This thesis examines the need for a multilateral regime for the regulation of foreign direct investment. The absence of such a regime has slowed the growth of foreign direct investment, as investment decisions are difficult to make because of the uncertainty of investment rules. Attempts to establish a multilateral framework for investment have failed due to disagreement between developed and developing countries on its scope. The major source of controversy has been the inclusion of the national treatment standard in the prospective agreement. This thesis analyses the position of both sides, and attempts to find a balance between the positive and negative effects of the multilateral framework for regulating foreign direct investment. It argues that an investment regime modelled after the General Agreement on Trade in Services could be beneficial, as it would provide security for investment, and flexibility for host countries to control the inflow of foreign investment.

This thesis is concerned with the usability of Raspberry Pi as the access point in the mobilebroadband network environment. The first part of the thesis is dedicated to Raspberry Pi itself;hardware required to set up WLAN and WAN; and to the analysis of suitable solutions forbandwidth aggregation, particularly the load balancing of mobile broadband connections andtheir aggregation into one logical link. The second part deals with the implementation of thesesolutions and subsequently with their testing and verification. The evaluation of results gives aninteresting outcome. Load balancing has proven to be resilient and feasible solution forbandwidth aggregation in the mobile broadband network environment where the speed, packetloss and jitter are of main concern. The second scenario, where the connections are bundled intoone logical link, has turned out to give variable results. Its performance is susceptible to thechanges in the mobile broadband network as the packets across the links in the bundle alternatein the round-robin fashion.

Šis robotas buvo kuriamas ne su tikslu sukurti ar išrasti kažką nauja, bet pritaikyti kuo daugiau sugebėjimų ir žinių. Pagrindiniai šio darbo tikslai: • Atlikti panašių įrenginių ir technologijų analizę. • Suprojektuoti ir pagaminti balansuojantį robotą su lokalaus pozicionavimo sistema • Parašyti programinę įrangą • Pagaminti prototipą • Atlikti prototipo bandymus. Šis rašo darbas susidaro iš panašių įrenginių ir panaudotų technologijų analizės, roboto struktūros aprašymo, spausdinto montažo plokščių projektavimo ir gamybos ypatumų, programos algoritmo, įvairių bandymų ir rezultatų. / This robot was built with intentions to create or develop something new, but to apply as much skill and knowledge. The main goals of this paper ware: • Make an analysis of similar equipment and used technologies. • Design and make a balancing robot with local positioning system • Write a program for the robot • Create a prototype • Carry out test of the robot performance. This paper consists of analysis of similar equipment and used technologies, robot structure description, printed circuit board design and making, program algoritms, various tests and test results.

In this thesis we propose a cloud Input Shaper and Dynamic Resource Controller to provide application-level quality of service guarantees in cloud computing environments. The Input Shaper splits the cloud into two areas: one for shaped traffic that achieves quality of service targets, and one for overflow traffic that may not achieve the targets. The Dynamic Resource Controller profiles customers’ applications, then calculates and allocates the resources required by the applications to achieve given quality of service targets. The Input Shaper then shapes the rate of incoming requests to ensure that the applications achieve their quality of service targets based on the amount of allocated resources. To evaluate our system we create a new benchmark application that is suitable for use in cloud computing environments. It is designed to reflect the current design of cloud based applications and can dynamically scale each application tier to handle large and varying workload levels. In addition, the client emulator that drives the benchmark also mimics realistic user behaviors such as browsing from multiple tabs, using JavaScript, and has variable thinking and typing speeds. We show that a cloud management system evaluated using previous benchmarks could violate its estimated quality of service achievement rate by over 20%. The Input Shaper and Dynamic Resource Controller system consist of an application performance modeler, a resource allocator, decision engine, and an Apache HTTP server module to reshape the rate of incoming web requests. By dynamically allocating resources to applications, we show that their response times can be improved by as much as 30%. Also, the amount of resources required to host applications can be decreased by 20% while achieving quality of service objectives. The Input Shaper can reduce VMs’ resource utilization variances by 88%, and reduce the number of servers by 45%.

Distributed key-value systems have been widely used as elemental components of many Internet-scale services at sites such as Amazon, Facebook and Twitter. This thesis examines a system design approach to scale existing key-value systems, both horizontally and vertically, by carefully engineering and integrating techniques that are grounded in recent theory but also informed by underlying architectures and expected workloads in practice. As a case study, we re-design FAWN-KV—a distributed key-value cluster consisting of “wimpy” key-value nodes—to use less memory but achieve higher throughput even in the worst case. First, to improve the worst-case throughput of a FAWN-KV system, we propose a randomized load balancing scheme that can fully utilize all the nodes regardless of their query distribution. We analytically prove and empirically demonstrate that deploying a very small but extremely fast load balancer at FAWN-KV can effectively prevent uneven or dynamic workloads creating hotspots on individual nodes. Moreover, our analysis provides service designers a mathematically tractable approach to estimate the worst-case throughput and also avoid drastic overprovisioning in similar distributed key-value systems. Second, to implement the high-speed load balancer and also to improve the space efficiency of individual key-value nodes, we propose novel data structures and algorithms, including the cuckoo filter, a Bloom filter replacement that is high-speed, highly compact and delete-supporting, and optimistic cuckoo hashing, a fast and space-efficient hashing scheme that scales on multiple CPUs. Both algorithms are built upon conventional cuckoo hashing but are optimized for our target architectures and workloads. Using them as building blocks, we design and implement MemC3 to serve transient data from DRAM with high throughput and low-latency retrievals, and SILT to provide cost-effective access to persistent data on flash storage with extremely small memory footprint (e.g., 0.7 bytes per entry)

We present an algorithm for imputation of incomplete datasets based on Bayesian exchangeability through Pólya sampling. Each (donee) unit with a missing value is imputed multiple times by observed (real) values on units from a donor pool. The donor pools are constructed using auxiliary variables. Several features from kernel estimation are used to counteract unbalances that are due to sparse and bounded data. Three balancing features can be used with only one single continuous auxiliary variable, but an additional fourth feature need, multiple continuous auxiliary variables. They mainly contribute by reducing nonresponse bias. We examine how the donor pool size should be determined, that is the number of potential donors within the pool. External information is shown to be easily incorporated in the imputation algorithm. Our simulation studies show that with a study variable which can be seen as a function of one or two continuous auxiliaries plus residual noise, the method performs as well or almost as well as competing methods when the function is linear, but usually much better when the function is nonlinear. / <p>At the time of the doctoral defense, the following papers were unpublished and had a status as follows: Paper 1: In press. Paper 3: Submitted. Paper 4: Submitted.</p>

As the further development of single-core architectures faces seemingly insurmountable physical and technological limitations, computer designers have turned their attention to alternative approaches. One such promising alternative is the use of several smaller cores working in unison as a programmable hardware accelerator. It is clear that the vast – and, as yet, largely untapped – potential of hardware accelerators is coming to the forefront of computer architecture. There are many challenges that must be addressed for the programmable hardware accelerator to be realized in practice. In this thesis, load-balancing, on-chip communication, and an execution model are studied. Imbalanced distribution of workloads across the processing elements constitutes wasteful use of resources, which results in degrading the performance of the system. In this thesis, a hardware-based load-balancing technique is proposed, which is demonstrated to be more scalable than state-of-the-art loadbalancing techniques. To facilitate efficient communication among ever increasing number of cores, a scalable communication network is imperative. Packet switching networks-on-chip (NoC) is considered as a viable candidate for scalable communication fabric. The size of flit, which is a unit of flow control in NoC, is one of important design parameters that determine latency, throughput and cost of NoC routers. How to determine an optimal flit size is studied in this thesis and a novel router architecture is proposed, which overcomes a problem related with the flit size. This thesis also includes a new execution model and its supporting architecture. An event-driven model that is an extension of hardware description language is employed as an execution model. The dynamic scheduling and module-level prefetching for supporting the event-driven execution model are evaluated.

The past decade has witnessed the fast development of peer-assisted video ondemand (PA-VoD) systems, which have attracted millions of online users. The efforts on improving the quality of video programs have never ceased since the beginning, and nowadays offering high-definition (HD) channels has become a common practice. However, compared with standard-definition (SD) channels, HD channels have to sustain a higher streaming rate to peers, which is a challenging task. In real systems, HD channels often suffer from poor streaming quality, or impose a heavy burden on the servers. This thesis conducts an in-depth study on peer cache and upload bandwidth management at the same time for multi-channel PA-VoD systems, where HD and SD channels coexist with different bandwidth and cache requirements. The objective is to minimize the server bandwidth consumption, and thus the maintenance cost of VoD service providers. The solution is cross-channel allocation (or view-upload decoupling), i.e., making SD channels help HD viewers with the surplus peer-contributed resources. The management of these resources includes bandwidth allocation and caching strategies. We first propose a generic modeling framework to capture the essential characteristics of PA-VoD systems: the demand and supply of bandwidth from peers. Our modeling framework can be customized or extended to model a variety of caching strategies, including FIFO, passive caching, and active caching with different user behaviors. We then apply the modeling framework to two representative scenarios: stationary scenarios, where the channels have fixed popularity; and non-stationary scenarios, in which a new movie is released, and peers enter the channel in a flash-crowd manner. We prove using our models that passive caching is efficient for stationary user behaviors, and derive the optimal caching solutions when the channels in the system demonstrate different popularity evolutions, i.e., with non-stationary behaviors. With the insights gained from our modeling work, we design effective centralized heuristic algorithms and practical distributed strategies for peer cache replacement and upload bandwidth allocation, with a near-optimal utilization of these resources. We propose centralized and distributed cross-channel allocation, and also extend the substreaming technique from live streaming to VoD systems, where it demonstrates its extreme feasibility. Our extensive simulation results verify the efficacy of these heuristic and practical strategies. / Graduate / 0984 / changlecsu@gmail.com

In this thesis, we develop an exact algorithm for an assembly line balancing problem with equipment selection decisions. Two objectives are considered: minimizing the total equipment costs and the number of workstations. Our aim is to choose the type of the equipment(s) in every workstation and determine the assignment of the tasks to each workstation and equipment type. We aim to propose a set of efficient solutions for each problem and leave the choice of the best solution to the decision maker&rsquo / s preferences. A branch and bound algorithm is developed whose efficiency is increased with some dominance rules and powerful lower bounds. Moreover, modified ranked positional weight heuristic method is used as initial upper bound. The effectiveness of the proposed procedure is demonstrated by computational analysis in which the effects of changing certain parameter values are investigated. We find that our algorithm is capable of solving the problem instances with up to 25 tasks and 5 equipments.

Mit dem Spitzentechnologiecluster „Energieeffiziente Produkt- und Prozessinnovationen in der Produktionstechnik“ (eniPROD®) werden die am Wissenschaftsstandort Chemnitz vorhandenen exzellenten Forschungsbereiche gebündelt, um einen national und international sichtbaren Beitrag zur Umsetzung der Vision einer nahezu emissionsfreien Produktion bei gleichzeitiger Erhöhung der Ressourceneffizienz zu leisten. Um dieses Ziel erreichen zu können, sind Methoden erforderlich, mit denen Energieverbräuche unter Einbeziehung technischer, ökonomischer und ökologischer Kriterien erfasst und bewertet werden können. Die im Rahmen von eniPROD® gebildete Querschnittsarbeitsgruppe 1 „Energetisch-wirtschaftliche Bilanzierung“ setzt sich intensiv mit solchen Bilanzierungs- und Bewertungsmethoden auseinander. Der vorliegende Band enthält die Beiträge eines von der Querschnittsarbeitsgruppe initiierten Workshops, in dem verschiedene Facetten des Themenkomplexes der energetisch-wirtschaftlichen Bilanzierung und Bewertung von Wissenschaftlern verschiedener Disziplinen aufgegriffen und diskutiert wurden.