Simulation Environment

We simulated both approaches for a sample scenario of people wanting to share and discuss a presentation over an ad hoc network and browse the web over the infrastructure network at the same time. This feature is extremely useful in many scenarios. For example, consider the case where Kisco's employees conduct a business meeting with Macrosoft's employees at Macrosoft's headquarters. With MultiNet and a single wireless network card, Kisco employees can share documents, presentations, and data with Macrosoft's employees over an ad hoc network. Macrosoft's employees can stay connected to their internal network via the access point infrastructure while sharing electronic information with Kisco's employees. Macrosoft does not have to give Kisco employees access in their internal network in order for the two parties to communicate.

We model traffic over the two networks, and analyze the packet trace using our simulator. Traffic over the infrastructure network is considered to be mostly web browsing. We used Surge[5] to model http requests according to the behavior of an Internet user. Surge is a tool that generates web requests with statistical properties similar to measured Internet data. The generated sequence of URL requests exhibit representative distributions for requested document size, temporal locality, spatial locality, user off times, document popularity and embedded document count. For our purposes, Surge was used to generate a web trace for a 1 hour 50 minute duration, and this web trace was then broken down to a sample packet trace for this period. The distribution of the packet sizes over the infrastructure network is illustrated in Figure6.

Figure 6: Packet trace for the web browsing application over the infrastructure network

The ad hoc network is used for two purposes: sharing a presentation, and supporting discussions using a sample chat application. Three presentations are shared in our application over a 1 hour 50 minute period. Each presentation is a 2 MB file, and is downloaded to the target machine using an FTP session over the ad hoc network. They are downloaded in the 1st minute, the 38th minute, and the 75th minute. Further, the user also chats continuously with other people in the presentation room, discussing the presentation and other relevant topics. Packet traces for both the applications, FTP and chat, were obtained by sniffing the network, using Ethereal[2], while running the respective applications. MSN messenger was used for a sample chat trace for a 30 minute duration. The Packet traces for FTP and chat were then extended over the duration of our application, and are illustrated in Figure 7.

In our simulations we assume that wireless networks operate at their maximum TCP throughput of 4.4 and 5.8 Mbps for an ad hoc and infrastructure network respectively. We then analyze the packet traces for independent networks, and generate another trace for MultiNet. We use a `75%IS 25%AH' switching strategy presented in Section 7.3 with a switching cycle time of 400ms. The switching delay is set to 1 ms, and we explain the reason for choosing this value in Section 8.1. Further, the power consumed when switching is assumed to be negligible. We do not expect these simplifying assumptions to greatly affect the results of our experiments. We analyze packet traces for the two radio and MultiNet case and compute the total power consumed and the average delay encountered by the packets. All the cards are assumed to be Cisco AIR-PCM350, and their corresponding power consumption numbers are used from [14]. Specifically, the card consumes 45 mW of power in sleep mode, 1.08W in idle mode, 1.3W in receive mode, and 1.875W in transmit mode. Further, in PSM, the energy consumed by the Cisco AIR-PCM 350 in one power save cycle is given by: $0.045*n*t + 24200$ milliJoules, where $n$ is the Listen Interval and $t$ is the Beacon Period of the AP. The details of these numbers are presented in [14].