Abstract-In the context of the 'selfish-mine' strategy proposed by Eyal and Sirer, we study the effect of propagation delay on the evolution of the Bitcoin blockchain. First, we use a simplified Markov model that tracks the contrasting states of belief about the blockchain of a small pool of miners and the 'rest of the community' to establish that the use of block-hiding strategies, such as selfish-mine, causes the rate of production of orphan blocks to increase. Then we use a spatial Poisson process model to study values of Eyal and Sirer's parameter γ, which denotes the proportion of the honest community that mine on a previously-secret block released by the pool in response to the mining of a block by the honest community. Finally, we use discrete-event simulation to study the behaviour of a network of Bitcoin miners, a proportion of which is colluding in using the selfish-mine strategy, under the assumption that there is a propagation delay in the communication of information between miners.
This review paper focusses on DESMO-J, a comprehensive and stable Java-based open-source simulation library. DESMO-J is recommended in numerous academic publications for implementing discrete event simulation models for various applications. The library was integrated into several commercial software products. DESMO-J's functional range and usability is continuously improved by the Department of Informatics of the University of Hamburg (Germany). The paper summarizes DESMO-J's core functionality and important design decisions. It also compares DESMO-J to other discrete event simulation frameworks. Furthermore, latest developments and new opportunities are addressed in more detail. These include a) improvements relating to the quality and applicability of the software itself, e.g. a port to .NET, b) optional extension packages like visualization libraries and c) new components facilitating a more powerful and flexible simulation logic, like adaption to real time or a compact representation of production chains and similar queuing systems. Finally, the paper exemplarily describes how to apply DESMO-J to harbor logistics and business process modeling, thus providing insights into DESMO-J practice.
Ad hoc networks are self-configuring networks of mobile nodes, connected by wireless links. Suppose each mobile node can make observations within a circular area of radius r obs centred on its own location. The area coverage of the network is defined as the total area observed by the mobile nodes. We investigate a distributed scalable method based on local interactions with minimal sensing and low computational cost whereby the nodes move autonomously (self-deployment) in order to maximise the coverage of the network, while at the same time ensuring that the mobile nodes do not move so far away from each other (thus trivially maximising the coverage) that they become disconnected. Certain nodes may be instructed to move to specified locations. These guide nodes induce a correlated movement of groups of nodes which follow the guide nodes and establish maximal coverage in the specified locations. Simulation results demonstrate the coverage achieved by a group of 100 nodes when moving on an unbounded plane (optional guide nodes induce a collective motion to areas of interest) and when moving on a bounded plane with barriers or hills.
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