Correlated Resource Models of Internet End Hosts

Understanding and modelling resources of Internet end hosts is 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 the SETI@home project. This data covers a 5-year period with statistics for 2.7 million hosts. The 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 between them. We find that resources with few discrete values (core count, memory) are well modeled by exponential laws governing the change of relative resource quantities over time. Resources with a continuous range of values are well modeled with either correlated normal distributions (processor speed for integer operations and floating point operations) or log-normal distributions (available disk space). We validate and show the utility of the models by applying them to a resource allocation problem for Internet-distributed applications, and demonstrate their value over other models. We also make our trace data and tool for automatically generating realistic Internet end hosts publicly available

Correlated resource models of internet end hosts

Abstract-Understanding and modeling resources of Internet end hosts is essential for the design of desktop software and Internetdistributed 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 covers a 5-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 wellmodeled 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

Chronic microsensors for longitudinal, subsecond dopamine detection in behaving animals

Neurotransmission operates on a millisecond timescale but is changed by normal experience or neuropathology over days to months. Despite the importance of long-term neurotransmitter dynamics, no technique exists to track these changes in a subject from day to day over extended periods of time. Here we describe and characterize a microsensor that can detect the neurotransmitter dopamine with subsecond temporal resolution over months in vivo in rats and mice