Skip to Main Content
Understanding and modeling resources of Internet end hosts are essential for the design of desktop software and Internet-distributed applications. In this paper, we develop a correlated resource model of Internet end hosts based on real-trace data taken from several volunteer computing projects, including SETI@home. This data cover a five-year period with statistics for 6.7 million hosts. Our resource model is based on statistical analysis of host computational power, memory, and storage as well as how these resources change over time and the correlations among them. We find that resources with few discrete values (core count, memory) are well modeled by approximations governing the change of relative resource quantities over time. Resources with a continuous range of values are well modeled by correlated log-normal distributions (cache, processor speed, and available disk space). We validate and show the utility of the model by applying it to a resource allocation problem for Internet-distributed applications, and compare it to other models. We also make our trace data and tool for automatically generating realistic Internet end hosts publicly available.