The impacts of trade policy reforms on the Sri Lankan economy

This dissertation presents an analysis of the impacts of trade policy reforms in Sri Lanka. A Computable General Equilibrium (CGE) model is constructed with detailed description of the domestic production structure and foreign trade. The model is then used to investigate the effects of trade policy reforms on resource allocation and welfare.^ Prior to 1977, Sri Lanka maintained stringent control over its imports through rigid quantitative restrictions. A new economic policy reform package was introduced in 1977, and it shifted Sri Lanka's development strategy toward an export oriented policy regime. The shift of policy focus from a restrictive trade regime toward a more open trade regime is expected to have a significant impact on the volume of external trade, domestic production structure, allocation of resources, and social welfare.^ Simulations are carried out to assess the effects of three major policy reforms: (1) a devaluation of the Sri Lanka rupee, (2) a partial or a complete elimination of export duties, and (3) a devaluation-cum-removal of export duties.^ Simulation results indicate that the macroeconomic impact of a devaluation-cum-removal of export duties can be substantial. They also suggest that the resource-pull effects of a devaluation and a devaluation-cum-export duty removal policy are significant. However, the model shows that a devaluation combined with an export duty reduction is likely to be a superior strategy. ^

Interoperable resource brokering with policy-based provisioning and job allocation

The increasing needs for computational power in areas such as weather simulation, genomics or Internet applications have led to sharing of geographically distributed and heterogeneous resources from commercial data centers and scientific institutions. Research in the areas of utility, grid and cloud computing, together with improvements in network and hardware virtualization has resulted in methods to locate and use resources to rapidly provision virtual environments in a flexible manner, while lowering costs for consumers and providers. ^ However, there is still a lack of methodologies to enable efficient and seamless sharing of resources among institutions. In this work, we concentrate in the problem of executing parallel scientific applications across distributed resources belonging to separate organizations. Our approach can be divided in three main points. First, we define and implement an interoperable grid protocol to distribute job workloads among partners with different middleware and execution resources. Second, we research and implement different policies for virtual resource provisioning and job-to-resource allocation, taking advantage of their cooperation to improve execution cost and performance. Third, we explore the consequences of on-demand provisioning and allocation in the problem of site-selection for the execution of parallel workloads, and propose new strategies to reduce job slowdown and overall cost.^

A framework for policy based coordinated adaptation in mobile systems

Adaptation is an important requirement for mobile applications due to the varying levels of resource availability that characterizes mobile environments. However without proper control, multiple applications can each adapt independently in response to a range of different adaptive stimuli, causing conflicts or sub optimal performance. In this thesis we presented a framework, which enables multiple adaptation mechanisms to coexist on one platform. The key component of this framework was the 'Policy Server', which has all the system policies and governs the rules for adaptation. We also simulated our framework and subjected it to various adaptation scenarios to demonstrate the working of the system as a whole. With the help of the simulation it was shown that our framework enables seamless adaptation of multiple applications.

Interoperable Resource Brokering with Policy-based Provisioning and Job Allocation

The increasing needs for computational power in areas such as weather simulation, genomics or Internet applications have led to sharing of geographically distributed and heterogeneous resources from commercial data centers and scientific institutions. Research in the areas of utility, grid and cloud computing, together with improvements in network and hardware virtualization has resulted in methods to locate and use resources to rapidly provision virtual environments in a flexible manner, while lowering costs for consumers and providers. However, there is still a lack of methodologies to enable efficient and seamless sharing of resources among institutions. In this work, we concentrate in the problem of executing parallel scientific applications across distributed resources belonging to separate organizations. Our approach can be divided in three main points. First, we define and implement an interoperable grid protocol to distribute job workloads among partners with different middleware and execution resources. Second, we research and implement different policies for virtual resource provisioning and job-to-resource allocation, taking advantage of their cooperation to improve execution cost and performance. Third, we explore the consequences of on-demand provisioning and allocation in the problem of site-selection for the execution of parallel workloads, and propose new strategies to reduce job slowdown and overall cost.