource allocation approaches should prefer decentralised, incentive-compatible discovery mechanisms.…”