Data processing of physiological sensor data and alarm determination utilising activity recognition

Current physiological sensors are passive and transmit sensed data to Monitoring centre (MC) through wireless body area network (WBAN) without processing data intelligently. We propose a solution to discern data requestors for prioritising and inferring data to reduce transactions and conserve battery power, which is important requirements of mobile health (mHealth). However, there is a problem for alarm determination without knowing the activity of the user. For example, 170 beats per minute of heart rate can be normal during exercising, however an alarm should be raised if this figure has been sensed during sleep. To solve this problem, we suggest utilising the existing activity recognition (AR) applications. Most of health related wearable devices include accelerometers along with physiological sensors. This paper presents a novel approach and solution to utilise physiological data with AR so that they can provide not only improved and efficient services such as alarm determination but also provide richer health information which may provide content for new markets as well as additional application services such as converged mobile health with aged care services. This has been verified by experimented tests using vital signs such as heart pulse rate, respiration rate and body temperature with a demonstrated outcome of AR accelerometer sensors integrated with an Android app

Channel allocation for smooth video delivery over cognitive radio networks

This is the published version

A hybrid localization approach in 3D wireless sensor network

Location information acquisition is crucial for many wireless sensor network (WSN) applications. While existing localization approaches mainly focus on 2D plane, the emerging 3D localization brings WSNs closer to reality with much enhanced accuracy. Two types of 3D localization algorithms are mainly used in localization application: the range-based localization and the range-free localization. The range-based localization algorithm has strict requirements on hardware and therefore is costly to implement in practice. The range-free localization algorithm reduces the hardware cost but at the expense of low localization accuracy. On addressing the shortage of both algorithms, in this paper, we develop a novel hybrid localization scheme, which utilizes the range-based attribute RSSI and the range-free attribute hopsize, to achieve accurate yet low-cost 3D localization. As anchor node deployment strategy plays an important role in improving the localization accuracy, an anchor node configuration scheme is also developed in this work by utilizing the MIS (maximal independent set) of a network. With proper anchor node configuration and propagation model selection, using simulations, we show that our proposed algorithm improves the localization accuracy by 38.9% compared with 3D DV-HOP and 52.7% compared with 3D centroid

DisLoc: A Convex Partitioning Based Approach for Distributed 3-D Localization in Wireless Sensor Networks

Accurate localization in wireless sensor networks (WSNs) is fundamental to many applications, such as geographic routing and position-aware data processing. This, however, is challenging in large scale 3-D WSNs due to the irregular topology, such as holes in the path, of the network. The irregular topology may cause overestimated Euclidean distance between nodes as the communication path is bent and accordingly introduces severe errors in 3-D WSN localization. As an effort towards the issue, this paper develops a distributed algorithm to achieve accurate 3-D WSN localization. Our proposal is composed of two steps, segmentation and joint localization. In specific, the entire network is first divided into several subnetworks by applying the approximate convex partitioning. A spatial convex node recognition mechanism is developed to assist the network segmentation, which relies on the connectivity information only. After that, each subnetwork is accurately localized by using the multidimensional scaling-based algorithm. The proposed localization algorithm also applies a new 3-D coordinate transformation algorithm, which helps reduce the errors introduced by coordinate integration between subnetworks and improve the localization accuracy. Using extensive simulations, we show that our proposal can effectively segment a complex 3-D sensor network and significantly improve the localization rate in comparison with existing solutions

BitTorrent under a microscope : towards static QoS provision in dynamic peer-to-peer networks

For peer-to-peer (P2P) networks continually to flourish, QoS provision is critical. However, the P2P networks are notoriously dynamic and heterogeneous. As a result, QoS provision in P2P networks is a challenging task with nodes of the varying and intermittent throughput. This raises a fundamental problem: is stable and delicate QoS provision achievable in the highly dynamic and heterogeneous P2P networks? In this work, we investigate BitTorrent (BT) with the particular interest in its QoS performance in the highly dynamic and heterogeneous network. Our contributions are two-fold. First, we develop an analytical model to examine a randomly selected BT node under a microscope. Based on the model, we study the mean and variance of nodal download rate in the dynamic network and the performance of BT in QoS provision under different levels of peer churns. Our analysis unveils that although BT strives to provide nodes with guaranteed throughput, due to the network dynamics, the download rates of the peers oscillate extraordinarily and can hardly converge to the target QoS as proposed in previous literature. Second, to improve the QoS provision, we propose an enhanced protocol incorporating with BT. The proposed protocol enables nodes to quickly and elaborately search their uploaders, and as a result, achieve guaranteed and stable QoS in the dynamic networks. Using both analysis and simulations, we validate the effectiveness of the proposed protocol in comparisons with the original BT

P2P live streaming towards best video quality

Reproduced with the kind permission of the copyright owne