The research work presents an enhanced cross-layer routing solution for Wireless Mesh Networks (WMN) based on Received Signal Strength. WMN is an emerging technology with varied applications due to inherent advantages ranging from self-organisation to auto-con guration. Routing in WMN is fundamen- tally achieved by hop counts which have been proven to be de cient in terms of network performance. The realistic need to enhance the link quality metric to improve network performance has been a growing concern in recent times. The cross-Layer routing approach is one of the identi ed methods of improving routing process in Wireless technology. This work presents an RSSI-aware routing metric implemented on Optimized Link-State Routing (OLSR) for WMN. The embedded Received Signal Strength Information (RSSI) from the mesh nodes on the network is extracted, processed, transformed and incorporated into the routing process. This is to estimate efficiently the link quality for network path selections to improved network performance. The measured RSSI data is filtered by an Exponentially Weighted Moving Average (EWMA) filter. This novel routing metric method is called RSSI-aware ETT (rETT). The performance of rETT is then optimised and the results compared with the fundamental hop count metric and the link quality metric by Expected Transmission Counts (ETX). The results reveal some characteristics of RSSI samples and link conditions through the analysis of the statistical data. The divergence or variability of the samples is a function of interference and multi-path e effect on the link. The implementation results show that the routing metric with rETT is more intelligent at choosing better network paths for the packets than hop count and ETX estimations. rETT improvement on network throughput is more than double (120%) compared to hop counts and 21% improvement compared to ETX. Also, an improvement of 33% was achieved in network delay compared to hop counts and 28% better than ETX. This work brings another perspective into link-quality metric solutions for WMN by using RSSI to drive the metric of the wireless routing protocol. It was carried out on test-beds and the results obtained are more realistic and practical. The proposed metric has shown improvement in performance over the classical hop counts metric and ETX link quality metric.

Thesis (M.S.)--University of Florida, 2004. / Title from title page of source document. Document formatted into pages; contains 106 pages. Includes vita. Includes bibliographical references.

Thesis (Ph.D.)--Hong Kong University of Science and Technology, 2009. / Includes bibliographical references (p. 110-120).

ITC/USA 2015 Conference Proceedings / The Fifty-First Annual International Telemetering Conference and Technical Exhibition / October 26-29, 2015 / Bally's Hotel & Convention Center, Las Vegas, NV / The use of wireless data networks is ubiquitous in the consumer world. They have gained significant traction due to advantages afforded by the lack of wires. These same advantages can prove valuable in Flight Test for data acquisition. Sensor nodes are ideal candidates for low bandwidth wireless networks. Located in remote, hard to reach and hostile environments, wirelessly acquiring data from such sensor can solve a number of existing issues for FTI engineers. Implementing such wireless communication introduces a number of challenges such as guaranteeing reliable transfer of the sensor data and time synchronization of the remote nodes. This paper addresses wireless sensor acquisition, the associated challenges and discusses approaches and solutions to these problems.

Enabling efficient media streaming over wireless channels requires efficient utilization of the limited wireless spectrum while satisfying multimedia applications' quality of service (QoS) requirements. In this dissertation, we provide insights into network and application-centric approaches for media streaming over wireless channels. In network-centric approaches, the fundamental problem is how to model network variations at the different layers and optimize the total quality across these layers. We use Finite-state Markov chain (FSMC) models to investigate the packet loss and delay performance over a wireless link. We propose a new method for partitioning the received SNR space that results in a FSMC model with tractable queueing performance. We then use this model to derive closed-form expressions for the {\em Effective Bandwidth\/} subject to either packet loss or packet delay constraints. In application-centric approaches, we take into account the VBR nature of video frames and channel dynamics and integrate in the analysis the dynamics of the playback buffer occupancy. We introduce a mixture of sourec/channel rate adaptation schemes that target efficient utilization of the wireless spectrum and safeguard the continuity of media streaming over wireless channels. First, we propose two source-rate control schemes for streaming video over wireless channels that provide gracefully degraded quality and soft guarantees on frame delay. The schemes are designed to maximize the source bit rate at the encoder while preventing/reducing events of starvation at the decoder. Second, we present a novel cycle-based rate adaptation scheme. The scheme is designed to maximize the source bit rate at the encoder while guaranteeing an upper bound on the probability of starvation at the playback buffer. This approach can be applied to both {\em one-way} and {\em interactive} video. Finally, we propose a playback-adaptive source/channel rate control (SCRC) for video streaming over wireless channels. We exploit the so-called playback adaptation margin and the playback buffer occupancy to control the source and channel rates. The SCRC scheme is designed to limit potential playback discontinuities that may occur due to variations in the wireless link.

University of Macau / Faculty of Science and Technology. / Department of Electrical and Computer Engineering

Wireless sensors and their applications have become increasingly attractive for industry, building automation and energy control, paving the way for new applications of sensor networks which go well beyond traditional sensor applications. In recent years, there has been a rapid growth in the number of wireless devices operating in close proximity to the human body. Wearable sensor nodes are growing popular not only in our normal living lifestyle, but also within healthcare and military applications, where different radio units operating in/on/off body communicate pervasively. Expectations go beyond the research visions, towards deployment in real-world applications that would empower business processes and future business cases. Although theoretical and simulation models give initial results of the antenna behaviour and the radio channel performance of wireless body area network (WBAN) devices, empirical data from different set of measurements still form an essential part of the radio propagation models. Usually, measurements are performed in laboratory facilities which are equipped with bulky and expensive RF instrumentation within calibrated and controllable environments; thus, the acquired data has the highest possible reliability. However, there are still measurement uncertainties due to cables and connections and significant variations when designs are deployed and measured in real scenarios, such as hospitals wards, commercial buildings or even the battle field. Consequently, more flexible and less expensive measurement tools are required. In this sense, wireless sensor nodes offer not only easiness to deploy or flexibility, but also adaptability to different environments. In this thesis, custom-built wireless sensor nodes are used to characterise different on-body radio channels operating in the IEEE 802.15.4 communication standard at the 2.45 GHz ISM band. Measurement results are also compared with those from the conventional technique using a Vector Network Analyser. The wireless sensor nodes not only diminished the effect of semi-rigid or flexible coaxial cables (scattering or radiation) used with the Vector Network Analyser (VNA), but also provided a more realistic response of the radio link channel. The performance of the wireless sensors is presented over each of the 16 different channels present at the 2.45 GHz band. Additionally, custom-built wireless sensors are used to characterise and model the performance of different on-body radio links in dynamic environments, such as jogging, rowing, and cycling. The use of wireless sensors proves to be less obstructive and more flexible than traditional measurements using coaxial cables, VNA or signal generators. The statistical analysis of different WBAN channels highlighted important radio propagation features which can be used as sport classifiers models and motion detection. Moreover, specific on-body radio propagation channels are further explored, with the aim to recognize physiological features such as motion pattern, breathing activity and heartbeat. The time domain sample data is transformed to the frequency domain using a non-parametric FFT defined by the Welch’s periodogram. The Appendix-Section D explores other digital signal processing techniques which include spectrograms (STFT) and wavelet transforms (WT). Although a simple analysis is presented, strong DSP techniques proved to be good for signal de-noising and multi-resolution analysis. Finally, preliminary results are presented for indoor tracking using the RSS recorded by multiple wireless sensor nodes deployed in an indoor scenario. In contrast to outdoor environments, indoor scenarios are subject to a high level of multipath signals which are dependent on the indoor clutter. The presented algorithm is based on path loss analysis combined with spatial knowledge of each wireless sensor.

Security and trust are two interdependent concepts and are often used interchangeably when defining a secure wireless sensor network (WSN) system. However, security is different from trust in that, it assumes no node is trustworthy and requires ongoing authentication using sophisticated protocols leading to high communication and computation overheads. This makes the traditional cryptographic security tools hard, if not impossible, to be used in wireless sensor networks that are severely resource constrained. Trust on the other hand is the exact opposite of security in that any node can interact with any other and requires no authentication and unwrapping of hidden keys to carry on with their business and hence carries zero overhead. However, this leads to the miss-use and abuse of networks causing loss and damage to the owners of the networks. This thesis focuses on developing novel methods for modelling and managing trust that enable WSN to be secure while significantly reducing computing and communication overheads. Although researchers have been studying the problem of trust modelling and management in wireless sensor networks for over a decade, their focus was on the trust associated with routing messages between nodes (communication trust). However, wireless sensor networks are mainly deployed to sense the world and report data, both continuous and discrete. However, there are no methods in the literature that focus on the trust associated with misreporting data (data trust). In this thesis, we model the trust associated with the integrity of the data, and propose methods to combine the data trust with the communication trust to infer the total trust. Bayesian probabilistic approach is used to model and manage trust. A new risk assessment algorithm for establishing trust in wireless sensor networks based on the quality of services characteristics of sensor nodes, using the traditional weighting approach is introduced. Then a Beta distribution is used to model communication trust (due to its binary nature) and determine the weights in terms of the Beta distribution parameters to probabilistically combine direct and indirect trust. The thesis extends the Bayesian probabilistic approach to model data trust for cases when the sensed data is continuous. It introduces the Gaussian trust and reputation system to that accounts for uncertain characteristics of sensor data. Finally we introduce a Bayesian fusion algorithm to combine the data trust and communication trust to infer the overall trust between nodes. Simulation results are presented to demonstrate how the models accurately classify different nodes as being trustworthy or not based on their reliability in sensor reporting and routing functions.

Security and trust are two interdependent concepts and are often used interchangeably when defining a secure wireless sensor network (WSN) system. However, security is different from trust in that, it assumes no node is trustworthy and requires ongoing authentication using sophisticated protocols leading to high communication and computation overheads. This makes the traditional cryptographic security tools hard, if not impossible, to be used in wireless sensor networks that are severely resource constrained. Trust on the other hand is the exact opposite of security in that any node can interact with any other and requires no authentication and unwrapping of hidden keys to carry on with their business and hence carries zero overhead. However, this leads to the miss-use and abuse of networks causing loss and damage to the owners of the networks. This thesis focuses on developing novel methods for modelling and managing trust that enable WSN to be secure while significantly reducing computing and communication overheads. Although researchers have been studying the problem of trust modelling and management in wireless sensor networks for over a decade, their focus was on the trust associated with routing messages between nodes (communication trust). However, wireless sensor networks are mainly deployed to sense the world and report data, both continuous and discrete. However, there are no methods in the literature that focus on the trust associated with misreporting data (data trust). In this thesis, we model the trust associated with the integrity of the data, and propose methods to combine the data trust with the communication trust to infer the total trust. Bayesian probabilistic approach is used to model and manage trust. A new risk assessment algorithm for establishing trust in wireless sensor networks based on the quality of services characteristics of sensor nodes, using the traditional weighting approach is introduced. Then a Beta distribution is used to model communication trust (due to its binary nature) and determine the weights in terms of the Beta distribution parameters to probabilistically combine direct and indirect trust. The thesis extends the Bayesian probabilistic approach to model data trust for cases when the sensed data is continuous. It introduces the Gaussian trust and reputation system to that accounts for uncertain characteristics of sensor data. Finally we introduce a Bayesian fusion algorithm to combine the data trust and communication trust to infer the overall trust between nodes. Simulation results are presented to demonstrate how the models accurately classify different nodes as being trustworthy or not based on their reliability in sensor reporting and routing functions.

A masters thesis focussing on achieving improvements in transmission reliability and energy efficiency for a battery-powered wireless sensor node on the edge of an industrial heterogeneous wireless network that consists predominantly of mains-powered nodes. A router-switching technique is proposed to allow the sensor node to make gains in transmission reliability and energy efficiency by taking advantage of the scenario where multiple wireless routers are in range and switching between them, instead of only being able to transmit to one router. The research involves simulation of a number of network scenarios where the router-switching technique is enabled and disabled, to measure the advantage gained for the sensor in terms of its functional lifetime. The simulation is based on an abstract model that focusses on the edge of the mains-powered area of the network, where the battery-powered sensor is located. The simulation results show that for many cases, router-switching provides a higher level of transmission reliability and lower levels of energy consumption than the scenario where router-switching is disabled, as well as improvements in data loss rates.