Protocol designs targeted at a specific network scenario or performance metric appear promising on paper, but the complexity and cost of implementing and tuning a routing protocol from scratch presents a major bottleneck in the protocol design process. A unique framework called 'Orchestra` is proposed in the literature to support the testing and development of novel routing designs. The idea of the Orchestra framework is to create generic and reusable routing functional components which can be combined to create unique protocol designs customized for a specific performance metric or network setting. The first contribution of this thesis is the development of a generic, modular, scalable and extensible architecture of the Orchestra framework. Once the architecture and implementation of the framework is completed, the second contribution of this thesis is the development of functional components and strategies to design and implement routing protocols for delay tolerant networks (DTNs). DTNs are a special type of ad hoc network characterized by intermittent connectivity, long propagation delays and high loss rate. Thus, traditional ad hoc routing approaches cannot be used in DTNs, and special features must be developed for the Orchestra framework to support the design of DTN routing protocols. The component-based architecture of Orchestra can capture a variety of modules that can be used to assemble a routing protocol. However, manually assembling these components may result in suboptimal designs, because it is difficult to determine what the best combination is for a particular set of performance objectives and network characteristics. The third contribution of the thesis addresses this problem. A genetic algorithm based approach to automate the process of routing protocol design is developed and its performance is evaluated in the context of the Orchestra framework. / Master of Science

Les réseaux tolérants aux retards (DTN) ont été conçus pour fournir un moyen de communication durable entre terminaux mobiles dans les régions dépourvues d’infrastructure cellulaire. Dans de tels réseaux, l’ensemble des voisins de chaque nœud change au fil du temps en raison de la mobilité des nœuds, ce qui entraîne une connectivité intermittente et des routes instables dans le réseau. Nous analysons la performance d’un système d’incitation pour les DTN à deux sauts dans lequel une source en arriéré offre une récompense fixe aux relais pour délivrer un message. Un seul message à la fois est proposé par la source. Pour un message donné, seul le premier relais à le délivrer reçoit la récompense correspondant à ce message, induisant ainsi une compétition entre les relais. Les relais cherchent à maximiser la récompense attendue pour chaque message alors que l’objectif de la source est de satisfaire une contrainte donnée sur la probabilité de livraison du message. Nous considérons deux réglages différents : l’un dans lequel la source indique aux relais pendant combien de temps un message est en circulation, et l’autre dans lequel la source ne donne pas cette information. Dans le premier paramètre, nous montrons que la politique optimale d’un relais est de type seuil : il accepte un message jusqu’à un premier seuil et le conserve jusqu’à ce qu’il atteigne la destination ou le deuxième seuil. Les formules de calcul des seuils ainsi que de la probabilité de livraison des messages sont dérivées pour une source d’arriérés. Nous étudions ensuite la performance asymptotique de ce réglage dans la limite moyenne du champ. Lorsque le deuxième seuil est infini, nous donnons l’ODE du champ moyen et montrons que tous les messages ont la même probabilité de réussite. Lorsque le deuxième seuil est fini, nous ne donnons qu’une approximation ODE car dans ce cas, la dynamique n’est pas markovienne. Pour le second réglage, nous supposons que la source propose chaque message pour une période de temps fixe et qu’un relais décide d’accepter un message selon une politique randomisée lors d’une rencontre avec la source. S’il accepte le message, un relais le garde jusqu’à ce qu’il atteigne la destina- tion. Nous établissons dans quelle condition la probabilité d’acceptation des relais est strictement positive et montrons que, dans cette condition, il existe un équilibre de Nash symétrique unique, dans lequel aucun relais n’a quelque chose à gagner en changeant unilatéralement sa probabilité d’acceptation. Des expressions explicites pour la probabilité de livraison du message et le temps moyen de livraison d’un message à l’équilibre symétrique de Nash sont dérivées, ainsi qu’une expression de la valeur asymptotique de la livraison du message. Enfin, nous présentons de nombreux résultats de simulations pour com- parer les performances de la stratégie de type seuil et de la stratégie ran- domisée, afin de déterminer dans quelle condition il est rentable pour la source de donner l’information sur l’âge d’un message aux relais. / Delay-Tolerant Networks (DTNs) were designed to provide a sustainable means of communication between mobile terminals in regions without cellular infrastructure. In such networks, the set of neighbors of every node changes over time due to the mobility of nodes, resulting in intermittent connectivity and unstable routes in the network. We analyze the performance of an incentive scheme for two-hop DTNs in which a backlogged source pro- poses a fixed reward to the relays to deliver a message. Only one message at a time is proposed by the source. For a given message, only the first relay to deliver it gets the reward corresponding to this message thereby inducing a competition between the relays. The relays seek to maximize the expected reward for each message whereas the objective of the source is to satisfy a given constraint on the probability of message delivery. We consider two different settings: one in which the source tells the relays for how long a message is in circulation, and one in which the source does not give this information. In the first setting, we show that the optimal policy of a relay is of thresh- old type: it accepts a message until a first threshold and then keeps the message until it either meets the destination or reaches the second threshold. Formulas for computing the thresholds as well as probability of message delivery are derived for a backlogged source. We then investigate the asymptotic performance of this setting in the mean field limit. When the second thresh- old in infinite, we give the mean-field ODE and show that all the messages have the same probability of successful delivery. When the second threshold is finite we only give an ODE approximation since in this case the dynamics are not Markovian. For the second setting, we assume that the source proposes each message for a fixed period of time and that a relay decides to accept a message accord- ing to a randomized policy upon encounter with the source. If it accepts the message, a relay keeps it until it reaches the destination. We establish under which condition the acceptance probability of the relays is strictly positive and show that, under this condition, there exists a unique symmetric Nash equilibrium, in which no relay has anything to gain by unilaterally changing its acceptance probability. Explicit expressions for the probability of message delivery and the mean time to deliver a message at the symmetric Nash equilibrium are derived, as well as an expression of the asymptotic value of message delivery. Finally, we present numerous simulations results to compare performances of the threshold-type strategy and the randomized strategy, in order to determine under which condition it is profitable for the source to give the information on the age of a message to the relays

Delay-tolerant networks (DTNs) have the potential to connect devices and areas of the world that are under-served by traditional networks. The idea is that an end-to-end connection may never be present. To make communication possible, intermediate nodes take custody of the data being transferred and forward it as the opportunity arises. Both links and nodes may be inherently unreliable and disconnections may be long-lived. A critical challenge for DTNs is determining routes through the network without ever having an end-to-end connection. <br /><br /> This thesis presents a practical routing protocol that uses only observed information about the network. Previous approaches either require complete future knowledge about the connection schedules, or use many copies of each message. Instead, our protocol uses a metric that estimates the average waiting time for each potential next hop. This learned topology information is distributed using a link-state routing protocol, where the link-state packets are flooded using epidemic routing. The routing is recomputed each time connections are established, allowing messages to take advantage of unpredictable contacts. Messages are exchanged if the topology suggests that a connected node is "closer" than the current node. <br /><br /> Simulation results are presented, showing that the protocol provides performance similar to that of schemes that have global knowledge of the network topology, yet without requiring that knowledge. Further, it requires a significantly less resources than the epidemic alternative, suggesting that this approach scales better with the number of messages in the network.

Delay-tolerant networks (DTNs) have the potential to connect devices and areas of the world that are under-served by traditional networks. The idea is that an end-to-end connection may never be present. To make communication possible, intermediate nodes take custody of the data being transferred and forward it as the opportunity arises. Both links and nodes may be inherently unreliable and disconnections may be long-lived. A critical challenge for DTNs is determining routes through the network without ever having an end-to-end connection. <br /><br /> This thesis presents a practical routing protocol that uses only observed information about the network. Previous approaches either require complete future knowledge about the connection schedules, or use many copies of each message. Instead, our protocol uses a metric that estimates the average waiting time for each potential next hop. This learned topology information is distributed using a link-state routing protocol, where the link-state packets are flooded using epidemic routing. The routing is recomputed each time connections are established, allowing messages to take advantage of unpredictable contacts. Messages are exchanged if the topology suggests that a connected node is "closer" than the current node. <br /><br /> Simulation results are presented, showing that the protocol provides performance similar to that of schemes that have global knowledge of the network topology, yet without requiring that knowledge. Further, it requires a significantly less resources than the epidemic alternative, suggesting that this approach scales better with the number of messages in the network.

Mobile Ad hoc NETworks (MANETs) aim at making communication between mobile nodes feasible without any infrastructure support. Sparse MANETs fall into the class of Delay Tolerant Networks which are intermittently connected networks and where there is no contemporaneous end-to-end path at any given time. We first, propose a new reliable transport scheme for DTNs based on the use of ACKnowledgments and random linear coding. We model the evolution of the network under our scheme using a fluid-limit approach. We optimize our scheme to obtain mean file transfer times on certain optimal parameters obtained through differential evolution approach. Secondly, we propose and study a novel and enhanced ACK to improve reliable transport for DTNs covering both unicast and multicast flows. We make use of random linear coding at relays so that packets can reach the destination faster. We obtain reliability based on the use of so-called Global Selective ACKnowledgment. We obtain significant improvement through G-SACKs and coding at relays. Finally, we tackle the problem of estimating file-spread in DTNs with direct delivery and epidemic routing. We estimate and track the degree of spread of a message in the network. We provide analytical basis to our estimation framework alongwith insights validated with simulations. We observe that the deterministic fluid model can indeed be a good predictor with a large of nodes. Moreover, we use Kalman filter and Minimum- Mean-Squared-Error (MMSE) to track the spreading process and find that Kalman filter provides more accurate results as compared to MMSE

Sensor devices and the emergent networks that they enable are capable of transmitting information between data sources and a permanent data sink. Since these devices have low-power and intermittent connectivity, latency of the data may be tolerated in an effort to save energy for certain classes of data. The BUBBLE routing algorithm developed by Hui et al. in 2008 provides consistent routing by employing a model which computes individual nodes popularity from sets of nodes and then uses these popularity values for forwarding decisions. This thesis considers enhancements to BUBBLE based on the hypothesis that nodes do form groups and certain centrality values of nodes within these groups can be used to improve routing decisions further. Built on this insight, there are two algorithms proposed in this thesis. First is the Community-Based- Forwarding (CBF), which uses pairwise group interactions and pairwise node-to-group interactions as a measure of popularity for routing messages. By having a different measure of popularity than BUBBLE, as an additional factor in determining message forwarding, CBF is a more conservative routing scheme than BUBBLE. Thus, it provides consistently superior message transmission and delivery performance at an acceptable delay cost in resource constrained environments. To overcome this drawback, the concept of unique interaction pattern within groups of nodes is introduced in CBF and it is further renewed into an enhanced algorithm known as Hybrid-Community-Based- Forwarding (HCBF). Utilizing this factor will channel messages along the entire path with consideration for higher probability of contact with the destination group and the destination node. Overall, the major contribution of this thesis is to design and evaluate an enhanced social based routing algorithm for resource-constrained Pocket Switched Networks (PSNs), which will optimize energy consumption related to data transfer. It will do so by explicitly considering features of communities in order to reduce packet loss while maintaining high delivery ratio and reduced delay.

Network infrastructures often need to stage content so that it is accessible to consumers. The standard solution, deploying the content on a centralised server, can be inadequate in several situations. Our thesis is that information encoded in social networks can be used to tailor content staging decisions to the user base and thereby build better data delivery infrastructures. This claim is supported by two case studies, which apply social information in challenging situations where traditional content staging is infeasible. Our approach works by examining empirical traces to identify relevant social properties, and then exploits them. The first study looks at cost-effectively serving the ``Long Tail'' of rich-media user-generated content, which need to be staged close to viewers to control latency and jitter. Our traces show that a preference for the unpopular tail items often spreads virally and is localised to some part of the social network. Exploiting this, we propose Buzztraq, which decreases replication costs by selectively copying items to locations favoured by viral spread. We also design SpinThrift, which separates popular and unpopular content based on the relative proportion of viral accesses, and opportunistically spins down disks containing unpopular content, thereby saving energy. The second study examines whether human face-to-face contacts can efficiently create paths over time between arbitrary users. Here, content is staged by spreading it through intermediate users until the destination is reached. Flooding every node minimises delivery times but is not scalable. We show that the human contact network is resilient to individual path failures, and for unicast paths, can efficiently approximate flooding in delivery time distribution simply by randomly sampling a handful of paths found by it. Multicast by contained flooding within a community is also efficient. However, connectivity relies on rare contacts and frequent contacts are often not useful for data delivery. Also, periods of similar duration could achieve different levels of connectivity; we devise a test to identify good periods. We finish by discussing how these properties influence routing algorithms.

<p>Wireless mesh networks are widely used for various communication purposes and are often deployed in a broad range of outdoor applications. In cases where the deployment area is outside the reach of fixed infrastructure, energy efficient operation of the mesh nodes is very important. Many approaches have been explored to find energy efficient network solutions for these types of scenarios. This thesisproposes power saving mechanisms where the mesh network nodes opportunistically access coexistent vehicular networks. This is referred to as Opportunistic Vehicle Assisted Ferrying (OVAF). The history of using moving particles for message carrying can be found in research on intermittently connected networks. However, this approachhas never been considered with fully connected networks. Two different models are presented to model the OVAFmechanism: \textbf{a}. \emph{A flow based model}, and \textbf{b}. \emph{Apacket based model}. For each model an analytic lower bound isobtained by formulating a linear integer optimization with differentcost functions. Heuristics, which simplify the complexity of theproblem, are then developed for eachmodel. Arriving vehicles and generated packets are also modeled asrandom processes under various scenarios using different parameters.Results are presented which demonstrate the superiority of the OVAFrouting method compared to conventional multihop forwarding (Up to $60\%$increase in energy saving).</p> / Master of Applied Science (MASc)

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.

在耐延遲網路環境下節點的相遇情況不是很頻繁，這可能導致節點間的連線斷斷續續，使得有效地將訊息傳遞成為一件困難的事情。藉由社群感知轉送機制的中間度指標特性，可以來提升傳送成功率。雖然大多數研究幾乎都是將訊息轉送到單一目的地或是多個且已知的目的地。然而，一些應用像是廣告的散佈，要將訊息送給對訊息有興趣的人，但卻不知道是誰。因此，關鍵的問題為如何建立社群網路關係的親密度機制，來選擇作為轉送訊息的節點，並利用群體廣播的方式盡可能有效地傳播至最多可能目標目的地，進而提升效能。 本論文以群播機制和社群感知當作基礎概念，來設計新的轉送訊息的方法和公式化選擇中繼節點的機制。最後，我們使用政治大學實際軌跡來模擬，將模擬結果與其它路由演算法比較，其結果證明我們所提出的方法能提高訊息傳送成功率和正確率，降低傳送延遲時間和傳送訊息的成本。 / In delay tolerant networks (DTNs), nodes infrequently encounter with each others. This results in intermittent connectivity of the nodes, and makes it difficult to deliver the message effectively. A social-aware forwarding scheme can help for successful delivery ratio by utilizing the characteristic of their centrality metric. Most of the previous studies focus on message delivery to single destination or some priori known destinations. However, some applications like advertisement dissemination may not know who will be the interested persons to be delivered. Therefore, the key challenge is how to establish the social relationship strategy to select appropriate nodes as relays, and furthermore to use multicasting to disseminate effectively as many “target” destinations as possible to improve the performance. This thesis developed a new strategy which has a new forwarding message scheme and formulates the selection of the relay nodes based on the concept of the multicasting and the social network. Finally, we used the reality trace data of National Chengchi University to simulate. The simulation results are compared to others DTNs routing protocols as well as other social-aware forwarding schemes. The results showed that our proposed approach can enhance the successful delivery ratio and delivery accuracy, decrease the delivery delay and reduce the delivery overhead.