Forewarding in Mobile Opportunistic Networks

Recent advances in processor speeds, mobile communications and battery life have enabled computers to evolve from completely wired to completely mobile. In the most extreme case, all nodes are mobile and communication takes place at available opportunities – using both traditional communication infrastructure as well as the mobility of intermediate nodes. These are mobile opportunistic networks. Data communication in such networks is a difficult problem, because of the dynamic underlying topology, the scarcity of network resources and the lack of global information. Establishing end-to-end routes in such networks is usually not feasible. Instead a store-and-carry forwarding paradigm is better suited for such networks. This dissertation describes and analyzes algorithms for forwarding of messages in such networks. In order to design effective forwarding algorithms for mobile opportunistic networks, we start by first building an understanding of the set of all paths between nodes, which represent the available opportunities for any forwarding algorithm. Relying on real measurements, we enumerate paths between nodes and uncover what we refer to as the path explosion effect. The term path explosion refers to the fact that the number of paths between a randomly selected pair of nodes increases exponentially with time. We draw from the theory of epidemics to model and explain the path explosion effect. This is the first contribution of the thesis, and is a key observation that underlies subsequent results. Our second contribution is the study of forwarding algorithms. For this, we rely on trace driven simulations of different algorithms that span a range of design dimensions. We compare the performance (success rate and average delay) of these algorithms. We make the surprising observation that most algorithms we consider have roughly similar performance. We explain this result in light of the path explosion phenomenon. While the performance of most algorithms we studied was roughly the same, these algorithms differed in terms of cost. This prompted us to focus on designing algorithms with the explicit intent of reducing costs. For this, we cast the problem of forwarding as an optimal stopping problem. Our third main contribution is the design of strategies based on optimal stopping principles which we refer to as Delegation schemes. Our analysis shows that using a delegation scheme reduces cost over naive forwarding by a factor of O(√N), where N is the number of nodes in the network. We further validate this result on real traces, where the cost reduction observed is even greater. Our results so far include a key assumption, which is unbounded buffers on nodes. Next, we relax this assumption, so that the problem shifts to one of prioritization of messages for transmission and dropping. Our fourth contribution is the study of message prioritization schemes, combined with forwarding. Our main result is that one achieves higher performance by assigning higher priorities to young messages in the network. We again interpret this result in light of the path explosion effect.

Spatial Pattern Learning, Catastophic Forgetting and Optimal Rules of Synaptic Transmission

It is a neural network truth universally acknowledged, that the signal transmitted to a target node must be equal to the product of the path signal times a weight. Analysis of catastrophic forgetting by distributed codes leads to the unexpected conclusion that this universal synaptic transmission rule may not be optimal in certain neural networks. The distributed outstar, a network designed to support stable codes with fast or slow learning, generalizes the outstar network for spatial pattern learning. In the outstar, signals from a source node cause weights to learn and recall arbitrary patterns across a target field of nodes. The distributed outstar replaces the outstar source node with a source field, of arbitrarily many nodes, where the activity pattern may be arbitrarily distributed or compressed. Learning proceeds according to a principle of atrophy due to disuse whereby a path weight decreases in joint proportion to the transmittcd path signal and the degree of disuse of the target node. During learning, the total signal to a target node converges toward that node's activity level. Weight changes at a node are apportioned according to the distributed pattern of converging signals three types of synaptic transmission, a product rule, a capacity rule, and a threshold rule, are examined for this system. The three rules are computationally equivalent when source field activity is maximally compressed, or winner-take-all when source field activity is distributed, catastrophic forgetting may occur. Only the threshold rule solves this problem. Analysis of spatial pattern learning by distributed codes thereby leads to the conjecture that the optimal unit of long-term memory in such a system is a subtractive threshold, rather than a multiplicative weight.

Practical wireless sensor networks power consumption metrics for building energy management applications

The power consumption of wireless sensor networks (WSN) module is an important practical concern in building energy management (BEM) system deployments. A set of metrics are created to assess the power profiles of WSN in real world condition. The aim of this work is to understand and eventually eliminate the uncertainties in WSN power consumption during long term deployments and the compatibility with existing and emerging energy harvesting technologies. This paper investigates the key metrics in data processing, wireless data transmission, data sensing and duty cycle parameter to understand the system power profile from a practical deployment prospective. Based on the proposed analysis, the impacts of individual metric on power consumption in a typical BEM application are presented and the subsequent low power solutions are investigated.

Phase estimation receiver for full-field detection: a novel receiver structure for electronic dispersion compensation of metropolitan area networks

The development of ultra high speed (~20 Gsamples/s) analogue to digital converters (ADCs), and the delayed deployment of 40 Gbit/s transmission due to the economic downturn, has stimulated the investigation of digital signal processing (DSP) techniques for compensation of optical transmission impairments. In the future, DSP will offer an entire suite of tools to compensate for optical impairments and facilitate the use of advanced modulation formats. Chromatic dispersion is a very significant impairment for high speed optical transmission. This thesis investigates a novel electronic method of dispersion compensation which allows for cost-effective accurate detection of the amplitude and phase of the optical field into the radio frequency domain. The first electronic dispersion compensation (EDC) schemes accessed only the amplitude information using square law detection and achieved an increase in transmission distances. This thesis presents a method by using a frequency sensitive filter to estimate the phase of the received optical field and, in conjunction with the amplitude information, the entire field can be digitised using ADCs. This allows DSP technologies to take the next step in optical communications without requiring complex coherent detection. This is of particular of interest in metropolitan area networks. The full-field receiver investigated requires only an additional asymmetrical Mach-Zehnder interferometer and balanced photodiode to achieve a 50% increase in EDC reach compared to amplitude only detection.

Analysis and optimisation of semiconductor reflective modulators for optical networks

Reflective modulators based on the combination of an electroabsorption modulator (EAM) and semiconductor optical amplifier (SOA) are attractive devices for applications in long reach carrier distributed passive optical networks (PONs) due to the gain provided by the SOA and the high speed and low chirp modulation of the EAM. Integrated R-EAM-SOAs have experimentally shown two unexpected and unintuitive characteristics which are not observed in a single pass transmission SOA: the clamping of the output power of the device around a maximum value and low patterning distortion despite the SOA being in a regime of gain saturation. In this thesis a detailed analysis is carried out using both experimental measurements and modelling in order to understand these phenomena. For the first time it is shown that both the internal loss between SOA and R-EAM and the SOA gain play an integral role in the behaviour of gain saturated R-EAM-SOAs. Internal loss and SOA gain are also optimised for use in a carrier distributed PONs in order to access both the positive effect of output power clamping, and hence upstream dynamic range reduction, combined with low patterning operation of the SOA Reflective concepts are also gaining interest for metro transport networks and short reach, high bit rate, inter-datacentre links. Moving the optical carrier generation away from the transmitter also has potential advantages for these applications as it avoids the need for cooled photonics being placed directly on hot router line-cards. A detailed analysis is carried out in this thesis on a novel colourless reflective duobinary modulator, which would enable wavelength flexibility in a power-efficient reflective metro node.

Efficient delivery of scalable media streaming over lossy networks

Recent years have witnessed a rapid growth in the demand for streaming video over the Internet, exposing challenges in coping with heterogeneous device capabilities and varying network throughput. When we couple this rise in streaming with the growing number of portable devices (smart phones, tablets, laptops) we see an ever-increasing demand for high-definition videos online while on the move. Wireless networks are inherently characterised by restricted shared bandwidth and relatively high error loss rates, thus presenting a challenge for the efficient delivery of high quality video. Additionally, mobile devices can support/demand a range of video resolutions and qualities. This demand for mobile streaming highlights the need for adaptive video streaming schemes that can adjust to available bandwidth and heterogeneity, and can provide us with graceful changes in video quality, all while respecting our viewing satisfaction. In this context the use of well-known scalable media streaming techniques, commonly known as scalable coding, is an attractive solution and the focus of this thesis. In this thesis we investigate the transmission of existing scalable video models over a lossy network and determine how the variation in viewable quality is affected by packet loss. This work focuses on leveraging the benefits of scalable media, while reducing the effects of data loss on achievable video quality. The overall approach is focused on the strategic packetisation of the underlying scalable video and how to best utilise error resiliency to maximise viewable quality. In particular, we examine the manner in which scalable video is packetised for transmission over lossy networks and propose new techniques that reduce the impact of packet loss on scalable video by selectively choosing how to packetise the data and which data to transmit. We also exploit redundancy techniques, such as error resiliency, to enhance the stream quality by ensuring a smooth play-out with fewer changes in achievable video quality. The contributions of this thesis are in the creation of new segmentation and encapsulation techniques which increase the viewable quality of existing scalable models by fragmenting and re-allocating the video sub-streams based on user requirements, available bandwidth and variations in loss rates. We offer new packetisation techniques which reduce the effects of packet loss on viewable quality by leveraging the increase in the number of frames per group of pictures (GOP) and by providing equality of data in every packet transmitted per GOP. These provide novel mechanisms for packetizing and error resiliency, as well as providing new applications for existing techniques such as Interleaving and Priority Encoded Transmission. We also introduce three new scalable coding models, which offer a balance between transmission cost and the consistency of viewable quality.

An energy-efficient data delivery scheme for delay-sensitive traffic in wireless sensor networks

We propose a novel data-delivery method for delay-sensitive traffic that significantly reduces the energy consumption in wireless sensor networks without reducing the number of packets that meet end-to-end real-time deadlines. The proposed method, referred to as SensiQoS, leverages the spatial and temporal correlation between the data generated by events in a sensor network and realizes energy savings through application-specific in-network aggregation of the data. SensiQoS maximizes energy savings by adaptively waiting for packets from upstream nodes to perform in-network processing without missing the real-time deadline for the data packets. SensiQoS is a distributed packet scheduling scheme, where nodes make localized decisions on when to schedule a packet for transmission to meet its end-to-end real-time deadline and to which neighbor they should forward the packet to save energy. We also present a localized algorithm for nodes to adapt to network traffic to maximize energy savings in the network. Simulation results show that SensiQoS improves the energy savings in sensor networks where events are sensed by multiple nodes, and spatial and/or temporal correlation exists among the data packets. Energy savings due to SensiQoS increase with increase in the density of the sensor nodes and the size of the sensed events. © 2010 Harshavardhan Sabbineni and Krishnendu Chakrabarty.

Computational inference of neural information flow networks.

Determining how information flows along anatomical brain pathways is a fundamental requirement for understanding how animals perceive their environments, learn, and behave. Attempts to reveal such neural information flow have been made using linear computational methods, but neural interactions are known to be nonlinear. Here, we demonstrate that a dynamic Bayesian network (DBN) inference algorithm we originally developed to infer nonlinear transcriptional regulatory networks from gene expression data collected with microarrays is also successful at inferring nonlinear neural information flow networks from electrophysiology data collected with microelectrode arrays. The inferred networks we recover from the songbird auditory pathway are correctly restricted to a subset of known anatomical paths, are consistent with timing of the system, and reveal both the importance of reciprocal feedback in auditory processing and greater information flow to higher-order auditory areas when birds hear natural as opposed to synthetic sounds. A linear method applied to the same data incorrectly produces networks with information flow to non-neural tissue and over paths known not to exist. To our knowledge, this study represents the first biologically validated demonstration of an algorithm to successfully infer neural information flow networks.

Access Point Association Coordination in Densely Deployed 802.11 Wireless Networks

Dense deployment of wireless local area network (WLAN) access points (APs) is an important part of the next generation Wi-Fi and standardization (802.11ax) efforts are underway. Increasing demand for WLAN connectivity motivates such dense deployments, especially in geographical areas with large numbers of users, such as stadiums, large enterprises, multi-tenant buildings, and urban cities. Although densification of WLAN APs guarantees coverage, it is susceptible to increased interference and uncoordinated association of stations (STAs) to APs, which degrade network throughput. Therefore, to improve network throughput, algorithms are proposed in this thesis to optimally coordinate AP associations in the presence of interference. In essence, coordination of APs in dense WLANs (DWLANs) is achieved through coordination of STAs' associations with APs. While existing approaches suggest tuning of APs' beacon powers or using transmit power control (TPC) for association control, here, the signal-to-interference-plus-noise ratio (SINRs) of STAs and the clear channel assessment (CCA) threshold of the 802.11 MAC protocol are employed. The proposed algorithms in this thesis enhance throughput and minimize coverage holes inherent in cell breathing and TPC techniques by not altering the transmit powers of APs, which determine cell coverage. Besides uncoordinated AP associations, unnecessary frequent transmission deferment is envisaged as another problem in DWLANs due to the clear channel assessment aspect of the carrier sensing multiple access collision avoidance (CSMA/CA) scheme in 802.11 standards and the short spatial reuse distance between co-channel APs. To address this problem in addition to AP association coordination, an algorithm is proposed for CCA threshold adjustment in each AP cell, such that CCA threshold used in one cell mitigates transmission deferment in neighboring cells. Performance evaluation reveals that the proposed association optimization algorithms achieve significant gain in throughput when compared with the default strongest signal first (SSF) association scheme in the current 802.11 standard. Also, further gain in throughput is observed when the CCA threshold adjustment is combined with the optimized association. Results show that when STA-AP association is optimized and CCA threshold is adjusted in each cell, throughput improves. Finally, transmission delay and the number of packet re-transmissions due to collision and contention significantly decrease.

Transmission line matching effects on the performance of shunt-C/series-tuned and series-L/parallel-tuned Class-E amplifiers

The impact that the transmission-line load-network has on the performance of the recently introduced series-L/parallel-tuned Class-E amplifier and the classic shunt-C/series-tuned configuration when compared to optimally derived lumped load networks is discussed. In addition an improved load topology which facilitates harmonic suppression of up to 5 order as required for maximum Class-E efficiency as well as load resistance transformation and a design procedure involving the use of Kuroda's identity and Richard's transformation enable a distributed synthesis process which dispenses with the need for iterative tuning as previously required in order to achieve optimum Class-E operation. © 2005 IEEE.

Modeling energy consumption in error-prone IEEE 802.11-based wireless ad-hoc networks

In the IEEE 802.11 MAC layer protocol, there are different trade-off points between the number of nodes competing for the medium and the network capacity provided to them. There is also a trade-off between the wireless channel condition during the transmission period and the energy consumption of the nodes. Current approaches at modeling energy consumption in 802.11 based networks do not consider the influence of the channel condition on all types of frames (control and data) in the WLAN. Nor do they consider the effect on the different MAC and PHY schemes that can occur in 802.11 networks. In this paper, we investigate energy consumption corresponding to the number of competing nodes in IEEE 802.11's MAC and PHY layers in error-prone wireless channel conditions, and present a new energy consumption model. Analysis of the power consumed by each type of MAC and PHY over different bit error rates shows that the parameters in these layers play a critical role in determining the overall energy consumption of the ad-hoc network. The goal of this research is not only to compare the energy consumption using exact formulae in saturated IEEE 802.11-based DCF networks under varying numbers of competing nodes, but also, as the results show, to demonstrate that channel errors have a significant impact on the energy consumption.

A programmable architecture for layered multimedia streams in IPv6 networks

A new configurable architecture is presented that offers multiple levels of video playback by accommodating variable levels of network utilization and bandwidth. By utilizing scalable MPEG-4 encoding at the network edge and using specific video delivery protocols, media streaming components are merged to fully optimize video playback for IPv6 networks, thus improving QoS. This is achieved by introducing “programmable network functionality” (PNF) which splits layered video transmission and distributes it evenly over available bandwidth, reducing packet loss and delay caused by out-of-profile DiffServ classes. An FPGA design is given which gives improved performance, e.g. link utilization, end-to-end delay, and that during congestion, improves on-time delivery of video frames by up to 80% when compared to current “static” DiffServ.

Capacity and resource allocation of cooperative MIMO in ad hoc networks

Cooperative MIMO (Multiple Input–Multiple Output) allows multiple nodes share their antennas to emulate antenna arrays and transmit or receive cooperatively. It has the ability to increase the capacity for future wireless communication systems and it is particularly suited for ad hoc networks. In this study, based on the transmission procedure of a typical cooperative MIMO system, we first analyze the capacity of single-hop cooperative MIMO systems, and then we derive the optimal resource allocation strategy to maximize the end-to-end capacity in multi-hop cooperative MIMO systems. The study shows three implications. First, only when the intra-cluster channel is better than the inter-cluster channel, cooperative MIMO results in a capacity increment. Second, for a given scenario there is an optimal number of cooperative nodes. For instance, in our study an optimal deployment of three cooperative nodes achieve a capacity increment of 2 bps/Hz when compared with direct transmission. Third, an optimal resource allocation strategy plays a significant role in maximizing end-to-end capacity in multi-hop cooperative MIMO systems. Numerical results show that when optimal resource allocation is applied we achieve more than 20% end-to-end capacity increment in average when compared with an equal resource allocation strategy.

Analysis and Design of Class-E3F and Transmission-Line Class-E3F2 Power Amplifiers

In this paper, analysis and synthesis approach for two new variants within the Class-EF power amplifier (PA) family is elaborated. These amplifiers are classified here as Class-E3 F2 and transmission-line (TL) Class-E3 F 2. The proposed circuits offer means to alleviate some of the major issues faced by existing topologies such as substantial power losses due to the parasitic resistance of the large inductor in the Class-EF load network and deviation from ideal Class-EF operation due to the effect of device output inductance at high frequencies. Both lumped-element and transmission-line load networks for the Class-E 3 F PA are described. The load networks of the Class-E3 F and TL Class-E 3 F2amplifier topologies developed in this paper simultaneously satisfy the Class-EF optimum impedance requirements at fundamental frequency, second, and third harmonics as well as simultaneously providing matching to the circuit optimum load resistance for any prescribed system load resistance. Optimum circuit component values are analytically derived and validated by harmonic balance simulations. Trade-offs between circuit figures of merit and component values with some practical limitations being considered are discussed. © 2010 IEEE.

Novel Radio Link Buffer Management Schemes for End-User Multi-class Traffic in High Speed Packet Access Networks

The requirement to provide multimedia services with QoS support in mobile networks has led to standardization and deployment of high speed data access technologies such as the High Speed Downlink Packet Access (HSDPA) system. HSDPA improves downlink packet data and multimedia services support in WCDMA-based cellular networks. As is the trend in emerging wireless access technologies, HSDPA supports end-user multi-class sessions comprising parallel flows with diverse Quality of Service (QoS) requirements, such as real-time (RT) voice or video streaming concurrent with non real-time (NRT) data service being transmitted to the same user, with differentiated queuing at the radio link interface. Hence, in this paper we present and evaluate novel radio link buffer management schemes for QoS control of multimedia traffic comprising concurrent RT and NRT flows in the same HSDPA end-user session. The new buffer management schemes—Enhanced Time Space Priority (E-TSP) and Dynamic Time Space Priority (D-TSP)—are designed to improve radio link and network resource utilization as well as optimize end-to-end QoS performance of both RT and NRT flows in the end-user session. Both schemes are based on a Time-Space Priority (TSP) queuing system, which provides joint delay and loss differentiation between the flows by queuing (partially) loss tolerant RT flow packets for higher transmission priority but with restricted access to the buffer space, whilst allowing unlimited access to the buffer space for delay-tolerant NRT flow but with queuing for lower transmission priority. Experiments by means of extensive system-level HSDPA simulations demonstrates that with the proposed TSP-based radio link buffer management schemes, significant end-to-end QoS performance gains accrue to end-user traffic with simultaneous RT and NRT flows, in addition to improved resource utilization in the radio access network.