Enhanced Collision Resolution for the IEEE 802.11 Distributed Coordination Function

The IEEE 802.11 standard relies on the Distributed Coordination Function (DCF) as the fundamental medium access control method. DCF uses the Binary Exponential Backoff (BEB) algorithm to regulate channel access. The backoff period determined by BEB depends on a contention window (CW) whose size is doubled if a station suffers a collision and reset to its minimum value after a successful transmission. BEB doubles the CW size upon collision to reduce the collision probability in retransmission. However, this CW increase reduces channel access time because stations will spend more time sensing the channel rather than accessing it. Although resetting the CW to its minimum value increases channel access, it negatively affects fairness because it favours successfully transmitting stations over stations suffering from collisions. Moreover, resetting CW leads to increasing the collision probability and therefore increases the number of collisions. % Quality control editor: Please ensure that the intended meaning has been maintained in the edits of the previous sentence. Since increasing channel access time and reducing the probability of collisions are important factors to improve the DCF performance, and they conflict with each other, improving one will have an adverse effect on the other and consequently will harm the DCF performance. We propose an algorithm, \gls{ECRA}, that solves collisions once they occur without instantly increasing the CW size. Our algorithm reduces the collision probability without affecting channel access time. We also propose an accurate analytical model that allows comparing the theoretical saturation and maximum throughputs of our algorithm with those of benchmark algorithms. Our model uses a collision probability that is dependent on the station transmission history and thus provides a precise estimation of the probability that a station transmits in a random timeslot, which results in a more accurate throughput analysis. We present extensive simulations for fixed and mobile scenarios. The results show that on average, our algorithm outperformed BEB in terms of throughput and fairness. Compared to other benchmark algorithms, our algorithm improved, on average, throughput and delay performance

A differentiated Services Architecture for Quality of Service Provisioning in Wireless Local Area Networks

Currently the issue of Quality of Service (QoS) is a major problem in IP networks due to the growth in multimedia traffic (e.g. voice and video applications) and therefore many mechanisms like IntServ, DiffServ, etc. have been proposed. Since the IEEE 802.11b (or Wi-Fi) standard was approved in 1999, it has gained in popularity to become the leading Wireless Local Area Network (WLAN) technology with millions of such networks deployed worldwide. Wireless networks have a limited capacity (11 Mbits/s in the case of Wi-Fi networks) owing to the limited amount of frequency spectrum available. At any given time there may be a large number of users contending for access which results in the bandwidth available to each user being severely limited. Moreover, the system does not differentiate between traffic types which means that all traffic, regardless of its importance or priority, experiences the same QoS. An important network application requiring QoS guarantees is the provision of time-bounded services, such as voice over IP and video streaming, where the combination of packet delay, jitter and packet loss will impact on the perceived QoS. Consequently this has led to a large amount of research work focussing mainly on QoS enhancement schemes for the 802.11 MAC mechanism. The Task Group E of the IEEE 802.11 working group has been developing an extension to the Wi-Fi standard that proposes to make changes to the MAC mechanism to support applications with QoS requirements. The 802.11e QoS standard is currently undergoing final revisions before approval expected sometime in 2004. As 802.11e WLAN equipment is not yet available, performance reports can only be based on simulation. The objective of this thesis was to develop a computer simulator that implements the upcoming IEEE 802.11e standard and to use this simulator to evaluate the QoS performance enhancement potential of 802.11e. This thesis discusses the QoS facilities, analyses the MAC protocol enhancements and compares them with the original 802.11 standard. The issue of QoS provisioning is primarily concerned with providing predictable performance guarantees with regard to throughput, packet delay, jitter and packet loss. The simulated results indicate that the proposed QoS enhancements to the MAC will considerably improve QoS performance in 802.11b WLANs. However, in order for the proposed 802.11e QoS mechanism to be effective the 802.11e parameters will need to be continually adjusted in order to ensure QoS guarantees are fulfilled for all traffic loads

Backoff as Performance improvements Algorithms - A Comprehenssive Review

As a significant part of the Media Access Control protocol, the backoff algorithm purpose is to minimize number of collisions if not totally avoid any collision in Mobile Ad Hoc Networks, in the case of contention between nodes to access a channel. Researchers have proposed many algorithms for backoff to enhance the network performance and improve it. This paper aims at exploring the main and most studied backoff algorithms and how do these algorithms lead to an enhancement of the MANETs performance. This paper also compares between the algorithms proposed in the literature and evaluates to what extent they have affected the performance and enhance it

Decentralised Learning MACs for Collision-free Access in WLANs

By combining the features of CSMA and TDMA, fully decentralised WLAN MAC schemes have recently been proposed that converge to collision-free schedules. In this paper we describe a MAC with optimal long-run throughput that is almost decentralised. We then design two \changed{schemes} that are practically realisable, decentralised approximations of this optimal scheme and operate with different amounts of sensing information. We achieve this by (1) introducing learning algorithms that can substantially speed up convergence to collision free operation; (2) developing a decentralised schedule length adaptation scheme that provides long-run fair (uniform) access to the medium while maintaining collision-free access for arbitrary numbers of stations

Improving Performance for CSMA/CA Based Wireless Networks

Carrier Sense Multiple Access with Collision Avoidance (CSMA/CA) based wireless networks are becoming increasingly ubiquitous. With the aim of supporting rich multimedia applications such as high-definition television (HDTV, 20Mbps) and DVD (9.8Mbps), one of the technology trends is towards increasingly higher bandwidth. Some recent IEEE 802.11n proposals seek to provide PHY rates of up to 600 Mbps. In addition to increasing bandwidth, there is also strong interest in extending the coverage of CSMA/CA based wireless networks. One solution is to relay traffic via multiple intermediate stations if the sender and the receiver are far apart. The so called “mesh” networks based on this relay-based approach, if properly designed, may feature both “high speed” and “large coverage” at the same time. This thesis focusses on MAC layer performance enhancements in CSMA/CA based networks in this context. Firstly, we observe that higher PHY rates do not necessarily translate into corresponding increases in MAC layer throughput due to the overhead of the CSMA/CA based MAC/PHY layers. To mitigate the overhead, we propose a novel MAC scheme whereby transported information is partially acknowledged and retransmitted. Theoretical analysis and extensive simulations show that the proposed MAC approach can achieve high efficiency (low MAC overhead) for a wide range of channel variations and realistic traffic types. Secondly, we investigate the close interaction between the MAC layer and the buffer above it to improve performance for real world traffic such as TCP. Surprisingly, the issue of buffer sizing in 802.11 wireless networks has received little attention in the literature yet it poses fundamentally new challenges compared to buffer sizing in wired networks. We propose a new adaptive buffer sizing approach for 802.11e WLANs that maintains a high level of link utilisation, while minimising queueing delay. Thirdly, we highlight that gross unfairness can exist between competing flows in multihop mesh networks even if we assume that orthogonal channels are used in neighbouring hops. That is, even without inter-channel interference and hidden terminals, multi-hop mesh networks which aim to offer a both “high speed” and “large coverage” are not achieved. We propose the use of 802.11e’s TXOP mechanism to restore/enfore fairness. The proposed approach is implementable using off-the-shelf devices and fully decentralised (requires no message passing)

A Q-Learning approach with collective contention estimation for bandwidth-efficient and fair access control in IEEE 802.11p vehicular networks

Vehicular Ad hoc Networks (VANETs) are wireless networks formed of moving vehicle-stations, that enable safety-related packet exchanges among them. Their infrastructure-less, unbounded nature allows the formation of dense networks that present a channel sharing issue, which is harder to tackle than in conventional WLANs, due to fundamental differences of the protocol stack. Optimising channel access strategies is important for the efficient usage of the available wireless bandwidth and the successful deployment of VANETs. We present a Q-Learning-based approach to wirelessly network a big number of vehicles and enable the efficient exchange of data packets among them. More specifically, this work focuses on a IEEE 802.11p-compatible contention-based Medium Access Control (MAC) protocol for efficiently sharing the wireless channel among multiple vehicular stations. The stations feature algorithms that "learn" how to act optimally in a network in order to maximise their achieved packet delivery and minimise bandwidth wastage. Additionally, via a Collective Contention Estimation (CCE) mechanism which we embed on the Q-Learning agent, faster convergence, higher throughput and short-term fairness are achieved

Contention-based learning MAC protocol for broadcast Vehicle-to-Vehicle Communication

Vehicle-to-Vehicle Communication (V2V) is an upcoming technology that can enable safer, more efficient transportation via wireless connectivity among moving cars. The key enabling technology, specifying the physical and medium access control (MAC) layers of the V2V stack is IEEE 802.11p, which belongs in the IEEE 802.11 family of protocols originally designed for use in WLANs. V2V networks are formed on an ad hoc basis from vehicular stations that rely on the delivery of broadcast transmissions for their envisioned services and applications. Broadcast is inherently more sensitive to channel contention than unicast due to the MAC protocol’s inability to adapt to increased network traffic and colliding packets never being detected or recovered. This paper addresses this inherent scalability problem of the IEEE 802.11p MAC protocol. The density of the network can range from being very sparse to hundreds of stations contenting for access to the channel. A suitable MAC needs to offer the capacity for V2V exchanges even in such dense topologies which will be common in urban networks. We present a modified version of the IEEE 802.11p MAC based on Reinforcement Learning (RL), aiming to reduce the packet collision probability and bandwidth wastage. Implementation details regarding both the learning algorithm tuning and the networking side are provided. We also present simulation results regarding achieved message packet delivery and possible delay overhead of this solution. Our solution shows up to 70% increase in throughput compared to the standard IEEE 802.11p as the network traffic increases, while maintaining the transmission latency within the acceptable levels