South American Defense Council: What it Means for Regional Security?

The South American Defense Council (CSD), created in March 2009 as a military coordinating body of the Union of South American Nations (UNASUR) demonstrates a growing trend among Latin American countries to approach matters of regional security independent of the United States. The CSD also indicates a maturation of democratic civil military relations in a region once dominated by authoritarian military regimes. The CSD aims to facilitate the exchange of information about regional defense policies, promote collaboration for disaster relief, and promote civil-military engagement. In less than a year it is hardly a tested entity, but the presence of 12 South American states coming together around security policy marks an important moment in the evolution of civil-military relations in the region. Brazil has taken on an important leadership role in the CSD, acting as a leader in recent regional peacekeeping efforts. As a geopolitical move, Brazil also sees a benefit in promoting good relationships with all countries of South america, given its common border with nine of them. Although the United States is not a member of the CSD, the organization's agenda of infromation exchange of defense policies, military cooperation, and capacity building, including disaster assistance and preparedness provide opportunities for greater collaboration. The CSD is not part of the Inter-American System created after the Second World War. It is unclear how its work will coincide with the OAS Committee on Hemispheric Security or its Secretariat for Multidimensional Security. The U.S. should view the CSD as a mechanism to promote joint initiatives that encourage democratic governance in the region.

Defense Against Node Compromise in Sensor Network Security

Recent advances in electronic and computer technologies lead to wide-spread deployment of wireless sensor networks (WSNs). WSNs have wide range applications, including military sensing and tracking, environment monitoring, smart environments, etc. Many WSNs have mission-critical tasks, such as military applications. Thus, the security issues in WSNs are kept in the foreground among research areas. Compared with other wireless networks, such as ad hoc, and cellular networks, security in WSNs is more complicated due to the constrained capabilities of sensor nodes and the properties of the deployment, such as large scale, hostile environment, etc. Security issues mainly come from attacks. In general, the attacks in WSNs can be classified as external attacks and internal attacks. In an external attack, the attacking node is not an authorized participant of the sensor network. Cryptography and other security methods can prevent some of external attacks. However, node compromise, the major and unique problem that leads to internal attacks, will eliminate all the efforts to prevent attacks. Knowing the probability of node compromise will help systems to detect and defend against it. Although there are some approaches that can be used to detect and defend against node compromise, few of them have the ability to estimate the probability of node compromise. Hence, we develop basic uniform, basic gradient, intelligent uniform and intelligent gradient models for node compromise distribution in order to adapt to different application environments by using probability theory. These models allow systems to estimate the probability of node compromise. Applying these models in system security designs can improve system security and decrease the overheads nearly in every security area. Moreover, based on these models, we design a novel secure routing algorithm to defend against the routing security issue that comes from the nodes that have already been compromised but have not been detected by the node compromise detecting mechanism. The routing paths in our algorithm detour those nodes which have already been detected as compromised nodes or have larger probabilities of being compromised. Simulation results show that our algorithm is effective to protect routing paths from node compromise whether detected or not.

Energy-Efficient Self-Organization of Wireless Acoustic Sensor Networks for Ground Target Tracking

With the developments in computing and communication technologies, wireless sensor networks have become popular in wide range of application areas such as health, military, environment and habitant monitoring. Moreover, wireless acoustic sensor networks have been widely used for target tracking applications due to their passive nature, reliability and low cost. Traditionally, acoustic sensor arrays built in linear, circular or other regular shapes are used for tracking acoustic sources. The maintaining of relative geometry of the acoustic sensors in the array is vital for accurate target tracking, which greatly reduces the flexibility of the sensor network. To overcome this limitation, we propose using only a single acoustic sensor at each sensor node. This design greatly improves the flexibility of the sensor network and makes it possible to deploy the sensor network in remote or hostile regions through air-drop or other stealth approaches. Acoustic arrays are capable of performing the target localization or generating the bearing estimations on their own. However, with only a single acoustic sensor, the sensor nodes will not be able to generate such measurements. Thus, self-organization of sensor nodes into virtual arrays to perform the target localization is essential. We developed an energy-efficient and distributed self-organization algorithm for target tracking using wireless acoustic sensor networks. The major error sources of the localization process were studied, and an energy-aware node selection criterion was developed to minimize the target localization errors. Using this node selection criterion, the self-organization algorithm selects a near-optimal localization sensor group to minimize the target tracking errors. In addition, a message passing protocol was developed to implement the self-organization algorithm in a distributed manner. In order to achieve extended sensor network lifetime, energy conservation was incorporated into the self-organization algorithm by incorporating a sleep-wakeup management mechanism with a novel cross layer adaptive wakeup probability adjustment scheme. The simulation results confirm that the developed self-organization algorithm provides satisfactory target tracking performance. Moreover, the energy saving analysis confirms the effectiveness of the cross layer power management scheme in achieving extended sensor network lifetime without degrading the target tracking performance.

Wireless Sensor Network Deployment

Wireless Sensor Networks (WSNs) are widely used for various civilian and military applications, and thus have attracted significant interest in recent years. This work investigates the important problem of optimal deployment of WSNs in terms of coverage and energy consumption. Five deployment algorithms are developed for maximal sensing range and minimal energy consumption in order to provide optimal sensing coverage and maximum lifetime. Also, all developed algorithms include self-healing capabilities in order to restore the operation of WSNs after a number of nodes have become inoperative. Two centralized optimization algorithms are developed, one based on Genetic Algorithms (GAs) and one based on Particle Swarm Optimization (PSO). Both optimization algorithms use powerful central nodes to calculate and obtain the global optimum outcomes. The GA is used to determine the optimal tradeoff between network coverage and overall distance travelled by fixed range sensors. The PSO algorithm is used to ensure 100% network coverage and minimize the energy consumed by mobile and range-adjustable sensors. Up to 30% - 90% energy savings can be provided in different scenarios by using the developed optimization algorithms thereby extending the lifetime of the sensor by 1.4 to 10 times. Three distributed optimization algorithms are also developed to relocate the sensors and optimize the coverage of networks with more stringent design and cost constraints. Each algorithm is cooperatively executed by all sensors to achieve better coverage. Two of our algorithms use the relative positions between sensors to optimize the coverage and energy savings. They provide 20% to 25% more energy savings than existing solutions. Our third algorithm is developed for networks without self-localization capabilities and supports the optimal deployment of such networks without requiring the use of expensive geolocation hardware or energy consuming localization algorithms. This is important for indoor monitoring applications since current localization algorithms cannot provide good accuracy for sensor relocation algorithms in such indoor environments. Also, no sensor redeployment algorithms, which can operate without self-localization systems, developed before our work.

Post-Revolutionary Post-Modernism: Central American Detective Fiction by the Turn of the 21st Century

Contemporary Central American fiction has become a vital project of revision of the tragic events and the social conditions in the recent history of the countries from which they emerge. The literary projects of Sergio Ramirez (Nicaragua), Dante Liano (Guatemala), Horacio Castellanos Moya (El Salvador), and Ramon Fonseca Mora (Panama), are representative of the latest trends in Central American narrative. These trends conform to a new literary paradigm that consists of an amalgam of styles and discourses, which combine the testimonial, the historical, and the political with the mystery and suspense of noir thrillers. Contemporary Central American noir narrative depicts the persistent war against social injustice, violence, criminal activities, as well as the new technological advances and economic challenges of the post-war neo-liberal order that still prevails throughout the region. Drawing on postmodernism theory proposed by Ihab Hassan, Linda Hutcheon and Brian MacHale, I argued that the new Central American literary paradigm exemplified by Sergio Ramirez’s El cielo llora por mí, Dante Liano’s El hombre de Montserrat, Horacio Castellanos Moya’s El arma en el hombre and La diabla en el espejo, and Ramon Fonseca Mora’s El desenterrador, are highly structured novels that display the characteristic marks of postmodern cultural expression through their ambivalence, which results from the coexistence of multiple styles and conflicting ideologies and narrative trends. The novels analyzed in this dissertation make use of a noir sensitivity in which corruption, decay and disillusionment are at their core to portray the events that shaped the modern history of the countries from which they emerge. The revolutionary armed struggle, the state of terror imposed by military regimes and the fight against drug trafficking and organized crime, are among the major themes of these contemporary works of fiction, which I have categorized as perfect examples of the post-revolutionary post-modernism Central American detective fiction at the turn of the 21st century.