Economic scheduling in Grid computing using Tender models
2007-12-17T17:00:17Z (GMT) by
Economic scheduling needs to be considered for Grid computing environment, because it gives an incentive for resource providers to supply their resources. Moreover, it enforces efficient use of resources, because the users have to pay for their use. Tendering is a suitable model for Grid scheduling because users start the negotiations for finding suitable resources for executing their jobs. Furthermore, the users specify their job requirements with their requests and therefore the resources reply with bids that are based on the cost of taking on the job and the availability of their processors. In this thesis, a framework for economic Grid scheduling using tendering is proposed. The framework entities such as users, brokers and resources employ tender/contract-net model to negotiate the prices and deadlines. The brokers’ role is acting on behalf of users. During the negotiations, the entities aim to maximise their performance which is measured by a number of metrics. In order to evaluate the entities’ performance under different scenarios, a Java- based simulator, called MICOSim, supporting event-driven simulation of economic Grid scheduling is presented. MICOSim can perform a simulation of more than one hundred entities faster than real time. It is concluded from the evaluation that users who are interested in increasing the job success rate and paying less for executing their jobs have to consider received prices to select the most appropriate bids, while users who are interested in improving the job average satisfaction rate have to consider either received completion time or both price and completion time to select the most suitable bids when the submission of jobs is static. The best broker strategy is the one that doesn’t take into account meeting the job deadlines in the bids it sends to job owners. Finally, the resource strategy that considers the price to determine if to reply to a request or not is superior to other resource strategies. The only exception is employing this strategy with price that is too low. However, there is a tiny difference between the performances of different user strategies in dynamic submission. It is also concluded from the evaluation that broker strategies have the best performance when the revenue they target from the users is reasonable. Thus, the broker’s aim has to be receiving reasonable revenue (neither too low nor too high) from acting on behalf of users. It is observed from the results that the strategy performance is influenced by the behaviour of other entities such as the submission time of user jobs. Finally, it is observed that the characteristics of entities have an effect on the performance of strategies. For example, the two user strategies that consider the received completion time and both price and completion time to determine if to accept a broker bid have similar performance, because of the existence of resources with various prices from cheap to expensive and existence of resources which don’t care about the price paid for the execution. So, the price threshold doesn’t have a large effect on the performance.