Contention and Traffic Load-aware Association in IEEE 802.11 WLANs: Algorithms and Implementation Stratos Keranidis Thanasis Korakis Iordanis Koutsopoulos Leandros Tassiulas Department of Computer and Communication Engineering, University of Thessaly, Greece Centre for Research and Technology Hellas, CERTH, Greece E-mail: {efkerani, korakis, jordan, leandros}@uth.gr Abstract—Efficient association of a station with the appropriate access point has always been a challenging problem. The standard approach of considering only the Received Signal Strength, has recently been substituted by more efficient schemes that consider channel conditions, cell population etc. However, in spite of the large variety of approaches, several factors that determine to a large extent user throughput after association with an access point have been overlooked. In this work, we propose innovative metrics on which association should be based. First, we capture the contention from one-hop and interference from two-hop neighbors that is inherent in IEEE 802.11 WLAN environments. Second we include the PHY transmission rate and show preference to higher rates that reduce the above effects. Third, unlike most relevant approaches, we define an activity factor that reveals the anticipated activity due to backlogged traffic. We devise an association protocol suite, through which messages containing the information above are passed between the AP and the user to support association decisions for the uplink and downlink. We implement the proposed mechanism using the MAD-WiFi open source driver and moreover show through experiments in a wireless testbed that it significantly improves user performance in real conditions. Index Terms—Wireless communications, Association, Handoff, MAC, IEEE 802.11 I. INTRODUCTION In IEEE 802.11 WLANs, each station (STA) has to first associate with an access point (AP), before it can start trans- mitting data to other nodes in the network. This association procedure consists of four phases. During the first phase, a STA has to discover the networks in its vicinity before it can join a Basic Service Set (BSS). This process is called scanning and can be either passive or active. In passive scanning, a STA scans all available channels and listens to information periodically broadcasted by the APs in their beacon frames. In active scanning, a STA tries to find the BSSs in its vicinity by transmitting a Probe Request frame on each channel of the channel list. APs respond by sending Probe Response frames. Having collected these frames, the STA decides which AP it will associate with, in the second phase. According to the standard [1], AP selection is based on the Received Signal Strength Indication (RSSI). A STA simply selects the AP from which it has received the strongest signal during the scanning process. In the third phase, the STA has to follow the authenti- cation process if the selected AP follows some authentication mode. Finally, the STA sends an Association Request frame to the selected AP and sequentially the AP responds with an Association Response frame. If the Association Response frame is received with a ”successful” status value, the STA is now associated with the AP. The rest of the paper is organized as follows. In the remaining of this section the state of the art related work is presented and a summarization of our contribution follows. A detailed analysis of our metric definition follows in section II. Details about the proposed algorithms and their implemen- tation are provided in section III. The configuration of our experiments, concerning the testbed and the methodology used is then described in section IV. In section V, we experimentally evaluate the performance of our implementation. Finally, in section VI, we present the conclusion and discussion of future work. A. Related Work The performance of the standard AP selection policy has been extensively studied and it is well known that it leads to inefficient use of the network resources [2],[3]. In addition, due to the asymmetric nature of the wireless medium, this policy becomes unsuitable, as RSSI is an indicator just for the downlink channel and not for the uplink. An association mech- anism considering signal to interference and noise (SINR) per connection, as well as asymmetric traffic was proposed in our previous work [4]. Although our approach considered uplink channel conditions as well, thus offering a significant improvement, it was not able to lead to the best available throughput performance. One of the major issues studied among relevant works has been the proper definition of AP load. The authors in [5], proposed an AP selection policy that estimates AP load based on instantaneous measurements of the transmission rate and the fraction of time an AP acquires the channel for its transmissions. However, this model faces the disadvantage of considering only downlink traffic and therefore assumes that channel contention is only among APs. Another common assumption of works on the field has been to denote AP load as a factor reflecting the AP’s inability to satisfy the requirements of its associated users [2],[6]. Another approach followed in [7], bases association decisions on a metric denoted as airtime cost, which considers both uplink and downlink traffic as well as AP load. The above approaches, have the common char- acteristic of considering the effect induced by transmissions only of associated users in the AP load estimation. However, since the IEEE 802.11 MAC layer is based on contention, the efficiency of an AP is not only dependent on