Accurate and Efficient Measurements of IP level Performance to Drive Interface Selection in Heterogeneous Wireless Networks

TL;DR

This paper introduces accurate, efficient IP-level performance measurement techniques for interface selection in heterogeneous wireless networks, emphasizing kernel-based methods for scalability and low CPU usage.

Contribution

It proposes and evaluates kernel-based mechanisms for IP connectivity and performance monitoring, improving accuracy and efficiency over application-level methods.

Findings

Kernel implementation reduces CPU usage significantly.

Performance monitoring scales to thousands of flows.

Guidelines for parameter tuning are provided.

Abstract

Optimal interface selection is a key mobility management issue in heterogeneous wireless networks. Measuring the physical or link level performance on a given wireless access networks does not provide a reliable indication of the IP connectivity, delay and loss on the (bidirectional) paths from the Mobile Host to the node that is handling the mobility, over different heterogeneous networks. In this paper, we propose, implement and analyze mechanisms for connectivity check and performance (network delay and packet loss) monitoring over IP access networks. We evaluate the accuracy and timeliness of the performance estimates and provide guidelines for tuning up the parameters. From the implementation perspective, we show that using application level measurements is highly CPU intensive, while a kernel based implementation has comparably a very low CPU usage. The Linux kernel implementation results in an efficient use of batteries in Mobile Hosts and intermediate Mobility Management Nodes can scale up to monitoring thousands of flows. The proposed solutions have been implemented in the context of a specific mobility management solution, but the results are of general applicability. The Linux implementation is available as Open Source.