Emma Fitzgerald

A system for coupled road traffic utility maximisation and risk management using VANET

We propose a system for dynamic, online management of traffic accident risk in which vehicles exchange information via a vehicular ad-hoc network and use received information in calculating an estimate of current risk levels. We test the systems effectiveness in increasing the utility of the road network while maintaining the accident rate. We further prove the convergence of our proposed algorithm and investigate the information propagation, convergence rate and bandwidth requirements of the system and find that the system is able to increase the utility at maintained accident rate while operating within the confines of the IEEE 802.11p radio standard.

The failure of CSMA in emerging wireless network scenarios

The current family of 802.11 protocols are based on the Carrier Sense Multiple Access (CSMA) mechanism which is a simple and robust means of sharing a channel. However, two current trends in wireless networks point towards a situation where CSMA fails to perform better than pure random access solutions such as ALOHA. The first trend is the ever increasing raw data rate in each generation of 802.11 which is set to continue with the current 802.11ax standardisation. The second is the move towards smaller frames as end users increasingly use mobile devices instead of desktop computers. We show that as the ratio of propagation delay to packet transmission time increases, the performance of CSMA degrades correspondingly, to the point where ALOHA outperforms CSMA.

Modeling, implementation and evaluation of IEEE 802.11ac in NS-3 for enterprise networks

In this work we implement features for IEEE 802.11ac in the NS-3 simulator, in particular wider channels and bit-error calculations for higher modulation coding schemes. We also implement four wireless LAN deployment scenarios from the 802.11ax working group scenario document, and evaluate their performance under different operating conditions. Our simulation results demonstrate that many nodes in an enterprise network will yield lower average throughput to each AP and several APs on the same channel will create unreliable networks with some stations getting high throughput and some not able to send at all. Significant improvement in throughput was also observed with the use of frame aggregation.

Intention Sharing for Medium Access Control in Wireless LANs

In this paper we present a new class of MAC protocols for wireless LANs based on sharing of transmission intentions. We develop an example protocol implementation based on distributed, co-operative scheduling of data frames. Schedules are non-binding, requiring minimal negotiation between nodes. The protocol is implemented on top of standard 802.11 so that backwards compatibility with legacy nodes is maintained. We have developed efficient algorithms to merge multiple schedules from neighbouring nodes and find suitable gaps in which to schedule a given nodes frames. To test the protocols performance, we conducted simulation studies using OMNeT++. Our results show that our protocol achieves higher throughput and lower delay than 802.11 under high offered loads, and eliminates frame collisions.

An analytic model for Throughput Optimal Distributed Coordination Function (TO-DCF)

TO-DCF, a new backoff scheme for 802.11, has the potential to significantly increase throughput in dense wireless LANs while also opportunistically favouring nodes with heavier traffic loads and/or better channel conditions. In this paper we present an analytical model to investigate the behaviour and performance of the TO-DCF protocol with regards to operating parameters such as the number of nodes, the contention window size and the backoff countdown probabilities. We then compare numerical results from an implementation of our model with simulations. Our model shows a high level of accuracy, even when the model assumptions are relaxed, and provides guidance for network operators to correctly configure the weight functions for nodes running TO-DCF given the network’s operating conditions.

LUPMAC: A cross-layer MAC technique to improve the age of information over dense WLANs

Age of Information (AoI) is a relatively new metric introduced to capture the freshness of a particular piece of information. While throughput and delay measurements are widely studied in the context of dense IEEE 802.11 Wireless LANs (WLANs), little is known in the literature about the AoI in this context. In this work we study the effects on the average AoI and its variance when a sensor node is immersed in a dense IEEE 802.11 WLAN. We also introduce a new cross layer MAC technique, called Latest UPdate MAC (LUPMAC), aimed at modifying the existing IEEE 802.11 in order to minimize the average AoI at the receiver end. This technique lets the MAC layer keep only the most up to date packets of a particular piece of information in the buffer. We show, through simulation, that this technique achieves significant advantages in the case of a congested dense IEEE 802.11 WLAN, and it is resilient to changes in the variance of the total network delay.

Energy-Optimal Data Aggregation and Dissemination for the Internet of Things

Established approaches to data aggregation in wireless sensor networks (WSNs) do not cover the variety of new use cases developing with the advent of the Internet of Things (IoT). In particular, the current push toward fog computing, in which control, computation, and storage are moved to nodes close to the network edge, induces a need to collect data at multiple sinks, rather than the single sink typically considered in WSN aggregation algorithms. Moreover, for machine-to-machine communication scenarios, actuators subscribing to sensor measurements may also be present, in which case data should be not only aggregated and processed in-network but also disseminated to actuator nodes. In this paper, we present mixed-integer programming formulations and algorithms for the problem of energy-optimal routing and multiple-sink aggregation, as well as joint aggregation and dissemination, of sensor measurement data in IoT edge networks. We consider optimization of the network for both minimal total energy usage, and min-max per-node energy usage. We also provide a formulation and algorithm for throughput-optimal scheduling of transmissions under the physical interference model in the pure aggregation case. We have conducted a numerical study to compare the energy required for the two use cases, as well as the time to solve them, in generated network scenarios with varying topologies and between 10 and 40 nodes. Although aggregation only accounts for less than 15% of total energy usage in all cases tested, it provides substantial energy savings. Our results show more than 13 times greater energy usage for 40-node networks using direct, shortest-path flows from sensors to actuators, compared with our aggregation and dissemination solutions.

Performance evaluation of an intention sharing MAC scheme in wireless LANs with hidden nodes

We have previously presented Intent, a medium access control scheme for WLANs based on cooperative, distributed, non-binding frame scheduling. The main idea behind Intent is “intention sharing”-a mechanism that allows a node to be aware of transmissions previously scheduled by its neighbors. We now extend this scheme to networks with hidden nodes. We give a formulation of the scheduling problem and solve for the optimal solution using mixed-integer programming in a range of scenarios covering both mesh and infrastructure networks of varying density. We also provide an algorithmic solution and perform simulations using four variants of this, comparing the results with both the optimal solution and standard 802.11. Our algorithmic solution gives significantly better performance than 802.11 and comes within 1.1 times optimal performance when full, two-hop scheduling information is available. In addition, we show that it is not necessary to exchange complete scheduling information in order to perform distributed scheduling effectively but rather a conflict resolution or avoidance mechanism combined with non-binding schedules allows for similar performance with only a single round of information exchange between neighbouring nodes.

Understanding the WiFi usage of university students

In this work, we analyze the use of a WiFi network deployed in a large-scale technical university. To this extent, we leverage three weeks of WiFi traffic data logs and characterize the spatio-temporal correlation of the traffic at different granularities (each individual access point, groups of access points, entire network). The spatial correlation of traffic across nearby access points is also assessed. Then, we search for distinctive fingerprints left on the WiFi traffic by different situations/conditions; namely, we answer the following questions: Do students attending a lecture use the wireless network in a different way than students not attending a lecture?, and Is there any difference in the usage of the wireless network during architecture or engineering classes? A supervised learning approach based on Quadratic Discriminant Analysis (QDA) is used to classify empty vs. occupied rooms and engineering vs. architecture lectures using only WiFi traffic logs with promising results.

OMAC: An Opportunistic Medium Access Control Protocol for IEEE 802.11 Wireless Networks

The ambitious goal of the upcoming IEEE 802.11ax (HEW) standard for wireless LANs (WLANs) to enhance throughput by four times (and beyond), compared with IEEE 802.11ac, demands a radical improvement of present medium access control (MAC) functionality. To this end, a promising paradigm would be a graceful migration towards new MAC protocols which incorporate higher certainty in their decisions. However, this requires adequate information to be available to the devices, which in turn incurs excessive costs due to information exchange between devices. Also, scalability becomes an issue for emerging dense networks. In this paper, we take a step forward by proposing an opportunistic MAC (OMAC), which restrains these costs, while increasing throughput of the new generation HEW. OMAC eliminates overhead costs by solely relying on the local capability of devices in measuring signal activities in the channel. A particular OMAC node continually collects and records the received signal strengths (RSS) overheard from the channel, and regards each individual RSS level as being transmitted by a unique node without the need to know the actual identity of the node. The OMAC node uses this knowledge to select a recorded RSS as its reference, and triggers a desired transmission policy whenever a transmission with an RSS sufficiently close to this reference RSS is detected. Our results, obtained using simulations, indicate that OMAC improves the throughput performance significantly, and that the performance gain increases with an increase in network density.