Financial Market Models for the Grid

The existing network of computing devices around the world created by the Internet gives the possibility of establishing a global market for computing power, where anybody connected to this network can acquire computing power or sell his own spare computing resources in exchange for real money. This potential global market for computing power, which does not exist yet, is what we study in this thesis. Specifically, we study the market with both analytic and simulated models. This thesis predicts how a future global market for Grid computing will behave. We give arguments that such a large market, together with its potential indefinite growth, would not be able to scale if it were organized with a central server, and therefore we study a peer-to-peer market model in our simulations. We create a high-level model with the most relevant characteristics of the market, where buyers and sellers trade a single commodity. In our simulations, the parameters of the volume of contracts, proportion of satisfied agents and number of messages in the network achieve stable values in the long run. We also derive analytically the conditions that make the price get stable over time; we then implement these conditions in the simulation as local mechanisms of the market participants, which make the whole system achieve a stable price evolution. We are also confident that, as soon as the Grid market emerges, a parallel market of derivatives will be created as well. This market of derivatives will be important due to the non-storability nature of computing power. We develop a futures market for computing power based on Markov chains, where we initially model the behaviour of each participant with a particular Markov chain, and then we derive a global transition probability matrix that models the market as a whole. Furthermore, we analyse the performance of a futures trader operating in such a market, and we obtain an optimal trading strategy with the use of Markov Decision Processes. We finally develop a stochastic differential equation model that captures the essence of the spot price evolution of computing power observed in our market simulations. This model is based on a previously one proposed for the electricity market, and consists of the use of a Markov regime-switching mechanism in order to model the existence of spikes in the spot price. We then estimate the parameters in the model with the output data of our simulation program; the estimation is carried out both by maximum likelihood and the generalised method of moments

Negotiated resource brokering for quality of service provision of grid applications

Grid Computing is a distributed computing paradigm where many computers often formed from different organisations work together so that their computing power may be aggregated. Grids are often heterogeneous and resources vary significantly in CPU power, available RAM, disk space, OS, architecture and installed software etc. Added to this lack of uniformity is that best effort services are usually offered, as opposed to services that offer guarantees upon completion time via the use of Service Level Agreements (SLAs). The lack of guarantees means the uptake of Grids is stifled. The challenge tackled here is to add such guarantees, thus ensuring users are more willing to use the Grid given an obvious reluctance to pay or contribute, if the quality of the services returned lacks any guarantees. Grids resources are also finite in nature, hence priorities need establishing in order to best meet any guarantees placed upon the limited resources available. An economic approach is hence adopted to ensure end users reveal their true priorities for jobs, whilst also adding incentive for provisioning services, via a service charge. An economically oriented model is therefore proposed that provides SLAs with bicriteria constraints upon time and cost. This model is tested via discrete event simulation and a simulator is presented that is capable of testing the model. An architecture is then established that was developed to utilise the economic model for negotiating SLAs. Finally experimentation is reported upon from the use of the software developed when it was deployed upon a testbed, including admission control and steering of jobs within the Grid. Results are presented that show the interactions and relationship between the time and cost constraints within the model, including transitions between the dominance of one constraint over the other and other things such as the effects of rescheduling upon the market