The Lao People's Revolutionary Party has ruled Lao PDR as a single-Party State since the revolution of 1975. In the mid-1980s the Party initiated economic reforms to transition from the revolutionary "centrally planned system" into a "market-based economy." The reforms introduced a dilemma of adaptive-perpetuation: in order to perpetuate social practices through which the older generation of Party members produce their political dominance, those laboring for the Party must adapt these social practices to the market-based transformations of the political economy. The Party is increasingly dependent on the labor and consumerism of young people for the adaptive-perpetuation of the Party, its institutions, and its single-Party rule.

Propaganda production is the ideal form of labor in which to examine the dilemma of adaptive-perpetuation in practice. Once entirely State funded, by 2006 the Party's arts and literature magazine had to generate 40% of its income through advertising and sales; propaganda production became dependent upon its marketability to young consumers. With sales slumping and their livelihoods on the line, the magazine's administrators recruited established writers as instructors and formed a training-camp for young aspiring writers, with the hope that the products of youth would prove marketable to their peers. The perpetuation of the magazine unit, as a designated institutional home for their labor, an outlet for their products, and source of their income and social identity was dependent on two generations who simultaneously needed each other, and whose social practices were simultaneously threatened by each other.

My analysis contributes to theoretical understandings of bureaucratic adaptability and social practices which are at the roots of emerging forms of authoritarian rule in contemporary Southeast Asia. On a broader level the work provides theoretical insights into cultural representation, nationalism, artistic production, social incorporation, practices of inculcation, propaganda production, communities of practice, and legitimate peripheral participation.

The increased reliance on the Internet has made information and communication systems more vulnerable to security attacks.

Many recent incidents demonstrate this vulnerability, such as the rapid propagation of sophisticated malwares, the fast growth of botnets, denial-of-service (DoS) attacks against business and government websites, and attacks against the power grid system.

Experts must design and implement security solutions to defend against well organized and very sophisticated adversaries such as malicious insiders, cybercriminals, cyberterrorists, industrial spies, and, in some cases, nation-state intelligence agents.

Instead of designing a defense against a specific attack, Game Theory attempts to design a defense against a sophisticated attacker who plans in anticipation of a complex defense. By including this `second-guessing' element into the design process, Game Theory has the potential of crafting improved security mechanisms. In addition, Game Theory can model issues of trust, incentives, and externalities that arise in security systems.

This thesis illustrates the potential usefulness of Game Theory in security. By modeling the interactions between defenders and attackers as games in three types of common communication scenarios, we predict the adversaries' attacks, determine the set of assets that are most likely to be attacked, and suggest defense strategies for the defenders.

The first example is a communication scenario where some components might be compromised. Specifically, we consider Bob who is receiving information that might be corrupted by an attacker, Trudy. We model the interaction between Trudy and Bob as a zero-sum game where Trudy chooses whether and how to corrupt the data and Bob decides how much he should trust the received information. By analyzing the Nash equilibrium of the game, we have determined when Bob should trust the received information, and how Trudy should corrupt the data. We have also shown how a challenge-response option for Bob can

deter Trudy from corrupting the information.

The second example is a scenario where an intelligent virus is attempting to infect a network protected by an Intrusion Detection System (IDS). The IDS detects intrusions by analyzing the volume of traffic going inside the network. We model the interaction of the intelligent virus and the IDS as a zero-sum game where the IDS chooses the detection threshold, while the virus is trying to

choose its infection rate to maximize its ultimate spreading.

Using a Markov chain model, we compute the Nash equilibria of the game and analyze them. In general, a more aggressive virus is more damaging but is also faster to detect. Hence, in its best attack, the intelligent virus chooses an infection rate that balances between

an aggressive attack that can be easily detected and a slow attack that causes less damage. The best defense strategy against such a sophisticated virus is to quarantine the traffic and analyze it prior to letting it go inside the network (in addition to setting the optimal threshold).

The third example is a blocking security game. For this game, given a finite set of resources S, a defender needs to choose a feasible subset T of S

of resources to perform a mission critical task. The attacker, at the same time, tries to disrupt the task by choosing one resource e of S to attack. Each resource e of S has a cost &mu(e) of attack. The defender loses some value &lambda(T,e) whenever the task is disrupted

(i.e. the attacked resource &me belongs to his subset &T). This loss goes to the attacker. We analyze the game by using the combinatorial tools of blocking pairs of matrices (hence the name blocking security game).

We introduce the notion of critical subset of resources and use this notion to define a vulnerability metric for the task. We find that, in Nash equilibrium, the attacker always targets a critical set of resources and the defender chooses a feasible subset that minimally intersects that critical subset. We illustrate the model with two examples of communication scenarios that consider design of network topology in the presence of a strategic adversary.

The first example studies a scenario where a network manager is choosing a spanning tree of a graph while an attacker is trying to cut the tree by attacking one link of the graph. One of our findings in this scenario is that, the usual edge-connectivity metric

for a graph is not the appropriate vulnerability measure in a network where strategic adversaries are present. The second example deals with a supply-demand network where a network manager is choosing a feasible flow to transport the maximum amount of goods from a set of sources to a set of destinations,

and an attacker is trying to minimize this by attacking an arc of the network. In this case, we find that critical subsets of links are cutsets that maximize the minimum fraction of goods carried per link of the cutset. In most cases, these correspond to minimum cutsets of the graph.

Although computing Nash equilibria of a two-player game is generally complex, we have shown how, for a class of blocking games, one can compute a critical set of resources (hence a Nash equilibrium) in polynomial time.

Full report of a study that focused on the characteristics of CalWORKs participants in San Joaquin County, whether they face significant barriers to employment, and how, if at all, these barriers affect their employment, earnings, and reliance on CalWORKs.

Queueing networks are used to model complicated processing environments such as data centers, call centers, transportation networks, health systems, etc. A queueing network consists of multiple interconnected queues with some routing structure, and a set of servers that have different and possibly overlapping capabilities in processing tasks (jobs) of different queues. One of the most important challenges in designing processing systems is to come up with a low-complexity and efficient scheduling policy.

In this thesis, we consider the problem of robust scheduling for various types of processing networks. We call a policy robust if it does not depend on system parameters such as arrival and service rates. A major challenge in designing efficient scheduling policies for new large-scale processing networks is the lack of reliable estimates of system parameters; thus, designing a robust scheduling policy is of great practical interest. We develop a novel methodology for designing robust scheduling policies for queueing networks. The key idea of our design is to use the queue-length changes information to learn the right allocation of service resources to different tasks by stochastic gradient projection method. Our scheduling policy is oblivious to the knowledge of arrival rates and service rates of tasks in the network. Further, we propose a new fork-join processing network for scheduling jobs that are represented as directed acyclic graphs. We apply our robust scheduling policy to this fork-join network, and prove rate stability of the network under some mild assumptions.

Next, we consider the stability of open multiclass queueing networks under longest-queue (LQ) scheduling. LQ scheduling is of great practical interest since (a) it requires only local decisions per group of queues; (b) the policy is robust to knowledge of arrival rates, service rates and routing probabilities of the network. Throughput-optimality of LQ scheduling policy for open multiclass queueing network is still an open problem. We resolve the open problem for a special case of multiclass queueing networks with two servers that can each process two queues, and show that LQ is indeed throughput-optimal.

Finally, we consider transportation networks that can be well modeled by queueing networks. We abstractly model a network of signalized intersections regulated by fixed-time controls as a deterministic queueing network with periodic arrival and service rates. This system is characterized by a delay-differential equation. We show that there exists a unique periodic trajectory of queue-lengths, and every trajectory or solution of the system converges to this periodic trajectory, independent of the initial conditions.

A policy brief of a study focused on the characteristics of CalWORKs participants in San Joaquin County, whether they face significant barriers to employment, and how, if at all, these barriers affect their employment, earnings, and reliance on CalWORKs.