Rate Adaptation in Congested Wireless Networks through Real-Time Measurements

Abstract

Rate adaptation is a critical component that impacts the performance of IEEE 802.11 wireless networks. In congested networks, traditional rate adaptation algorithms have been shown to choose lower data-rates for packet transmissions, leading to reduced total network throughput and capacity. A primary reason for this behavior is the lack of real-time congestion measurement techniques that can assist in the identification of congestion related packet losses in a wireless network. In this work, we first propose two real-time congestion measurement techniques, namely an active probe-based method called Channel Access Delay, and a passive method called Channel Busy Time. We evaluate the two techniques in a testbed network and a large WLAN connected to the Internet. We then present the design and evaluation of Wireless cOngestion Optimized Fallback (WOOF), a rate adaptation scheme that uses congestion measurement to identify congestion related packet losses. Through simulation and testbed implementation we show that, compared to other well-known rate adaptation algorithms, WOOF achieves up to 300% throughput improvement in congested networks.

Joint Transmission Rate, Power, and Carrier Sense Settings: An Initial Measurement Study

“…While some of the features that we describe are IEEE 802.11a specific, most of the discussion applies to IEEE 802.11 in general. We base our discussion mainly on empirical evidence gathered through experiments in our testbed, related work [10], [8], [7], [13], [14], [12] In IEEE 802.11 networks, each packet contains a preamble, which is used for packet detection (also referred as signal detection) by the receiving radio as well as for timing acquisition (in order to find out when the payload actually begins), and also by various hardware calibration algorithms (for instance automatic gain control and frequency offset estimation) and channel estimation necessary for optimal decoding of the payload. The payload comprises the actual data to be transmitted and a header that contains information about the used transmission mode.…”

“…While the former is affected by transmit rate and power control mechanisms in the network, the latter is mainly determined by carrier sensing. The literature is rich with heuristics-based proposals on transmit rate control [21], [1], [2], [7], power control [3], [4], [5] and carrier sensing [6]. Even the standard carrier-sensing mechanism is mainly a heuristic, which is performed at the senders but affects mainly the receivers (i.e., the intended receiver as well as the receiver of the ongoing transmission), which might or might not be experiencing the same conditions as the potential sender.…”

“…For instance, in [6], dynamic transmit rate control and carrier sensing is shown to be advantageous, while [22] concludes that the product of transmit power and carrier sense threshold should be a fixed constant (i.e., should be changed at the same time). In [7], passive measurements of channel busy time are used to perform rate adaptation under congestion. In [23], [24], joint transmit power and rate control algorithms are proposed.…”

“…However, through transmit power control, the radio link transmit power can be dynamically tuned to compensate for variations and differences in channel conditions and hence, the SNR at a receiver is significantly affected by the transmission power settings. Similarly, observing that nodes should not adapt their rates due to losses during congestion, channel busy time (i.e., the fraction of time the medium is utilized) can be used as a metric [7]. Note that, in this case, the measurements of channel busy time are dependent on the underlying physical carrier sense mechanisms, which play a fundamental role in avoiding packet collisions.…”

Homomorphic Encryption Algorithm Used for Security Enhancement in Wireless Sensor Network Content-Based Routing

“…The blend of the power of processing, storage, and wireless communication implies that information can be acclimatized and spread utilizing keen algorithms [1], [5]. Also, many applications utilize wireless sensor nodes and suggest a noteworthy part of these systems would need to get the self-association ability.…”