O comportamento dinâmico das redes sem fio as torna muito peculiares e de difícil análise. No entanto, algumas destas redes, como as de sensores com funcionamento intermitente, redes periódicas ou cíclicas e as do sistema de satélites de órbita baixa têm um comportamento dinâmico relativamente previsível, pois as variações da topologia da rede no tempo são quase que determinísticas. Recentemente, um modelo teórico -- grafos evolutivos -- foi proposto com o intuito de capturar o comportamento dinâmico destas redes e formalizar algoritmos de roteamento de custo mínimo, além de outros. Os algoritmos e idéias obtidos com este modelo são teoricamente muito eficientes, mas, no entanto, antes deste trabalho não existiam estudos do uso destes modelos em situações práticas. Assim, o objetivo deste trabalho é analisar a aplicabilidade da teoria de grafos evolutivos na construção de protocolos de roteamento eficientes em cenários realistas. Foram implementados dois protocolos de roteamento para redes móveis ad hoc baseados nos algoritmos de grafos evolutivos, são eles: Jornada que Chega Mais Cedo e Jornada Mais Curta. Extensivas simulações foram realizadas utilizando o simulador de redes NS2 e os resultados foram comparados com outros quatro protocolos clássicos para este tipo de rede: AODV, DSR, OLSR e DSDV. Os resultados preliminares mostram que este recente modelo tem muito potencial para ser uma ferramenta poderosa no desenvolvimento e análise de algoritmos para redes dinâmicas com comportamento previsível. No entanto, foram apontados alguns aspectos que precisam ser melhores estudados para que estes algoritmos possam ser utilizados em situações reais. / The assessment of routing protocols for wireless networks is a difficult task, because of the networks\' highly dynamic behavior and the absence of benchmarks. However, some of these networks, such as intermittent wireless sensors networks, periodic or cyclic networks, and low earth orbit satellites systems, have more predictable dynamics, as the temporal variations in the network topology are somehow deterministic, which may make them easier to study. Recently, a graph theoretic model -- the evolving graphs -- was proposed to help to capture the dynamic behavior of these networks, in view of the construction of least cost routing and other algorithms. The algorithms and insights obtained through this model are theoretically very efficient and intriguing. However, before this work there was no study on the use of such theoretical results into practical situations. Therefore, the objective of our work is to analyze the applicability of the evolving graph theory in the construction of efficient routing protocols in realistic scenarios. We use the NS2 network simulator to first implement two evolving graph based routing protocols: Foremost Journey and Shortest Journey, They are evaluated and compared to four major ad-hoc protocols: AODV, DSR, OLSR and DSDV. Interestingly, our experiments show that evolving graphs have all the potentials to be an effective and powerful tool in the development and analysis of algorithms for dynamic networks, with predictable dynamics at least. In order to make this model widely applicable, however, some practical issues still have to be addressed and incorporated into the model.

In this dissertation, we describe the portable, open-source distributed simulation framework (WINDS) targeting simulations of wireless network infrastructures that we have developed. We present the simulation framework which uses modular architecture and apply the framework to studies of mobility pattern effects, routing and intrusion detection mechanisms in simulations of large-scale wireless ad hoc, infrastructure, and totally mobile networks. The distributed simulations within the framework execute seamlessly and transparently to the user on a symmetric multiprocessor cluster computer or a network of computers with no modifications to the code or user objects. A visual graphical interface precisely depicts simulation object states and interactions throughout the simulation execution, giving the user full control over the simulation in real time. The network configuration is detected by the framework, and communication latency is taken into consideration when dynamically adjusting the simulation clock, allowing the simulation to run on a heterogeneous computing system. The simulation framework is easily extensible to multi-cluster systems and computing grids. An entire simulation system can be constructed in a short time, utilizing user-created and supplied simulation components, including mobile nodes, base stations, routing algorithms, traffic patterns and other objects. These objects are automatically compiled and loaded by the simulation system, and are available for dynamic simulation injection at runtime. Using our distributed simulation framework, we have studied modern intrusion detection systems (IDS) and assessed applicability of existing intrusion detection techniques to wireless networks. We have developed a mobile agent-based IDS targeting mobile wireless networks, and introduced load-balancing optimizations aimed at limited-resource systems to improve intrusion detection performance. Packet-based monitoring agents of our IDS employ a CASE-based reasoner engine that performs fast lookups of network packets in the existing SNORT-based intrusion rule-set. Experiments were performed using the intrusion data from MIT Lincoln Laboratories studies, and executed on a cluster computer utilizing our distributed simulation system.

Approved for public release; distribution is unlimited / The radio channel places fundamental limitations on the performance of mobile ad hoc wireless networks. In the mobile radio environment, fading due to multipath delay spread impairs received signals. The purpose of this thesis is to develop a radio channel model and examine the effect of various parameters on channel behavior that is representative of environments in which mobile ad hoc wireless networks operate. The various physical phenomena considered are outdoor environments, fading and multipath propagation, type of terrains, and mobility (Doppler shift). A channel model based on a Tapped Delay Line (TDL) structure was developed and implemented in the MATLAB programming language, and the performance of the time-varying channel was studied by plotting the signal constellations. The simulation results indicate that the number of taps required in the TDL is 8 or less and the carrier frequency did not influence the performance significantly. The Jakes Doppler spectrum should be used in urban environments with high mobility; the Gaussian Doppler spectrum is the choice for low mobility urban environments and for the hilly terrain under both low and high mobility. / Civilian, Singapore Ministry of Defense

An energy-aware on-demand Bluetooth scatternet formation and routing protocol taking into account network architecture and traffic pattern is proposed. The scatternet formation protocol is able to cope with multiple sources initiating traffic simultaneously as well as prolong network lifetime. A modified Inquiry scheme using extended ID packet is introduced for fast device discovery and power efficient propagation of route request messages with low delay. A mechanism employing POLL packets in Page processes is proposed to transfer scatternet formation and route reply information without extra overhead. In addition, the energy aware forwarding nodes selection scheme is based on local information and results in more uniform network resource utilization and improved network lifetime. Simulation results show that this protocol can provide scatternet formation with reasonable delay and with good load balance which results in prolonged network lifetime for Bluetooth-based wireless sensor networks. In this research, a metric-based scatternet formation algorithm for the Bluetooth-based sensor motes is presented. It optimizes the Bluetooth network formation from the hop distance and link quality perspectives. In addition, a smart repair mechanism is proposed to deal with link/node failure and recover the network connectivity promptly with low overhead. The experiments with the Intel Mote platform demonstrate the effectiveness of the optimizations. This research also investigates the scalability of ad hoc routing protocols in very large-scale wireless ad hoc networks. A comprehensive simulation study is conducted of the performance of an on-demand routing protocol on a very large-scale, with as many as 50,000 nodes in the network. The scalability analysis is addressed based on various network sizes, node density, traffic load, and mobility. The reasons for packet loss are analyzed and categorized at each network layer. Based on the observations, we observe the effect of the parameter selection and try to exhaust the scalability boundary of the on-demand routing protocol for wireless ad hoc networks.

An ad hoc wireless network is an infrastructure-less, autonomous system of nodes connected through wireless links. In many current applications of ad hoc wireless networks, individual wireless nodes are autonomous, rational, and intelligent and are often referred to as selfish nodes, following game theoretic terminology. In an ad hoc wireless network, a typical node may be an intermediate node of a route from a source node to a destination node and therefore is often required to forward packets so as to enable communication to be established. Selfish nodes may not always forward the packets since the forwarding activity consumes the node’s own resources. Such behavior by individual nodes may lead to suboptimal situations where nodes, through their actions, lead to a state that is undesirable from an overall network viewpoint. To counter this, there is a need to stimulate cooperation through methods such as providing appropriate incentives. In this thesis, our interest is in designing rigorous incentive based methods for stimulating cooperation among wireless nodes, in the specific context of broadcast. In particular, we address the Incentive Compatible Broadcast problem: how do we design broadcast protocols that induce truth revelation by the individual wireless nodes? We do this using a game theory and mechanism design framework. Incentive compatibility of broadcast protocols could manifest in two forms: (1) Dominant Strategy Incentive Compatibility (DSIC) (also called strategy-proofness) and (2) Bayesian incentive compatibility (BIC). A DSIC broadcast protocol is one which makes it a best response for every wireless node to reveal its true type, regardless of what the other nodes reveal. A BIC broadcast protocol is one which makes truth revelation a best response for a node, given that the other nodes are truthful. The DSIC property is stronger and more desirable but more difficult to achieve. On the other hand, the BIC property is much weaker and easier to achieve. In this thesis, we first design a DSIC broadcast protocol for ad hoc networks using the well known VCG (Vickrey-Clarke-Groves) mechanisms and investigate its properties and performance. Next, we design a BIC broadcast protocol, investigate its properties, and compare its performance with that of the DSIC broadcast protocol. Both the protocols developed in this thesis provide an elegant solution to the incentive compatible broadcast problem in ad hoc networks with selfish nodes and help stimulate cooperation among the selfish wireless nodes.

We investigate sequential event detection problems arising in Wireless Sensor Networks (WSNs). A number of battery–powered sensor nodes of the same sensing modality are deployed in a region of interest(ROI). By an event we mean a random time(and, for spatial events, a random location) after which the random process being observed by the sensor field experiences a change in its probability law. The sensors make measurements at periodic time instants, perform some computations, and then communicate the results of their computations to the fusion centre. The decision making algorithm in the fusion centre employs a procedure that makes a decision on whether the event has occurred or not based on the information it has received until the current decision instant. We seek event detection algorithms in various scenarios, that are optimal in the sense that the mean detection delay (delay between the event occurrence time and the alarm time) is minimum under certain detection error constraints. In the first part of the thesis, we study event detection problems in a small extent network where the sensing coverage of any sensor includes the ROI. In particular, we are interested in the following problems: 1) quickest event detection with optimal control of the number of sensors that make observations(while the others sleep),2) quickest event detection on wireless ad hoc networks, and3) optimal transient change detection. In the second part of the thesis, we study the problem of quickest detection and isolation of an event in a large extent sensor network where the sensing coverage of any sensor is only a small portion of the ROI. One of the major applications envisioned for WSNs is detecting any abnormal activity or intrusions in the ROI. An intrusion is typically a rare event, and hence, much of the energy of sensors gets drained away in the pre–intrusion period. Hence, keeping all the sensors in the awake state is wasteful of resources and reduces the lifetime of the WSN. This motivates us to consider the problem of sleep–wake scheduling of sensors along with quickest event detection. We formulate the Bayesian quickest event detection problem with the objective of minimising the expected total cost due to i)the detection delay and ii) the usage of sensors, subject to the constraint that the probability of false alarm is upper bounded by .We obtain optimal event detection procedures, along with optimal closed loop and open loop control for the sleep–wake scheduling of sensors. In the classical change detection problem, at each sampling instant, a batch of samples(where is the number of sensors deployed in the ROI) is generated at the sensors and reaches the fusion centre instantaneously. However, in practice, the communication between the sensors and the fusion centre is facilitated by a wireless ad hoc network based on a random access mechanism such as in IEEE802.11 or IEEE802.15.4. Because of the medium access control(MAC)protocol of the wireless network employed, different samples of the same batch reach the fusion centre after random delays. The problem is to detect the occurrence of an event as early as possible subject to a false alarm constraint. In this more realistic situation, we consider a design in which the fusion centre comprises a sequencer followed by a decision maker. In earlier work from our research group, a Network Oblivious Decision Making (NODM) was considered. In NODM, the decision maker in the fusion centre is presented with complete batches of observations as if the network was not present and makes a decision only at instants at which these batches are presented. In this thesis, we consider the design in which the decision maker makes a decision at all time instants based on the samples of all the complete batches received thus far, and the samples, if any, that it has received from the next (partial) batch. We show that for optimal decision making the network–state is required by the decision maker. Hence, we call this setting Network Aware Decision Making (NADM). Also, we obtain a mean delay optimal NADM procedure, and show that it is a network–state dependent threshold rule on the a posteriori probability of change. In the classical change detection problem, the change is persistent, i.e., after the change–point, the state of nature remains in the in–change state for ever. However, in applications like intrusion detection, the event which causes the change disappears after a finite time, and the system goes to an out–of–change state. The distribution of observations in the out–of–change state is the same as that in the pre–change state. We call this short–lived change a transient change. We are interested in detecting whether a change has occurred, even after the change has disappeared at the time of detection. We model the transient change and formulate the problem of quickest transient change detection under the constraint that the probability of false alarm is bounded by . We also formulate a change detection problem which maximizes the probability of detection (i.e., probability of stopping in the in–change state) subject to the probability of false alarm being bounded by . We obtain optimal detection rules and show that they are threshold d rules on the a posteriori probability of pre–change, where the threshold depends on the a posteriori probabilities of pre–change, in–change, and out–of–change states. Finally, we consider the problem of detecting an event in a large extent WSN, where the event influences the observations of sensors only in the vicinity of where it occurs. Thus, in addition to the problem of event detection, we are faced with the problem of locating the event, also called the isolation problem. Since the distance of the sensor from the event affects the mean signal level that the sensor node senses, we consider a realistic signal propagation model in which the signal strength decays with distance. Thus, the post–change mean of the distribution of observations across sensors is different, and is unknown as the location of the event is unknown, making the problem highly challenging. Also, for a large extent WSN, a distributed solution is desirable. Thus, we are interested in obtaining distributed detection/isolation procedures which are detection delay optimal subject to false alarm and false isolation constraints. For this problem, we propose the following local decision rules, MAX, HALL, and ALL, which are based on the CUSUM statistic, at each of the sensor nodes. We identify corroborating sets of sensor nodes for event location, and propose a global rule for detection/isolation based on the local decisions of sensors in the corroborating sets. Also, we show the minimax detection delay optimality of the procedures HALL and ALL.