Passive Identification of Under-Utilized CPUs in High Performance Cluster Grid Networks

In this paper we propose a passive approach to using network traffic to discover the availability of resources in local distributed networks (e.g., cluster grids, campus desktop grids, etc.). To our knowledge, this is the first approach of its kind. The ability to quickly identify resource availability is critical because the presence of available resources directly affects the job execution time of a distributed environment. The proposed method creates a delay sensitive profile generated by the analysis of monitored network traffic, which emulates high performance UDP based grid services such as file transfer applications (FOBS, Tsunami, UDT, SABUL, etc.), message passing platforms (MPICHG2/Score, etc.), and others. An energy value is derived from the delay sensitive profile, which represents the state (over-utilized CPU or under-utilized CPU) of the resource of interest. Then a simple threshold (derived from initial calibrations on the over-utilized resources.) is applied to the energy value to identify the state of the resource. This method could be used to enhance existing resource discovery algorithms used in local distributed networks because this approach is capable of passively determining a major dynamic resource attribute - CPU utilization. The main benefits are the reduction in the necessary complexity associated with the use of non-passive algorithms (e.g., flooding algorithm, name-dropper algorithm, distinctive awareness algorithm, etc.) and the reduction in the extra network traffic that results from the continual need to determine the availability of dynamic resources. Since this method is passive in nature, there is no need to query potential resources directly to determine their availability to complete distributed computing related jobs. Results suggest that once the CPU utilization approaches 70% (unavailable) the network traffic produced by that node exhibits different behavior than when the CPU utilization is less than 70% (available).