Contributions to Service Level Agreement (SLA), Negotiation and Monitoring in Cloud Computing

Cloud computing is a dynamic field of research, as the latest advances in the cloud computing applications have led to development of a plethora of cloud services in the areas of software, hardware, storage, internet of things connected to the cloud, and 5G supported by the cloud networks. Due to ever increasing developments and the subsequent emergence of a wide range of cloud services, a cloud market was created with cloud providers and customers seeking to buy the cloud services. With the expansion of the cloud market and the presence of a virtual environment in which cloud services are provided and managed, the face to-face meetings between customers and cloud providers is almost impossible, and the negotiation over the cloud services using the state-of-the-art autonomous negotiation agents has been theorized and researched by several researchers in the field of cloud computing, however, the solutions offered by literature are less applicable in the real-time cloud market with the evolving nature of services and customers’ requirements. Therefore, this study aimed to develop the solutions addressing issues in relation to negotiation of cloud services leading to the development of a service-level agreement (SLA), and monitoring of the terms and conditions specified in the SLA. We proposed the autonomous service-level framework supported by the autonomous agents for negotiating over the cloud services on behalf of the cloud providers and customers. The proposed framework contained gathering, filtering, negotiation and SLA monitoring functions, which enhanced its applicability in the real-time cloud market environment. Gathering and filtering stages facilitated the effectiveness of the negotiation phase based on the requirements of customers and cloud services available in the cloud market. The negotiation phase was executed by the selection of autonomous agents, leading to the creation of an SLA with metrics agreed upon between the cloud provider and the customer. Autonomous agents improved the efficiency of negotiation over multiple issues by creating the SLA within a short time and benefiting both parties involved in the negation phase. Rubinstein’s Alternating Offers Protocol was found to be effective in drafting the automated SLA solutions in the challenging environment of the cloud market. We also aimed to apply various autonomous agents to build the new algorithms which can be used to create novel negotiation strategies for addressing the issues in SLAs in cloud computing. The monitoring approach based on the CloudSim tool was found to be an effective strategy for detecting violations against the SLA, which can be an important contribution to building effective monitoring solutions for improving the quality of services in the cloud market

How is Water Privatisation Justified? Frame Analysis of Poverty Reduction Strategy Papers (PRSPs).

Tutkielman lähtökohtana on oletus, että neoklassisesta talousteoriasta voidaan johtaa erityinen oikeusteoria, joka selittää veden yksityistämisen oikeutuksen. Tutkielman tavoitteena on kuvailla miten ja miksi veden yksityistämistä oikeutetaan kolmen tutkimuskysymyksen avulla: Minkälaisia ongelmia voidaan tunnistaa puhtaan juomaveden saannissa? Minkälaisia yksityistämistoimenpiteitä ehdotetaan näiden ongelmien ratkaisemiseksi? Miten näitä veden yksityistämistoimenpiteitä oikeutetaan? Tutkimuskysymykset kontekstualisoidaan tarkastelemalla kattavasti veden yksityistämisen historiaa ja nykyistä asemaa osana laajempaa neoliberaalia projektia sekä tutkimalla neoklassisen talousteorian normatiivista taustaa Pareto-optimaalisuuteen liittyvän käsitteistön avulla. Tutkimuksen aineistona käytetään 25:tä köyhyydenvähennysstrategiapaperia (Poverty Reduction Strategy Papers), jotka 25 matalan tulotason maata ovat julkaisseet yhteistyössä Maailmanpankin ja Kansainvälisen valuuttarahaston kanssa vuosina 2010-2014. Aineistoa tarkastellaan pääosin laadullisen tutkimuksen keinoin hyödyntämällä niin sisältö- kuin kehysanalyysiä tutkimusmenetelminä. Aineiston analyysin aikana esiin nousi ensiksi se, että huolimatta vesiongelmien laajuudesta ja suurista eroavaisuuksista, veden saannin ongelmat liittyivät pääasiallisesti veden epätasaiseen ja -oikeudenmukaiseen jakoon eikä niinkään veden aineelliseen niukkuuteen. Toiseksi tutkimus löysi kolme veden yksityistämistoimenpiteen strategiaa, joita olivat yksityistämisen strategia, kaupallistamisen strategia ja hallinnon vapauttamisen strategia. Viimeiseksi tutkimus löysi aineistoa tarkastelemalla neljä pääkehystä. Nämä kehykset olivat edistyksen kehys, taloudellisen hyödykkeen kehys, hallituksen vastainen kehys ja oikeuskehys. Tutkimustulokset viittaavat siihen, että veden yksityistämistoimenpiteet enenevissä määrin hämärtävät ’julkisen’ ja ’yksityisen’ välisen eron. Tämä tarkoittaa sitä, että ’julkinen’ toimii jo pitkälti markkinalogiikan mukaan eikä ero veden yksityistämisen ja valtion ohjauksen välillä ole enää yhtä merkittävä. Nämä toimenpiteet ovat oikeutettuja neoklassisesta talousteoriasta johdetun oikeusteorian avulla, joka pohjautuu Pareto-optimaalisuuteen. Näin kansainväliset rahoituslaitokset ja valtiot voivat paradoksaalisesti mahdollistaa vesihuoltojärjestelmien yksityistämistoimenpiteet, koska Pareto-optimaalisuus pyrkii luomaan utopistiset täydellisen kilpailun olosuhteet, missä vesiresurssit jaetaan kaikista tehokkaimmalla ja näin myös kaikista oikeudenmukaisimmalla tavalla.The premise of this thesis is that neoclassical economics as a particular theory of justice explains the justification of water privatisation. Hence, the aim of the study is to describe how and why water privatisation is justified by asking three research questions: What problems are distinguished in relation to access to safe drinking water? What privatisation measures are proposed as solutions? How are these water privatisation measures justified? These research questions are contextualised by providing a comprehensive account on the history and present status of water privatisation within the neoliberal project and examining the normative basis of neoclassical economics via the concept of Pareto optimality. This is done by analysing 25 Poverty Reduction Strategy Papers (PRSPs) that were published by 25 low-income countries under the guidance of the World Bank and the International Monetary Fund (IMF) during 2010-2014. These PRSPs are examined through content analysis and frame analysis in a largely qualitatively manner. In the analysis of PRSPs, the thesis found, first, that although the problems in relation to access to water were highly varied, the uneven and unequal access to water was more prevalent than physical water scarcity issues. Secondly, three strategies of privatisation measures were identified in PRSPs: strategy of privatisation, strategy of commercialisation and strategy of liberalisation of governance. Finally, the study found four principal frames justifying water privatisation in PRSPs. These frames were development frame, economic good frame, anti-government frame and right frame. The results suggest that water privatisation measures increasingly blur the distinction between ‘public’ and ‘private’. This implies that the ‘public’ is largely guided by the market logic, and thus the difference between water privatisation and public sector control is increasingly irrelevant. These privatisation measures are justified by drawing on neoclassical economics as a theory of justice that is based on Pareto optimality. This way, international financial institutions (IFIs) and states can paradoxically allow for privatisation measures in water supply systems since it can ideally create the conditions for perfect competition whereby water resources become allocated in the most efficient, and thus in the most just way

Economic Algorithms for the Management of Resources in Computer Systems

Cloud computing and distributed Grid computations in the e-science and commercial spheres are beginning to make accessible huge amounts of computing power with “just in time” availability. However, the economic models surrounding these systems are static and uniform, with charging models that, for web-based cloud systems work on a price per unit per hour basis, whilst for educational type resources, fixed contractual arrangements and multi-year projects are more prevalent. The common place practice of using just-in-time capacity planning and variable pricing algorithms, such as those pioneered by airlines like EasyJet, tells us that the cost of delivering these services and the price that should be paid for them is a much more complex beast. Future Grid and Cloud Computing computations will be enabled by participants trading resources in order to construct bundles of goods or services in both new commercial arenas and the more well established “e-science” experiments in science, engineering and, now emerging, social sciences. A combinatorial auction (CA) is a natural choice for determining the optimal allocation for a bundle of required goods and services, but the space and time dimensions that characterise a Grid compute cloud would appear to indicate they are incompatible. This thesis proposes that an analogue of a physical commodities market is more appropriate for distributed resource allocation and that there is a class of bundling problems whose complexity properties appear to make the utilisation of a CA impractical. We therefore compare the two techniques for resource bundling and investigate the crossover point, to enrich our understanding of how combinatorial auctions and distributed markets may be used together to improve distributed resource allocation practices.EThOS - Electronic Theses Online ServiceGBUnited Kingdo

Intelligent facial emotion recognition using moth-firefly optimization

In this research, we propose a facial expression recognition system with a variant of evolutionary firefly algorithm for feature optimization. First of all, a modified Local Binary Pattern descriptor is proposed to produce an initial discriminative face representation. A variant of the firefly algorithm is proposed to perform feature optimization. The proposed evolutionary firefly algorithm exploits the spiral search behaviour of moths and attractiveness search actions of fireflies to mitigate premature convergence of the Levy-flight firefly algorithm (LFA) and the moth-flame optimization (MFO) algorithm. Specifically, it employs the logarithmic spiral search capability of the moths to increase local exploitation of the fireflies, whereas in comparison with the flames in MFO, the fireflies not only represent the best solutions identified by the moths but also act as the search agents guided by the attractiveness function to increase global exploration. Simulated Annealing embedded with Levy flights is also used to increase exploitation of the most promising solution. Diverse single and ensemble classifiers are implemented for the recognition of seven expressions. Evaluated with frontal-view images extracted from CK+, JAFFE, and MMI, and 45-degree multi-view and 90-degree side-view images from BU-3DFE and MMI, respectively, our system achieves a superior performance, and outperforms other state-of-the-art feature optimization methods and related facial expression recognition models by a significant margin

Economic algorithms for the management of resources in computer systems

Cloud computing and distributed Grid computations in the e-science and commercial spheres are beginning to make accessible huge amounts of computing power with “just in time” availability. However, the economic models surrounding these systems are static and uniform, with charging models that, for web-based cloud systems work on a price per unit per hour basis, whilst for educational type resources, fixed contractual arrangements and multi-year projects are more prevalent. The common place practice of using just-in-time capacity planning and variable pricing algorithms, such as those pioneered by airlines like EasyJet, tells us that the cost of delivering these services and the price that should be paid for them is a much more complex beast. Future Grid and Cloud Computing computations will be enabled by participants trading resources in order to construct bundles of goods or services in both new commercial arenas and the more well established “e-science” experiments in science, engineering and, now emerging, social sciences. A combinatorial auction (CA) is a natural choice for determining the optimal allocation for a bundle of required goods and services, but the space and time dimensions that characterise a Grid compute cloud would appear to indicate they are incompatible. This thesis proposes that an analogue of a physical commodities market is more appropriate for distributed resource allocation and that there is a class of bundling problems whose complexity properties appear to make the utilisation of a CA impractical. We therefore compare the two techniques for resource bundling and investigate the crossover point, to enrich our understanding of how combinatorial auctions and distributed markets may be used together to improve distributed resource allocation practices.EThOS - Electronic Theses Online ServiceGBUnited Kingdo