The main purpose of mutual exclusion in a distributed environment is to control access to a shared resource. Large-scale distributed systems such as clouds or grids provide shared informatics resources to its clients. In this type of environment, Service Level Agreement (SLA) allows for the definition of a type of quality of service (QoS) between a resource provider and a client. This means that some constraints like priority, response time or reliability must be taken into consideration to maintain a good QoS. Permission-based algorithms are costly in messages, not easily extensible and naturally more robust, pertaining to failures when compared to token algorithms. In this paper, we propose two mutual exclusion algorithms, integrating priority and time constraints for each request, via deadline and execution time in the critical section, with the aim of ensuring a proper service quality. The proposed algorithms are based on a logical structure of nodes in complete binary trees. The algorithms named PBDMEAQoSα and PBDMEAQoSβ are SLA (Service Level Agreement) based. They integrate priority dynamics, which cumulates with the age of a request. PBDMEAQoSα requires 3log2N messages per access to critical section and a synchronization delay of 2log2N for a set of N nodes competing for the critical resource. PBDMEAQoSβ requires 2log2N messages per access to critical section and a synchronization delay of log2N.
26 June 2023 in Proceedings of the AAAI Conference on Artificial Intelligence
Agent-based modeling and simulation can provide a powerful test environment for crisis management scenarios. Human agent interaction has limitations in representing norms issued by an agent to a human agent that has emotions. In this study, we present an approach to the interaction between a virtual normative agent and a human agent in an evacuation scenario. Through simulation comparisons, it is shown that the method used in this study can more fully simulate the real-life out come of an emergency situation and also improves the au thenticity of the agent interaction.