Computer simulations have been used more than ever before to embark on developing and understanding complex systems such as Multi-Agent Systems (MAS). MAS are complex, non-deterministic, data-centric behaviour and nature. Simulations play a key role for the designer of an agent based system to experiment and study the impact of different architectures, environment and agent behaviour. As MAS are increasingly used to solve larger and more complex problems, scalability becomes an important issue for the successful deployment. An emerging viable solution is adopting distributed simulation techniques in executing MAS models in parallel. One approach is to distribute the shared state (or environment) of a simulation model across available computing resources. Based on this approach, PDES-MAS (Parallel and Discrete Event Simulations for Multi-Agent System) framework is designed to execute large scale models such as MAS. It adopts PDES techniques to distribute and run parallel simulation of Multi-Agent Systems (MAS). Several challenges arise on executing MAS models on a distributed environment, of which one issue that requires focus is data access. Accessing data efficiently in a latency-sensitive and large scale network overlay is a vital requirement for the scalability of the system. Following PDES paradigm, it is also very important that events (accessing shared state) in a parallel and discrete event simulation system are processed in a non decreasing (logical) time stamp order. So, this thesis presents a notion of logical time synchronised range queries to access data and in particular within the PDES-MAS framework. To localise data access, this thesis also provides mechanisms to distribute shared state in an adaptive manner such that the distribution reflects access patterns of simulating nodes. The algorithms are evaluated within the implementation of PDES-MAS framework using various agent based simulation traces. ACKNOWLEDGEMENTS