Network Address Translation (NAT) is a method by which Internet Protocol (IP) addresses are translated from one group to another, in a manner transparent to the end users. It translates the source and destination addresses and ports in the Internet Protocol datagram. There are several benefits for using NAT. NAT can be installed without changes to hosts or routers, it allows reuse of globally routable addresses, it facilitates easy migration or addition of new networks and it provides a method to keep private network addresses hidden from the outside world. NAT, however, is a processor- and memory-intensive activity for any device that implements it. This is because NAT involves reading from and writing to the header and payload information of every IP packet to do the address translation, a performance-intensive activity. It causes an increase in Central Processing Unit (CPU) and memory utilization and may impair throughput and increase the latency experienced by a packet. Thus, understanding the performance impact of NAT on a network device (in particular, a router) becomes an important factor when implementing NAT in any live network. This thesis aims to understand and quantify the impact of Network Address Translation on a network router by doing a series of performance tests after specifying the performance parameters to measure and, then, clearly defining the performance testing methodology that is used to study each of the performance parameters. After a discussion of previous research, the measurement system and subsequent measurement results are described. / Master of Science

This dissertation consists of three essays studying human behavior and contagion phenomenon in networks. The analysis especially focuses on information sharing, trade relationship and pest spread in networks. The first chapter outlines the dissertation by briefly discussing the motivations, methods, and main findings in each of the following chapters. Chapter two examines the information sharing in networks. We develop a heterogenous agents model in which connections between players act as a channel to exchange information. We focus on specialized equilibria, which is based on Nash tatonnement. It is shown that players utilize the signals in the linear form and only specialized equilibria can be stable. We also compare the sequential equilibria and stable equilibria, and it is shown that stable equilibria form a proper subset of the sequential ones, which gives a sharper prediction. The stable equilibria demonstrate star-like graphs, which is similar to the phenomenon "the law of the few" in the literature. Chapter three investigates the trade relationship among players where trade between two players can bring benefits as well as conflict. And if conflict happens, the players coordinate based on received information. We show that the optimal structure of trade networks ranges from complete market to Autarky. Also, we study the optimal timing for trade relationship establishment and the optimal size of organizations when facing scarce members. It is shown that when potential neighbors become more scarce, people care more about the future, or new technology breakthroughs occur more frequently, it is optimal to have more neighbors to back up for the potential technological breakthrough. The last chapter studies the pest spread in the networks. We use a directional and weighted network to study the spread of Tuta absoluta. A robust network-based approach is proposed to model seasonal flow of agricultural produce and examine its role in pest spread. Furthermore, the long-term establishment potential of the pest and its economic impact on the country are assessed. Preliminary analyses indicate that Tuta absoluta will invade most major tomato production regions within a year of introduction and the economic impact of invasion could range from $17-25 million. / Ph. D. / Networks play an important role in the society today, for example, the Internet, Facebook and other social media, cell phones, and communication networks. Networks have undeniable effects on human activity in modern society and this dissertation will focus on three topics: information sharing in networks, trade networks and diffusion in the networks. Information sharing in networks: In the society, individuals have different ability to refine signals, so their strategy about information will be different. In this paper, we assume that there are noisy signals about the true state of the world and individuals have a tradeoff between refining their signals by themselves and connecting to others to receive information. It is shown that players utilize the signals in the linear form and only specialized equilibria can be stable. Furthermore, the stable equilibria demonstrate star-like graphs, which is similar to the phenomenon “the law of the few” in the literature. The structure of trade networks: Trade is ubiquitous in modern society and has undeniable effects on human activity. The trade relationship among players can bring benefits as well as conflict. Facing the advantages and disadvantages of trade, players need to make decisions about who to trade with. We show that the optimal structure of trade networks ranges from complete market to Autarky as economy environment changes. Also, we study the optimal timing for trade relationship establishment and the optimal size of organizations when facing scarce members. It is shown that when potential neighbors become more scarce, people care more about the future, or new technology breakthroughs occur more frequently, it is optimal to have more neighbors to back up for the potential technological breakthrough. Diffusion in networks: Diffusions like information, diseases, rumor are usually through the network in the society. We study the pest spread Nepal in the networks. Based on road networks and trade patterns, we model the flow networks of the pest spread. Based on the flow network, the long-term establishment potential of the pest and its economic impact on the country are assessed. Preliminary analyses indicate that Tuta absoluta will invade most major tomato production regions within a year of introduction and the economic impact of invasion could range from $17-25 million.

The problem of revealing accurate statistics about a population while maintaining privacy of individuals is extensively studied in several related disciplines. Statisticians, information security experts, and computational theory researchers, to name a few, have produced extensive bodies of work regarding privacy preservation. Still the need to improve our ability to control the dissemination of potentially private information is driven home by an incessant rhythm of data breaches, data leaks, and privacy exposure. History has shown that both public and private sector organizations are not immune to loss of control over data due to lax handling, incidental leakage, or adversarial breaches. Prudent organizations should consider the sensitive nature of network security data and network operations performance data recorded as logged events. These logged events often contain data elements that are directly correlated with sensitive information about people and their activities -- often at the same level of detail as sensor data. Privacy preserving data publication has the potential to support reproducibility and exploration of new analytic techniques for network security. Providing sanitized data sets de-couples privacy protection efforts from analytic research. De-coupling privacy protections from analytical capabilities enables specialists to tease out the information and knowledge hidden in high dimensional data, while, at the same time, providing some degree of assurance that people's private information is not exposed unnecessarily. In this research we propose methods that support a risk based approach to privacy preserving data publication for network security data. Our main research objective is the design and implementation of technical methods to support the appropriate release of network security data so it can be utilized to develop new analytic methods in an ethical manner. Our intent is to produce a database which holds network security data representative of a contextualized network and people's interaction with the network mid-points and end-points without the problems of identifiability. / Ph. D. / Network security data is produced when people interact with devices (e.g., computers, printers, mobile telephones) and networks (e.g., a campus wireless network). The network security data can contain identifiers, like user names, that strongly correlate with real world people. In this work we develop methods to protect network security data from privacy-invasive misuse by the ’honest-but-curious’ authorized data users and unauthorized malicious attackers. Our main research objective is the design and implementation of technical methods to support the appropriate release of network security data so it can be utilized to develop new analytic methods in an ethical manner. Our intent is to produce a data set which holds network security data representative of people’s interaction with a contextualized network without the problems of identifiability.

Symptoms associated with Major Depressive Disorder (MDD) have become a source of distress and disability throughout the world, and MDD is among the most common disorders diagnosed annually in the United States. Despite this growing epidemic, scientists and practitioners continue to conceptualize MDD using a common-cause model, which suggests MDD is a result of a latent depression entity that gives rise to symptoms. This is particularly problematic in African American populations where some symptoms associated with depression (i.e., irritability and pain or numbness in the body) are different than those listed in the DSM. The current study examined depressive symptoms in African Americans using network theory, a novel theoretical and analytic approach that conceptualizes psychopathology as an inter-related system rather than one powered by an underlying entity that gives rise to manifest symptoms. Data collected via the Collaborative Psychiatric Epidemiology Surveys (CPES) was used to examine current symptoms (within the past week) of depression via the Center for Epidemiological Studies Depression Scale (CES-D) as well as symptoms within the past month, the latter analysis including otherwise excluded somatic symptoms often reported by African Americans. The goal of this study was to examine how these symptoms relate to each other in the African American population, which has yet to be investigated via network analysis. Results demonstrated that depressive networks of symptoms in African Americans are not as different from typical networks as previously indicated. Rather, psychological symptoms appear to be reported differently and focus on hopelessness and interpersonal relationships rather than sadness. Furthermore, physiological symptoms and those associated with anger did not prove to be more central within these networks.

学位プログラム名: 京都大学大学院思修館 / 京都大学 / 新制・課程博士 / 博士(総合学術) / 甲第25462号 / 総総博第38号 / 新制||総総||6(附属図書館) / 京都大学大学院総合生存学館総合生存学専攻 / (主査)教授 池田 裕一, 准教授 DEROCHEMarc-Henri Jean, 教授 飯吉 透 / 学位規則第4条第1項該当 / Doctor of Philosophy / Kyoto University / DFAM

ABSTRACT Aim of the study: This study aims to contribute to the existing knowledge on similarities and differences of networking styles across Europe and support either network contextualists or universalists with new empirical knowledge. Method used: A multiple case study was used in this paper. Qualitative data was gathered gathering from 10 interviews collected amongst experienced Swedish, Polish and Dutch entrepreneurs. Findings: Empirical findings have revealed significant differences in the networking patterns in the Netherlands, Sweden and Poland. Main networking motivation for Dutch entrepreneurs is seeking new sales opportunities, for Swedish it is the exchange of knowledge and information. All the entrepreneurs admitted that trust is an important component of network relationship. However, in Sweden trust seem to play more significant role. The empirical findings questioned the theory that trust can be easily transferred based on recommendations. No entrepreneur directly suggested that asked about trust acquisition. In Sweden informal networks are strongly preferred, while in the Netherlands formal network are much more popular. In Poland informal networks are also more popular. In the Netherlands, commercial, paid organizations may be extremely popular given the fact that all of the Dutch respondents participate in them, on the other hand in Sweden governmental networking organizations are quite common, in Poland no respondent have mentioned neither of them. Findings indicate that networking is still not as developed in Poland as it is in two other researched countries. Practical Implications: Common networking patterns cannot be expected in different European countries and background studies should be conducted before entering foreign market. There is still market growth opportunity for commercial networking organizations in Poland. Polish government should engage in more effective promotion of networking amongst entrepreneurs. Contribution: Empirical data confirm the contextualists approach that emphasizes the importance of national differences on networking and warns managers that resemblance of certain patterns cannot be assumed for different countries. This approach was confirmed since the findings exposed significant differences in several areas of networking. Keywords: Business networking, internationalization of business network, networking motivations, trust building, network type preferences, network contextualism and universalism.

ITC/USA 2011 Conference Proceedings / The Forty-Seventh Annual International Telemetering Conference and Technical Exhibition / October 24-27, 2011 / Bally's Las Vegas, Las Vegas, Nevada / This paper presents a method for the optimization of mixed networks that incorporates a mixed layer optimization of performance features. The expanded integrated Network Enhanced Telemetry (iNET) system envisioned telemetering for large and complex networks which will require core telemetry networks with ad hoc extensions for coverage. Organizing such a network has been successfully accomplished in simulations using a K-mean clustering algorithm. This paper shows how the features of these network elements will be captured and disseminated in a real system. This management of network elements across multiple layers is characterized as cross-layer optimization. This paper will also show how such cross layer features can be combined for a globally optimum solution. It shows by example how the iNET system comprising multiple ground stations, gateways, frequency, nodes, and three performance measures can be optimized to achieve overall optimal system performance.

Today, the radio spectrum is rarely fully utilized. This problem is valid in more domains, e.g., time, frequency and geographical location. To provide an efficient utilization of the radio spectrum, the Cognitive Radio Networks (CRNs) have been advanced. The key idea is to open up the licensed spectrum to unlicensed users, thus allowing them to use the so-called spectrum opportunities as long as they do not harmfully interfere with licensed users. An important focus is laid on the limitation of previously reported research efforts, which is due to the limited consideration of the problem of competition among unlicensed users for spectrum access in heterogeneous CRNs. A software framework is introduced, which is called PRioritized Opportunistic spectrum Access System (PROAS). In PROAS, the heterogeneity aspects of CRNs are specifically expressed in terms of cross-layer design and various wireless technologies. By considering factors like ease of implementation and efficiency of control, PROAS provides priority scheduling based solutions to alleviate the competition problem of unlicensed users in heterogenous CRNs. The advanced solutions include theoretical models, numerical analysis and experimental simulations for performance evaluation. By using PROAS, three particular CRN models are studied, which are based on ad-hoc, mesh-network and cellular-network technologies. The reported results show that PROAS has the ability to bridge the gap between research results and the practical implementation of CRNs.

The aim of this thesis is to conduct performance investigation of a combined system of Network Coding (NC) technique with Ant-Colony (ACO) routing protocol. This research analyses the impact of several workload characteristics, on system performance. Network coding is a significant key development of information transmission and processing. Network coding enhances the performance of multicast by employing encoding operations at intermediate nodes. Two steps should realize while using network coding in multicast communication: determining appropriate transmission paths from source to multi-receivers and using the suitable coding scheme. Intermediate nodes would combine several packets and relay them as a single packet. Although network coding can make a network achieve the maximum multicast rate, it always brings additional overheads. It is necessary to minimize unneeded overhead by using an optimization technique. On other hand, Ant Colony Optimization can be transformed into useful technique that seeks imitate the ant’s behaviour in finding the shortest path to its destination using quantities of pheromone that is left by former ants as guidance, so by using the same concept of the communication network environment, shorter paths can be formulated. The simulation results show that the resultant system considerably improves the performance of the network, by combining Ant Colony Optimization with network coding. 25% improvement in the bandwidth consumption can be achieved in comparison with conventional routing protocols. Additionally simulation results indicate that the proposed algorithm can decrease the computation time of system by a factor of 20%.

<div> <div> <div> <p>With the prevalence of web and cloud-based services, there is an ever growing requirement on the underlying network infrastructure to ensure that business critical traffic is continually serviced with acceptable performance. Networks must meet their performance requirements under failures. The global scale of cloud provider networks and the rapid evolution of these networks imply that failures are the norm in production networks today. Unplanned downtime can cost billions of dollars, and cause catastrophic consequences. The thesis is motivated by these challenges and aims to provide a principled solution to certifying network performance under failures. Network performance certification is complicated, due to both the variety of ways a network can fail, and the rich ways a network can respond to failures. The key contributions of this thesis are: (i) a general framework for robustly certifying the worst-case performance of a network across a given set of uncertain scenarios. A key novelty is that the framework models flexible network response enabled by recent emerging trends such as Software-Defined Networking; (ii) a toolkit which automates the key steps needed in robust certification making it suitable for use by a network architect, and which enables experimentation on a wide range of robust certification of practical interest; (iii) Slice, a general framework which efficiently classifies failure scenarios based on whether network performance is acceptable for those scenarios, and which allows reasoning about performance requirements that must be met over a given percentage of scenarios. We also show applications of our frameworks in synthesizing designs that are guaranteed to meet a performance goal over all or a desired percentage of a given set of scenarios. The thesis focuses on wide-area networks, but the approaches apply to data-center networks as well.</p></div></div></div>