Colin Keng-Yan Tan

Performance evaluation of MQTT and CoAP via a common middleware

Wireless sensor networks (WSNs) typically consist of sensor nodes and gateways that operate on devices with limited resources. As a result, WSNs require bandwidth-efficient and energy-efficient application protocols for data transmission. Message Queue Telemetry Transport (MQTT) and Constrained Application Protocol (CoAP) are two such protocols proposed for resource-constrained devices. In this paper, we design and implement a common middleware that supports MQTT and CoAP and provides a common programming interface. We design the middleware to be extensible to support future protocols. Using the common middleware, we conducted experiments to study the performance of MQTT and CoAP in terms of end-to-end delay and bandwidth consumption. Experimental results reveal that MQTT messages have lower delay than CoAP messages at lower packet loss rates and higher delay than CoAP messages at higher loss rates. Moreover, when the message size is small and the loss rate is equal to or less than 25%, CoAP generates lower additional traffic than MQTT to ensure message reliability.

Gaussian Process-Based Decentralized Data Fusion and Active Sensing for Mobility-on-Demand System.

Mobility-on-demand (MoD) systems have recently emerged as a promising paradigm of one-way vehicle sharing for sustainable personal urban mobility in densely populated cities. In this paper, we enhance the capability of a MoD system by deploying robotic shared vehicles that can autonomously cruise the streets to be hailed by users. A key challenge to managing the MoD system effectively is that of real-time, fine-grained mobility demand sensing and prediction. This paper presents a novel decentralized data fusion and active sensing algorithm for real-time, fine-grained mobility demand sensing and prediction with a fleet of autonomous robotic vehicles in a MoD system. Our Gaussian process (GP)-based decentralized data fusion algorithm can achieve a fine balance between predictive power and time efficiency. We theoretically guarantee its predictive performance to be equivalent to that of a sophisticated centralized sparse approximation for the GP model: The computation of such a sparse approximate GP model can thus be distributed among the MoD vehicles, hence achieving efficient and scalable demand prediction. Though our decentralized active sensing strategy is devised to gather the most informative demand data for demand prediction, it can achieve a dual effect of fleet rebalancing to service the mobility demands. Empirical evaluation on real-world mobility demand data shows that our proposed algorithm can achieve a better balance between predictive accuracy and time efficiency than state-of-the-art algorithms.

Stability Augmentation For Crosswind Landings Using Dynamic Cell Structures

This paper presents a Dynamic Cell Structure (DCS) based flight control system capable of enhancing lateral stability of aircrafts during severe crosswind landings. Two hybrid control systems are proposed. The first control system involves a Proportional Integral Derivative (PID) component and a modified DCS while the second control system involves a Non-linear Dynamic Inversion (NDI) component and a modified DCS. Three important changes have been made to the original DCS learning algorithm to increase the speed and accuracy of offline learning on the DCS. The classic gain controller within the NDI block is replaced with a PID component. Readings from the localizer of an aircraft are used to form a 2-dimensional input space and supplied to the control system in order to generate appropriate control surface deflections. The aim of the control system is to generate accurate control surface deflections such that precisely sufficient roll is produced to keep the aircraft along runway centerline (as required by the maneuver of crab landing). Simulations are carried out using a Piper PA-46 Malibu on the X-Plane simulator with the proposed control systems, and compared against the performance of the lateral stability component of a baseline PID system, dual-PID control system as well as that of a PID-NDI control system. Both the DCS-based hybrid control systems have shown tremendous improvement over the baseline PID system. Of all the systems compared, the DCS-NDI hybrid provides the best performance in terms of convergence time and average deflection from runway centerline. However, the computational complexity involved in the NDI block calls for a high performance system that can perform these complex computations in realtime. Considering the systems without an NDI component, the DCS-PID hybrid provides the best performance. The DCS-PID hybrid involves lesser computation as compared to the DCS-NDI hybrid, and performs better than the dual-PID control system. At high, yet realistic crosswind speeds of 50kts, both the proposed hybrid control systems are capable of converging to and maintaining runway centerline whereas the baseline PID system fails.

BOWL: augmenting the Semantic Web with beliefs

As the Semantic Web is an open, complex and constantly evolving medium, it is the norm, but not exception that information at different sites is incomplete or inconsistent. This poses challenges for the engineering and development of agent systems on the Semantic Web, since autonomous software agents need to understand, process and aggregate this information. Ontology language OWL provides core language constructs to semantically markup resources on the Semantic Web, on which software agents interact and cooperate to accomplish complex tasks. However, as OWL was designed on top of (a subset of) classic predicate logic, it lacks the ability to reason about inconsistent or incomplete information. Belief-augmented Frames (BAF) is a frame-based logic system that associates with each frame a supporting and a refuting belief value. In this paper, we propose a new ontology language Belief-augmented OWL (BOWL) by integrating OWL DL and BAF to incorporate the notion of confidence. BOWL is paraconsistent, hence it can perform useful reasoning services in the presence of inconsistencies and incompleteness. We define the abstract syntax and semantics of BOWL by extending those of OWL. We have proposed reasoning algorithms for various reasoning tasks in the BOWL framework and we have implemented the algorithms using the constraint logic programming framework. One example in the sensor fusion domain is presented to demonstrate the application of BOWL.

Robust airborne wireless backbone using low-cost UAVs and commodity WiFi technology

This paper proposes the use of low-cost unmanned aerial vehicles (UAVs) to enable communication between mutually unreachable ground stations in regions without communication infrastructure. The proposed method involves flying UAVs at communicable altitude in a pre-specified pattern over the ground stations. A fully autonomous control system based on the proportional integral derivative controller and the non-linear dynamic inversion controller has been built for this purpose. A modified Ad-hoc On-Demand Distance Vector (AODV) protocol is used to route data packets between the ground stations over the network formed by the UAVs using a delay tolerant approach. Using simulations, we show the effectiveness of the proposed solution, which consistently achieves a packet delivery ratio of above 90% regardless of number of UAVs. The average end-to-end delay drops steeply with an increase in number of UAVs. For a separation distance of 2 km between ground stations, four low-cost UAVs with commodity WiFi communications equipment can achieve an average end-to-end delay of 15 s and packet delivery ratio of 95%, thus giving a good balance between number of UAVs and average end-to-end delay.

Loop homological invariants associated to real projective spaces

Abstract Let A be a based subspace of Y. Under the assumptions that Y is path-connected and that the reduced diagonal map of A induces the zero map in all mod 2 reduced homology groups, we compute a formula for the mod 2 reduced Poincare series of the loop space Ω ( ( A ∧ R P ∞ ) ∪ A ∧ R P 1 ( Y ∧ R P 1 ) ) . Here R P ∞ and R P 1 denote the infinite real projective space and the real projective line respectively.

Participatory and Collaborative Design in the Creation of Applications for Societal Development

This paper discusses the significance of participation with end users with the other stakeholders and multidisciplinary collaboration in the design process for the creation of applications for societal development. We have applied the participatory design approach in two different scenarios: (1) in the context of designing tablet apps for autistic children and (2) in the context of designing a chat room for math students. In each context, we (a) inform the design process through a background research and (b) incorporate participatory design and collaboration with stakeholders into the design and evaluation process. Presenting both cases, we intend to discuss the problems and opportunities of participatory approaches for designing applications for societal development. In conclusion, the participatory design process allows highly particular responses and reactions of stakeholders which enriches the evolutionary design process.

Anytime Heuristic for Determining Agent Paths That Minimize Maximum Latency in a Sparse DTN

Mobile data relay agents (or ferries) have the potential to build wireless backbones over which sparsely located, unconnected nodes can communicate in a delay-tolerant fashion. Paths taken by agents determine the quality of such delay tolerant networks (DTNs). We consider the problem of determining agent paths that minimize the maximum pair wise latency in the network. We introduce the concept of Bounded Edge-Count Diametric Latency Minimizing Steiner trees (BECDLMST) where each edge represents an agent path and non-leaf nodes represent rendezvous points. Using ideas from particle swarm optimization, we propose an anytime algorithm to generate a near optimal BECDLMST. Beginning with a simple Minimum Diameter Steiner Tree (MDST), we apply an anytime heuristic and iteratively evolve the tree to produce a network structure that minimizes the maximum latency. Network latency results are presented for varying problem sizes in terms of number of nodes and number of agents.

Detection of Failures in Civil Structures Using Artificial Neural Networks

This paper presents an approach to failure detection in civil structure using supervised learning of data under normal conditions. For supervised learning to work, we would typically need data of anomalous cases and normal conditions. However, in reality there is abundant of data under normal conditions, and little or none anomalous data. Anomalous data can be generated from simulation using finite element modeling (FEM). However, every structure needs a specific FEM, and simulation may not cover all damage scenarios. Thus, we propose supervised learning of normal strain data using artificial neural networks and make prediction of the strain at future time instances. Large prediction error indicates anomalies in the structure. We also explore learning of both temporal trends and relationship of nearby sensors. Most literature in anomalies detection makes use of either temporal information or relationship between sensors, and we show that it is advantageous to use both.

Formation Control for Lightweight UAVs Under Realistic Communications and Wind Conditions

This paper presents a formation flight controller for lightweight UAVs when flying in windy scenarios under realistic communication limitations. The susceptibility of light aircrafts to even moderate winds necessitates a controller that corrects for its effects. On the other hand, the lightness causes the wingtip vortices, which form an important concern for most works in this area, to be negligible. The parameters used in order to track the separation trajectory are cross track error, XTD, and along track distance, ATD. The lateral controller has a modified Dynamic Cell Structure for the outer loop control and a Non Linear Dynamic Inversion (NLDI) controller for the inner loop control. The aim of the lateral controller is to generate accurate aileron deflections such that precisely sufficient roll is produced to keep the follower UAV on track by maintaining XTD at zero. The longitudinal controller consists of a Proportional Integral Derivative (PID) controller that controls throttle based on desired ground speed. Desired ground speed is computed using ATD and timing information obtained from the leader. Communication mechanisms have been proposed that will enable the controller to work well, despite packet latencies and possible link errors. Simulations are carried out by integrating two simulators: X-Plane 8.64 and Qualnet 4.5. Two separate X-Plane simulators (follower and leader) are interfaced via Qualnet, which simulates realistic wireless link characteristics. Results show that the proposed controller is capable of maintaining the follower within 10ft of the desired position at any point in time even with winds blowing at 30kts. The communication mechanism ensures good performance by the controller even with a 50% packet loss ratio, beyond which the probability of having more than 3 consecutive packet drops becomes high.