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Low cost, low power wireless sensors (motes) promise to revolutionize environmental data collection, but are they currently refined enough for widespread use by hydrologists? Their viability as a replacement for traditional data collection techniques was investigated in a 7 ha forested watershed in south-western British Columbia. The watershed included 41 instrument clusters measuring air and soil temperature, humidity, throughfall, soil moisture content, overland flow and groundwater head. The foundation of each cluster was a data box containing a MDA300 data acquisition board and a MICA2 processor board from Crossbow Technologies, Inc.™ that allowed for short range wireless data collection. The 41 motes each recorded data every 15 minutes from July, 2006, to April, 2007. In addition to reporting on the reliability of the motes and sensors during the 10 months deployment, the high spatial and temporal resolution data collected by this study gave the opportunity for many analyses of catchment processes. As soil moisture and throughfall are two influential processes in the exchange of water between the earth and the atmosphere, these were the focus of the data analysis. The first analysis was a resampling experiment on seven different events selected from the full data set. Comparing 100 different subsamples each of 5, 10 and 20 points for throughfall and soil moisture showed if increasing the sample size eventually produced diminishing returns in the ability to reproduce the true catchment mean. With significant differences in prediction ability for both soil moisture and throughfall at times of differing hydrologic activity, this analysis provides further support for the theories of changing moisture states of soil moisture and threshold values for throughfall. The second analysis described how the organization of soil moisture and throughfall changed during a range of weather conditions and timescales. Spatial representation of normalized values and Pearson correlation coefficients showed that there were distinct differences between wet and dry periods for soil moisture and between long and short analysis periods for throughfall. / Forestry, Faculty of / Graduate

In this thesis, we propose a suite of Evolutionary Algorithms (EA)-based protocols to solve the problems of clustering and routing in Wireless Sensor Networks (WSNs). At the beginning, the problem of the Cluster Heads (CHs) selection in WSNs is formulated as a single-objective optimization problem. A centralized weighted-sum multi-objective optimization protocol is proposed to find the optimal set of CHs. The proposed protocol finds a predetermined number of CHs in such way that they form one-hop clusters. The goal of the proposed protocol is to enhance the network's energy efficiency, data delivery reliability and the protocol's scalability. The formulated problem has been solved using three evolutionary approaches: Genetic Algorithms (GA), Differential Evolution (DE) and Particle Swarm Optimization (PSO) and we assessed each of their performance. Then, a PSO-based hierarchical clustering protocol that forms two-hop clusters is proposed to investigate the effect of the number of CHs on network's energy efficiency. This protocol enhances the WSN's energy efficiency by setting an upper bound on the number of CHs and trying to minimize the number of CHs compared to that upper bound. It also maximizes the protocol's scalability by using two-hop communication between the sensor nodes and their respective CHs. Then, a centralized weighted-sum PSO-based protocol is proposed for finding the optimal inter-cluster routing tree that connects the CHs to the Base Station (BS). This protocol is appropriate when the CHs are predetermined in advance. The proposed protocol uses a particle encoding scheme and defines an objective function to find the optimal routing tree. The objective function is used to build the trade-off between the energy-efficiency and data delivery reliability of the constructed tree. Finally, a centralized multi-objective Pareto-optimization approach is adapted to find the optimal network configuration that includes both the optimal set of CHs and the optimal routing tree. A new individual encoding scheme that represents a joint solution for both the clustering and routing problems in WSNs is proposed. The proposed protocol uses a variable number of CHs, and its objective is to assign each network node to its respective CH and each CH to its respective next hop. The joint problem of clustering and routing in WSNs is formulated as a multi-objective minimization problem with a variable number of CHs, aiming at determining an energy efficient, reliable ( in terms of data delivery) and scalable clustering and routing scheme. The formulated problem has been solved using two state-of-the-art Multi-Objective Evolutionary Algorithms (MOEA), and their performance has been compared. The proposed protocols were developed under realistic network settings. No assumptions were made about the nodes' location awareness or transmission range capabilities. The proposed protocols were tested using a realistic energy consumption model that is based on the characteristics of the Chipcon CC2420 radio transceiver data sheet. Extensive simulations on 50 homogeneous and heterogeneous WSN models were evaluated and compared against well-known cluster-based sensor network protocols.

Wireless networks enter a new era in which various objects, such as mobile phones, computers, vehicles, watches, are automatically and intelligently connected to provide ubiquitous services. Green communication protocols are required to save energy consumption and improve transmission performance. MAC protocols can detect the signal status and energy consumptions of physical channels to adapt to the dynamic wireless conditions. They can also provide node-to-node transmissions for network layer protocols under green wireless networks. The thesis presents three energy efficient communication solutions under different delay-tolerant networks scenarios to study the efficiency of MAC transmission protocols within wireless networks: CPMAC, AFLAS and TREE. CPMAC applies three energy-aware algorithms to transmit different quality requirements of data within one contact interval in sparsely connected sensor networks. Simulations and analysis shows CPMAC outperforms two other important MAC protocols in wireless sensor networks and vehicular ad-hoc networks in throughput, delay, energy consumption. AFLAS uses an adaptive frame length aggregation scheme for Vehicular Networks that is designed to improve transmission efficiency and increase data throughput. Suitable aggregation frame lengths are calculated according to the current wireless status, and applied in the MAC layer at the onset of data transmissions to save overhead and energy consumption. The simulations of AFLAS exhibit a significant improvement results in data throughput, retransmissions, overheads and transmission efficiency in comparison to non-adaptive aggregation schemes. TRaffic adaptive Energy Efficient MAC protocol (TREE) adapts its work modes: reservation and contention mode, to traffic density and adjusts its duty cycle to achieve energy efficiency. TREE demonstrates better performance in terms of energy efficiency and traffic adaptability than the schedule-based MAC protocol TDMA, the contention-based protocol CSMA and the traffic adaptive protocol TRAMA under mobile sensor network environments. By studying and designing MAC protocols in wireless environments, the thesis shows the comprehensive knowledge and principles of communication protocol designs with latency relaxed. Future work is discussed for further designs and implementations of green communication protocols.

Abstract Multiple-input multiple-output (MIMO) and cognitive radio (CR) are key techniques for present and future high-speed wireless technologies. On the other hand, there are rising energy costs and greenhouse emissions associated with the provision of high-speed wireless communications. Consequently, the design of high-speed energy efficient systems is paramount for next-generation wireless systems. This thesis studies energy-efficient antenna selection for spatial multiplexing multiple-antenna systems from a cross-layer perspective, contrary to the norm, where physical-layer energy efficiency metrics are optimized. The enhanced system performance achieved by cross-layer designs in wireless networks motivates this research. The aim of the thesis is to propose and analyze novel cross-layer energy-efficient transmit antenna selection schemes that enhance energy efficiency and system performance - with regard to throughput, transmission latency, packet error rate and receiver buffer requirements. Firstly, this thesis derives the analytical expression for data link throughput for point-to-point spatial multiplexing multiple-antenna systems - which include MIMO and underlay CR MIMO systems - equipped with linear receivers with N-process stop-and-wait (N-SAW) as the automatic repeat request (ARQ) protocol. The performance of cross-layer transmit antenna selection, which maximizes the derived throughput metric, is then analyzed. The impact of packet size, number of SAW processes and the stalling of packets inside the receiver reordering buffer is considered in the investigation. The results show that the cross-layer approach, which takes into account system characteristics at both the data link and physical layers, has superior performance in comparison with the conventional physical-layer approach, which optimizes capacity. Secondly, this thesis proposes a cross-layer energy efficiency metric, based on the derived system throughput. Energy-efficient transmit antenna selection for spatial multiplexing MIMO systems, which maximizes the proposed cross-layer energy efficiency metric, by jointly optimizing the transmit antenna subset and transmit power, subject to spectral efficiency and transmit power constraints, is then introduced and analyzed. Additionally, adaptive modulation is incorporated into the proposed cross-layer scheme to enhance system performance. Cross-layer energyefficient transmit antenna selection for underlay CR MIMO systems, where interference constraints now come into play, is then considered. Lastly, this thesis develops novel reduced complexity versions of the proposed cross-layer energyefficient transmit antenna selection schemes - along with detailed complexity analysis - which shows that the proposed cross-layer approach attains significant energy efficiency and performance gains at affordable computational complexity.

Next Generation Wireless Networks (NGWNs) are envisaged to be heterogeneous. They will integrate multiple Radio Access Technologies (RATs) on the same platform where the RAT s are expected to work together in a coordinated fashion. Radio resources will therefore be jointly managed. Joint Call Admission Control (JCAC) approach has been adopted to jointly allocate or handle the radio resources amongst the different RATs in an NGWN. A number of JCAC algorithms have been proposed in the literature with the objective of enabling efficient utilisation of the radio resources and ensuring that required QoS requirements are met . However, studies in JCAC have not typically considered the revenue obtained by network operators in NGWNs . With the implementation of NGWNs, user demand for network services is expected to significantly increase. Consequently, one of the challenges envisaged in the NGWNs for network operators is a large decoupling between users' traffic and the revenue obtained . Therefore, it is important to analyse the network operators' revenue in NGWN s and devise means to ensure that sufficient revenue is obtained. This research analyses network operators' revenue in a heterogeneous network environment while maintaining QoS by incorporating pricing in JCAC. An analytical model based on a multi-dimensional Markov decision process is used to model JCAC algorithm in an NGWN. The JCAC algorithm used is load-based whereby calls arriving in the network are admitted to the least loaded RATs. The performance of the algorithm is evaluated using MATLAB. The analysed NGWN consists of two RATs and two service classes. QoS performance is measured with connection-level QoS metrics namely call blocking probability and call dropping probability. Other investigated performance metrics are average number of calls in the systems, user utility and revenue obtained. Performance of the NGWN is carried out with a dynamic pricing scheme incorporated in JCAC. A discount approach is applied to determine new price under the dynamic pricing scheme. User behaviour with price variation is impacted by change of call arrival rate and average call duration. Simulations are also carried out with flat pricing for comparison purposes. The results obtained show that better system performance and high revenue for network operators are obtained with the dynamic pricing scheme. Furthermore, a hybrid pricing model is proposed whereby flat and dynamic pricing schemes are integrated, giving users flexibility of choosing an appropriate pricing scheme. The analysis is conducted with different percentages of users opting for either dynamic or flat pricing schemes. Simulation results show that higher user utility and improved QoS performance are obtained with the hybrid pricing model. Additionally, reasonable operators' revenue is guaranteed with the hybrid pricing model.

The current decade has witnessed a phenomenal growth in mobile wireless communication networks and subscribers. In 2015, mobile wireless devices and connections were reported to have grown to about 7.9 billion, exceeding human population. The explosive growth in mobile wireless communication network subscribers has created a huge demand for wireless network capacity, ubiquitous wireless network coverage, and enhanced Quality of Service (QoS). These demands have led to several challenging problems for wireless communication networks operators and designers. The Next Generation Wireless Networks (NGWNs) will support high mobility communications, such as communication in high-speed rails. Mobile users in such high mobility environment demand reliable QoS, however, such users are plagued with a poor signal-tonoise ratio, due to the high vehicular penetration loss, increased transmission outage and handover information overhead, leading to poor QoS provisioning for the networks' mobile users. Providing a reliable QoS for high mobility users remains one of the unique challenges for NGWNs. The increased wireless network capacity and coverage of NGWNs means that mobile communication users at the cell-edge should have enhanced network performance. However, due to path loss (path attenuation), interference, and radio background noise, mobile communication users at the cell-edge can experience relatively poor transmission channel qualities and subsequently forced to transmit at a low bit transmission rate, even when the wireless communication networks can support high bit transmission rate. Furthermore, the NGWNs are envisioned to be Heterogeneous Wireless Networks (HWNs). The NGWNs are going to be the integration platform of diverse homogeneous wireless communication networks for a convergent wireless communication network. The HWNs support single and multiple calls (group calls), simultaneously. Decision making is an integral core of radio resource management. One crucial decision making in HWNs is network selection. Network selection addresses the problem of how to select the best available access network for a given network user connection. For the integrated platform of HWNs to be truly seamless and efficient, a robust and stable wireless access network selection algorithm is needed. To meet these challenges for the different mobile wireless communication network users, the NGWNs will have to provide a great leap in wireless network capacity, coverage, QoS, and radio resource utilization. Moving wireless communication networks (mobile hotspots) have been proposed as a solution to providing reliable QoS to high mobility users. In this thesis, an Adaptive Thinning Mobility Aware (ATMA) Call Admission Control (CAC) algorithm for improving the QoS and radio resource utilization of the mobile hotspot networks, which are of critical importance for communicating nodes in moving wireless networks is proposed. The performance of proposed ATMA CAC scheme is investigated and compare it with the traditional CAC scheme. The ATMA scheme exploits the mobility events in the highspeed mobility communication environment and the calls (new and handoff calls) generation pattern to enhance the QoS (new call blocking and handoff call dropping probabilities) of the mobile users. The numbers of new and handoff calls in wireless communication networks are dynamic random processes that can be effectively modeled by the Continuous Furthermore, the NGWNs are envisioned to be Heterogeneous Wireless Networks (HWNs). The NGWNs are going to be the integration platform of diverse homogeneous wireless communication networks for a convergent wireless communication network. The HWNs support single and multiple calls (group calls), simultaneously. Decision making is an integral core of radio resource management. One crucial decision making in HWNs is network selection. Network selection addresses the problem of how to select the best available access network for a given network user connection. For the integrated platform of HWNs to be truly seamless and efficient, a robust and stable wireless access network selection algorithm is needed. To meet these challenges for the different mobile wireless communication network users, the NGWNs will have to provide a great leap in wireless network capacity, coverage, QoS, and radio resource utilization. Moving wireless communication networks (mobile hotspots) have been proposed as a solution to providing reliable QoS to high mobility users. In this thesis, an Adaptive Thinning Mobility Aware (ATMA) Call Admission Control (CAC) algorithm for improving the QoS and radio resource utilization of the mobile hotspot networks, which are of critical importance for communicating nodes in moving wireless networks is proposed.

In heterogeneous wireless networks (HWNs), both single-homed and multi-homed terminals are supported to provide connectivity to users. A multiservice single-homed multi-mode terminal can support multiple types of services, such as voice call, file download and video streaming simultaneously on any one of the available radio access technologies (RATs) such as Wireless Local Area Network (WLAN), and Long Term Evolution (LTE). Consequently, a single-homed multi-mode terminal having multiple on-going calls may need to perform a vertical handover from one RAT to another. One of the major issues in HWNs is how to select the most suitable RAT for multiple handoff calls, and the selection of a suitable RAT for multiple-calls from a single-homed multi-mode terminal in HWNs is a group decision problem. This is because a single-homed multi-mode terminal can connect to only one RAT at a time, and therefore multiple handoff calls from the terminal have to be handed over to the same RAT. In making group decision for multiple-calls, the quality of service (QoS) requirements for individual calls needs to be considered. Thus, the RAT that most satisfies the QoS requirements of individual calls is selected as the most suitable RAT for the multiple-calls. Whereas most research efforts in HWNs have concentrated on developing vertical handoff decision schemes for a single call from a multi-mode terminal, not much has been reported in the literature on RAT-selection for multiple-calls from a single-homed multi-mode terminal in next generation wireless networks (NGWNs). In addition, not much has been done to investigate the sensitivity of RAT-selection criteria for multiple-calls in NGWNs. Therefore, this dissertation addresses these issues by focusing on following two main aspects: (1) comparative analysis of four candidate multi-criteria group decision-making (MCGDM) schemes that could be adapted for making RAT-selection decisions for multiple-calls, and (2) development of a new RAT-selection scheme named the consensus RAT-selection model. In comparative analysis of the candidate RAT-selection schemes, four MCGDM schemes namely: distance to the ideal alternative-group decision making (DIA-GDM), multiplicative exponent weighting-group decision making (MEW-GDM), simply additive weighting-group decision making (SAW-GDM), technique for order preference by similarity to Ideal solution-group decision making (TOPSIS-GDM) are considered. The performance of the multiple-calls RAT-selection schemes is evaluated using the MATLAB simulation tool. The results show that DIA-GDM and TOPSIS-GDM schemes are more suitable for multiple handoff calls than SAW-GDM and MEW-GDM schemes. This is because they are consistent and less-sensitive in making RAT-selection decision than the other two schemes, with regards to RAT-selection criteria (service price, data rate, security, battery power consumption and network delay) in HWNs. In addition, the newly developed RAT-selection scheme incorporates RAT-consensus level for improving RAT-selection decisions for multiple-calls. Numerical results conducted in MATLAB validate the effectiveness and performance of the newly proposed RAT-selection scheme for multiple-calls in HWNs.

Wireless Sensor Networks (WSNs) have been applied to a wide range of application areas, including battle fields, transportation systems, and hospitals. The security issues in WSNs are still hot research topics. The constrained capabilities of sensors and the environments in which sensors are deployed, such as hostile and non-reachable areas, make the security more complicated. This dissertation describes the development and testing of a novel two-phase security mechanism for hierarchical WSNs that is capable of defending both outside and inside attacks. For the outside attacks, the attackers are usually malicious intruders that entered the network. The computation and communication capabilities of the sensors restrict them from directly defending the harmful intruders by performing traditionally encryption, authentication, or other cryptographic operations. However, the sensors can assist the more powerful nodes in a hierarchical structured WSN to track down these intruders and thereby prevent further damage. To fundamentally improve the security of a WSN, a multi-target tracking algorithm is developed to track the intruders. For the inside attacks, the attackers are compromised insiders. The intruders manipulate these insiders to indirectly attack other sensors. Therefore, detecting these malicious insiders in a timely manner is important to improve the security of a network. In this dissertation, we mainly focus on detecting the malicious insiders that try to break the normal communication among sensors, which creates holes in the WSN. As the malicious insiders attempt to break the communication by actively using HELLO flooding attack, we apply an immune-inspired algorithm called Dendritic Cell Algorithm (DCA) to detect this type of attack. If the malicious insiders adopt a subtle way to break the communication by dropping received packets, we implement another proposed technique, a short-and-safe routing (SSR) protocol to prevent this type of attack. The designed security mechanism can be applied to different sizes of both static and dynamic WSNs. We adopt a popular simulation tool, ns-2, and a numerical computing environment, MATLAB, to analyze and compare the computational complexities of the proposed security mechanism. Simulation results demonstrate effective performance of the developed corrective and preventive security mechanisms on detecting malicious nodes and tracking the intruders.

In this paper, we present a comprehensive performance evaluation of TCP NewReno and TCP Vegas with and without ACK thinning for static multihop wireless IEEE 802.11 networks. Opposed to previous studies, we consider not only IEEE 802.11 operating in ad hoc mode with 2 Mbit/s bandwidth, but also with 5.5 Mbit/s and 11 Mbit/s bandwidths. Simulation results using ns-2 show that TCP Vegas achieves between 15% and 83% more goodput and between 57% and 99% fewer packet retransmissions than TCP NewReno. Considering fairness among multiple TCP flows, we show that using TCP Vegas results in between 21% and 95% fairness improvement compared to TCP NewReno. The reduced amount of packet retransmissions of TCP Vegas also leads to significant savings of energy consumption. The paper gives insight on the particular reasons for such performance advantages of TCP Vegas in comparison to TCP NewReno.