We consider flooding-based resource discovery in distributed systems. With flooding, a node searching for a resource contacts its neighbors in the network, which in turn contact their own neighbors and so on until a node possessing the requested resource is located. Flooding assumes no knowledge about the network topology or the resource distribution thus offering an attractive means for resource discovery in dynamically evolving networks such as peer-to-peer systems. We provide analytical results for the performance of a number of flooding-based approaches that differ in the set of neighbors contacted at each step. The performance metrics we are interested in are the probability of locating a resource and the average number of steps and messages for doing so. We study both uniformly random resource requests and requests in the presence of popular (hot) resources. Our analysis is also extended to take into account the fact that nodes may become unavailable either due to failures or voluntary departures from the system. Our analytical results are validated through simulation.
Fog computing is an emerging and evolving technology, which bridges the cloud with the network edges, allowing computing to work in a decentralized manner. As such, it introduces a number of complex issues to the research community and the industry alike. Both of them have to deal with many open challenges including architecture standardization, resource management and placement, service management, Quality of Service (QoS), communication, participation, to name a few. In this work, we provide a comprehensive literature review along two axes—modeling with an emphasis in the proposed fog computing architectures and simulation which investigates the simulation tools which can be used to develop and evaluate novel fog-related ideas.
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