Abstract-In this paper a passive methodology for TCP performance evaluation over General Packet Radio Service (GPRS) networks is presented that relies on traffic monitoring at the GPRS ingress/egress router interface (Gi). Based on the IP and TCP headers of the packets we estimate the end-to-end performance of TCP connections such as connection setup behavior and data transfer goodput. In order to identify the effects behind the measured performance the introduced algorithms estimate round trip delays, packet loss ratios, available channel rates, throughput and carry out bottleneck analysis. Large-scale GPRS measurements in seven countries are presented to analyze TCP performance and demonstrate the applicability of the method. The effects of different TCP parameters such as maximum segment size, selective acknowledgements, timestamp usage and receiver window size are also quantified. GPRS measurement results are compared to a wireline dial-up network to identify the effects specific to the wireless environment.

Modern enterprise networks are of sufficient complexity that even simple faults can be difficult to diagnose -let alone transient outages or service degradations. Nowhere is this problem more apparent than in the 802.11-based wireless access networks now ubiquitous in the enterprise. In addition to the myriad complexities of the wired network, wireless networks face the additional challenges of shared spectrum, user mobility and authentication management. Not surprisingly, few organizations have the expertise, data or tools to decompose the underlying problems and interactions responsible for transient outages or performance degradations. In this paper, we present a set of analysis techniques and models to precisely determine all sources of data transfer delay due to media access and mobility in 802.11 networks -from the physical layer to the transport layer -as well as the interactions among them. While some sources of delay can be directly measured, many of the delay components, such as AP queuing, backoffs, contention, etc., must be inferred. To infer these delays from measurements, we develop a detailed model of MAC protocol behavior, both as it is described in the 802.11 specification as well as how it is implemented in vendor hardware. Combined with comprehensive traces of wireless activity taken from an enterprise network, we produce a complete delay breakdown for packet transmissions and pinpoint problems that constrain connectivity or limit performance.

No abstract

The combination of unlicensed spectrum, cheap wireless interfaces and the inherent convenience of untethered computing have made 802.11-based networks ubiquitous in the enterprise. Modern universities, corporate campuses and government offices routinely deploy scores of access points to blanket their sites with wireless Internet access. However, while the fine-grained behavior of the 802.11 protocol itself has been well studied, our understanding of how large 802.11 networks behave in their full empirical complexity is surprisingly limited. In this paper, we present a system called Jigsaw that uses multiple monitors to provide a single unified view of all physical, link, network and transport-layer activity on an 802.11 network. To drive this analysis, we have deployed an infrastructure of over 150 radio monitors that simultaneously capture all 802.11b and 802.11g activity in a large university building (1M+ cubic feet). We describe the challenges posed by both the scale and ambiguity inherent in such an architecture, and explain the algorithms and inference techniques we developed to address them. Finally, using a 24-hour distributed trace containing more than 1.5 billion events, we use Jigsaw's global cross-layer viewpoint to isolate performance artifacts, both explicit, such as management inefficiencies, and implicit, such as co-channel interference. We believe this is the first analysis combining this scale and level of detail for a production 802.11 network.

Modern enterprise networks are of sufficient complexity that even simple faults can be difficult to diagnose -let alone transient outages or service degradations. Nowhere is this problem more apparent than in the 802.11-based wireless access networks now ubiquitous in the enterprise. In addition to the myriad complexities of the wired network, wireless networks face the additional challenges of shared spectrum, user mobility and authentication management. Not surprisingly, few organizations have the expertise, data or tools to decompose the underlying problems and interactions responsible for transient outages or performance degradations. In this paper, we present a set of analysis techniques and models to precisely determine all sources of data transfer delay due to media access and mobility in 802.11 networks -from the physical layer to the transport layer -as well as the interactions among them. While some sources of delay can be directly measured, many of the delay components, such as AP queuing, backoffs, contention, etc., must be inferred. To infer these delays from measurements, we develop a detailed model of MAC protocol behavior, both as it is described in the 802.11 specification as well as how it is implemented in vendor hardware. Combined with comprehensive traces of wireless activity taken from an enterprise network, we produce a complete delay breakdown for packet transmissions and pinpoint problems that constrain connectivity or limit performance.