Large cloud and content (service) providers serve applications that are responsible for the vast majority of Internet traffic today. However, service providers have to contend with decades-old Internet protocols to do so and, in particular, to route latency sensitive user traffic over the public Internet to service provider networks. This reliance creates urgent problems as businesses/people/governments increasingly rely on the Internet for critical activities, and as new applications such as VR introduce increasingly strict network performance requirements. This dissertation explores the extent to which current ways service providers use the Internet's old protocols are sufficient to meet demands of today's and tomorrows applications. It then proposes using these old Internet protocols in new ways to reliably route user traffic over an unreliable public Internet by solving challenging optimization problems using new Internet measurement and modeling techniques. The systems described in this dissertation can help service providers work with existing infrastructure to deliver the reliable, performant service our increasingly connected society needs.

Cloud computing which provides computation and storage resources in a pay-per-usage manner has emerged as the most popular computation model nowadays. Under the new paradigm, users are able to request computation resources dynamically in real-time to accommodate their workload requirements. The flexible resource allocation feature endows cloud computing services with the capability to offer affordable and efficient computation services. However, moving data and applications into the cloud exposes a privacy leakage risk of the user data. As the growing awareness of data privacy, more and more users begin to choose proactive protection for their data in the cloud through data encryption. One major problem of data encryption is that it hinders many necessary data utilization functions since most of the functions cannot be directly applied to the encrypted data. The problem could potentially jeopardize the popularity of the cloud computing, therefore, achieving efficient data utilization over encrypted data while preserving user data privacy is an important research problem in cloud computing. The focus of this dissertation is to design secure and efficient schemes to address essential data utilization functions over encrypted data in cloud computing. To this end, we studied three problems in this research area. The first problem that is studied in this dissertation is fuzzy multi-keyword search over encrypted data. As fuzzy search is one of the most useful and essential data utilization functions in our daily life, we propose a novel design that incorporates Bloom filter and Locality-Sensitive Hashing to fulfill the security and function requirements of the problem. Secondly, we propose a secure index which is based on the most popular index structure, i.e., the inverted index. Our innovative design provides privacy protection over the secure index, the user query as well as the search pattern and the search result. Also, users can verify the correctness of the search results to ensure the proper computation is performed by the cloud. Finally, we focus ourselves on the privacy-sensitive data application in cloud computing, i.e., genetic testings over DNA sequences. To provide secure and efficient genetic testings in the cloud, we utilize Predicate Encryption and design a bilinear pairing based secure sequence matching scheme to achieve strong privacy guarantee while fulfilling the functionality requirement efficiently. In all of the three research thrusts, we present thorough theoretical security analysis and extensive simulation studies to evaluate the performance of the proposed schemes. The results demonstrate that the proposed schemes can effectively and efficiently address the challenging problems in practice. / Ph. D.

The cloud computing paradigm is realized through large scale distributed resource management and computation platforms such as MapReduce, Hadoop, Dryad, and Pregel. These platforms enable quick and efficient development of a large range of applications that can be sustained at scale in a fault-tolerant fashion. Two key technologies, namely resource virtualization and feature-rich enterprise storage, are further driving the wide-spread adoption of virtualized cloud environments. Many challenges arise when designing resource management techniques for both native and virtualized data centers. First, parameter tuning of MapReduce jobs for efficient resource utilization is a daunting and time consuming task. Second, while the MapReduce model is designed for and leverages information from native clusters to operate efficiently, the emergence of virtual cluster topology results in overlaying or hiding the actual network information. This leads to two resource selection and placement anomalies: (i) loss of data locality, and (ii) loss of job locality. Consequently, jobs may be placed physically far from their associated data or related jobs, which adversely affect the overall performance. Finally, the extant resource provisioning approach leads to significant wastage as enterprise cloud providers have to consider and provision for peak loads instead of average load (that is many times lower). In this dissertation, we design and develop a resource management framework to address the above challenges. We first design an innovative resource scheduler, CAM, aimed at MapReduce applications running in virtualized cloud environments. CAM reconciles both data and VM resource allocation with a variety of competing constraints, such as storage utilization, changing CPU load and network link capacities based on a flow-network algorithm. Additionally, our platform exposes the typically hidden lower-level topology information to the MapReduce job scheduler, which enables it to make optimal task assignments. Second, we design an online performance tuning system, mrOnline, which monitors the MapReduce job execution, tunes the parameters based on collected statistics and provides fine-grained control over parameter configuration changes to the user. To this end, we employ a gray-box based smart hill-climbing algorithm that leverages MapReduce runtime statistics and effectively converge to a desirable configuration within a single iteration. Finally, we target enterprise applications in virtualized environment where typically a network attached centralized storage system is deployed. We design a new protocol to share primary data de-duplication information available at the storage server with the client. This enables better client-side cache utilization and reduces server-client network traffic, which leads to overall high performance. Based on the protocol, a workload aware VM management strategy is further introduced to decrease the load to the storage server and enhance the I/O efficiency for clients. / Ph. D.

Traditionally, VLANs have been the most suitable solution for connecting computers. This, in line with the increased use of cloud services in recent years, has given rise to problems with scalability and security within VLAN networks, which need to be investigated. An alternative to VLAN is VXLAN, which was created specifically to be able to solve the shortcomings brought about by VLAN and to be able to function within a cloud environment.VXLAN has inherited many of VLAN's shortcomings, which is why this thesis concerns the security aspects within a simulated VXLAN network. This has been carried out by attacking the simulation with well-known attacks such as ARP spoofing, Ping of Death, MAC flooding, UDP flood attack, Time to live expiry attack, ICMP port unreachable and Sockstress. The goal of this thesis was to examine the attacks in terms of effectiveness and how well the proposed countermeasures worked. From the results of the study, it can be stated that the proposed measures did not necessarily have to be complicated in design, but as long as they were well-planned and feasible, the measures could defend the network against most of the attacks used in the study. / Traditionellt sett har VLAN varit den mest lämpade lösningen för att ansluta datorer. Detta har i takt med ökad användning av molntjänster de senaste åren gett upphov till problem med skalbarhet och säkerhet inom VLAN-nätverk, som behöver utredas. Ett alternativ till VLAN är VXLAN som skapades särskilt för att kunna lösa de brister som VLAN medfört och att kunna fungera inom en molnmiljö.VXLAN har ärvt många av VLANs brister, vilket var anledningen till varför denna uppsatsberör säkerhetsaspekter inom ett simulerat VXLAN- nätverk. Detta har genomförts genom att angripa simulationen med välkända attacker såsom ARP spoofing, Ping of Death, MAC flooding, UDP flood attack, Time to live expiry attack, ICMP port unreachable samt Sockstress. Målet med denna uppsats var att undersöka attackerna utefter effektivitet och hur väl de föreslagna åtgärderna fungerade. Från studiens resultat kan det konstateras att de föreslagna åtgärderna inte nödvändigtvis behövde vara komplicerat utformade, utan så länge de var välplanerade och genomförbara kunde åtgärderna försvara nätverket mot de flesta av studiens attacker.

Past few years have witnessed a dramatic shift for IT infrastructures from a self-sustained model to a centralized and multi-tenant elastic computing paradigm -- Cloud Computing, which significantly reshapes the landscape of existing data utilization services. In truth, public cloud service providers (CSPs), e.g. Google, Amazon, offer us unprecedented benefits, such as ubiquitous and flexible access, considerable capital expenditure savings and on-demand resource allocation. Cloud has become the virtual ``brain" as well to support and propel many important applications and system designs, for example, artificial intelligence, Internet of Things, and so forth; on the flip side, security and privacy are among the primary concerns with the adoption of cloud-based data services in that the user loses control of her/his outsourced data. Encrypting the sensitive user information certainly ensures the confidentiality. However, encryption places an extra layer of ambiguity and its direct use may be at odds with the practical requirements and defeat the purpose of cloud computing technology. We believe that security in nature should not be in contravention of the cloud outsourcing model. Rather, it is expected to complement the current achievements to further fuel the wide adoption of the public cloud service. This, in turn, requires us not to decouple them from the very beginning of the system design. Drawing the successes and failures from both academia and industry, we attempt to answer the challenges of realizing efficient and useful secure data services in the public cloud. In particular, we pay attention to security and privacy in two essential functions of the cloud ``brain", i.e. data storage and processing. Our first work centers on the secure chunk-based deduplication of encrypted data for cloud backup and achieves the performance comparable to the plaintext cloud storage deduplication while effectively mitigating the information leakage from the low-entropy chunks. On the other hand, we comprehensively study the promising yet challenging issue of search over encrypted data in the cloud environment, which allows a user to delegate her/his search task to a CSP server that hosts a collection of encrypted files while still guaranteeing some measure of query privacy. In order to accomplish this grand vision, we explore both software-based secure computation research that often relies on cryptography and concentrates on algorithmic design and theoretical proof, and trusted execution solutions that depend on hardware-based isolation and trusted computing. Hopefully, through the lens of our efforts, insights could be furnished into future research in the related areas. / Ph. D. / Past few years have witnessed a dramatic shift for IT infrastructures from a self-sustained model to a centralized and multi-tenant elastic computing paradigm – Cloud Computing, which significantly reshapes the landscape of existing data utilization services. In truth, public cloud service providers (CSPs), e.g. Google, Amazon, offer us unprecedented benefits, such as ubiquitous and flexible access, considerable capital expenditure savings and on-demand resource allocation. Cloud has become the virtual “brain” as well to support and propel many important applications and system designs, for example, artificial intelligence, Internet of Things, and so forth; on the flip side, security and privacy are among the primary concerns with the adoption of cloud-based data services in that the user loses control of her/his outsourced data. Encryption definitely provides strong protection to user sensitive data, but it also disables the direct use of cloud data services and may defeat the purpose of cloud computing technology. We believe that security in nature should not be in contravention of the cloud outsourcing model. Rather, it is expected to complement the current achievements to further fuel the wide adoption of the public cloud service. This, in turn, requires us not to decouple them from the very beginning of the system design. Drawing the successes and failures from both academia and industry, we attempt to answer the challenges of realizing efficient and useful secure data services in the public cloud. In particular, we pay attention to security and privacy in two essential functions of the cloud “brain”, i.e. data storage and processing. The first part of this research aims to provide a privacy-preserving data deduplication scheme with the performance comparable to the existing cloud backup storage deduplication. In the second part, we attempt to secure the fundamental information retrieval functions and offer effective solutions in various contexts of cloud data services.

A future Internet of Things (IoT) system will consist of a huge quantity of heterogeneous IoT devices, each capable of providing services upon request. It is of utmost importance for an IoT device to know if another IoT service is trustworthy when requesting it to provide a service. In this dissertation research, we develop trust-based service management techniques applicable to distributed, centralized, and hybrid IoT environments. For distributed IoT systems, we develop a trust protocol called Adaptive IoT Trust. The novelty lies in the use of distributed collaborating filtering to select trust feedback from owners of IoT nodes sharing similar social interests. We develop a novel adaptive filtering technique to adjust trust protocol parameters dynamically to minimize trust estimation bias and maximize application performance. Our adaptive IoT trust protocol is scalable to large IoT systems in terms of storage and computational costs. We perform a comparative analysis of our adaptive IoT trust protocol against contemporary IoT trust protocols to demonstrate the effectiveness of our adaptive IoT trust protocol. For centralized or hybrid cloud-based IoT systems, we propose the notion of Trust as a Service (TaaS), allowing an IoT device to query the service trustworthiness of another IoT device and also report its service experiences to the cloud. TaaS preserves the notion that trust is subjective despite the fact that trust computation is performed by the cloud. We use social similarity for filtering recommendations and dynamic weighted sum to combine self-observations and recommendations to minimize trust bias and convergence time against opportunistic service and false recommendation attacks. For large-scale IoT cloud systems, we develop a scalable trust management protocol called IoT-TaaS to realize TaaS. For hybrid IoT systems, we develop a new 3-layer hierarchical cloud structure for integrated mobility, service, and trust management. This architecture supports scalability, reconfigurability, fault tolerance, and resiliency against cloud node failure and network disconnection. We develop a trust protocol called IoT-HiTrust leveraging this 3-layer hierarchical structure to realize TaaS. We validate our trust-based IoT service management techniques developed with real-world IoT applications, including smart city air pollution detection, augmented map travel assistance, and travel planning, and demonstrate that our trust-based IoT service management techniques outperform contemporary non-trusted and trust-based IoT service management solutions. / Ph. D. / A future Internet of Things (IoT) system will consist of a huge quantity of heterogeneous IoT devices, each capable of providing services upon request. It is of utmost importance for an IoT device to know if another IoT service is trustworthy when requesting it to provide a service. In this dissertation research, we develop trust-based service management techniques applicable to distributed, centralized, and hybrid IoT environments. We have developed a distributed trust protocol called Adaptive IoT Trust for distributed IoT applications, a centralized trust protocol called IoT-TaaS for centralized IoT applications with cloud access, and a hierarchical trust management protocol called IoT-HiTrust for hybrid IoT applications. We have verified that desirable properties, including solution quality, accuracy, convergence, resiliency, and scalability have been achieved. Furthermore, we validate our trust-based IoT service management techniques developed with real-world IoT applications, including smart city air pollution detection, augmented map travel assistance, and travel planning, and demonstrate that our trust-based IoT service management techniques outperform contemporary non-trusted and trust-based IoT service management solutions.

[ES] La Gestión de la Cadena de Suministro se define como un conjunto de acciones que permiten a las empresas gestionar, planificar y controlar sus operaciones como una forma de facilitar la colaboración entre los miembros de la Cadena de Suministro. Para ser más eficaces y eficientes, las empresas están cada vez más dispuestas a rediseñar sus estrategias de Gestión de la Cadena de Suministro y a adoptar prácticas de gestión. Esta tesis doctoral analiza cómo se interrelacionan algunas variables relacionadas con la eficacia y la eficiencia en la Gestión de la Cadena de Suministro, y el posible impacto de estas interrelaciones en los resultados empresariales. Específicamente, profundizamos en las relaciones entre Cloud Computing, Integración de la Cadena de Suministro, Flexibilidad de la Cadena de Suministro, Personalización en Masa y Lean Production (que son variables asociadas con la eficacia y eficiencia de la Cadena de Suministro) y su papel en los resultados empresariales. En esta tesis, inicialmente consideramos dos factores importantes para conseguir eficacia y eficiencia en la Cadena de Suministro. Así, un primero factor estaría formado por la interrelación entre el uso de Cloud Computing, un nuevo paradigma en la interpretación de las Tecnologías de la información, y la Integración de la Cadena de Suministro. Bajos niveles en este factor permitirán a las empresas conseguir sus objetivos (ser eficaces) pero empleando muchos más recursos (menos eficientes) que altos valores en este factor. Un segundo factor recoge la interrelación de la Flexibilidad de la Cadena de Suministro y la Personalización en Masa. De forma similar al factor anterior, bajos niveles en este factor estarían asociados a una menor eficiencia (aun siendo eficaces), mientras que altos niveles, estaría asociados a una alta eficiencia. Ambos factores son consideradas en esta tesis, en primer lugar, de forma aislada, mediante revisiones sistemáticas de la literatura que permiten identificar qué se sabe en la literatura sobre la relación existente entre las variables que conforman cada factor. En segundo lugar, en esta tesis, se realiza un análisis explicativo en que se considera el efecto de Lean Production, y su relación con cada uno de los factores, lo que estaría asociado a unos altos niveles de eficiencia en la Cadena de Suministro, y se analiza cómo el efecto conjunto de Lean Production y cada uno de los factores (variables) consideradas afecta a los resultados de la empresa. Finalmente, en esta tesis se consideran todas las variables de forma conjunta (ambos factores y el efecto de Lean Production, actuando sobre los resultados empresariales), en un modelo holístico que utiliza la simulación para analizar el comportamiento del modelo. El valor de esta tesis es que académicos y gerentes de negocios pueden tener evidencia de apoyo sobre el papel que juegan Cloud Computing, Integración de la Cadena de Suministro, Flexibilidad de la Cadena de Suministro, Personalización en Masa y Lean Production, vinculadas operativa y estratégicamente, y cómo esta combinación podría transformarse en un mejor desempeño empresarial. El mejor conocimiento de estas relaciones puede afectar la manera en que investigadores y directivos abordan estos recursos de gestión, siendo más conscientes del importante papel de la Cadena de Suministro en la competitividad. Este trabajo se diferencia de los aportes anteriores por proporcionar enfoques teóricos y empíricos de las posibles interrelaciones entre las variables antes mencionadas. Los resultados de este estudio, por lo tanto, podrían ser muy útiles en el diseño de futuros esfuerzos de investigación en esta área. / [CA] La Gestió de la Cadena de Subministrament es defineix com un conjunt d'accions que permeten a les empreses gestionar, planificar i controlar les seues operacions com una manera de facilitar la col·laboració entre els membres de la Cadena de Subministrament. Per a ser més eficaços i eficients, les empreses estan cada vegada més disposades a redissenyar les seues estratègies de Gestió de la Cadena de Subministrament i a adoptar pràctiques de gestió. Aquesta tesi doctoral analitza com s'interrelacionen algunes variables relacionades amb l'eficàcia i l'eficiència en la Gestió de la Cadena de Subministrament, i el possible impacte d'aquestes interrelacions en els resultats empresarials. Específicament, aprofundim en les relacions entre Cloud Computing, Integració de la Cadena de Subministrament, Flexibilitat de la Cadena de Subministrament, Personalització en massa i Lean Production (que són variables associades amb l'eficàcia i eficiència de la Cadena de Subministrament) i el seu paper en els resultats empresarials. En aquesta tesi, inicialment considerem dos factors importants per a aconseguir eficàcia i eficiència en la Cadena de Subministrament. Així, un primer factor estaria format per la interrelació entre l'ús de Cloud Computing, un nou paradigma en la interpretació de les Tecnologies de la informació, i la Integració de la Cadena de Subministrament. Baixos nivells en aquest factor permetran a les empreses aconseguir els seus objectius (ser eficaços) però emprant molts més recursos (menys eficients) que alts valors en aquest factor. Un segon factor recull la interrelació de la Flexibilitat de la Cadena de Subministrament i la Personalització en massa. De forma similar al factor anterior, baixos nivells en aquest factor estarien associats a una menor eficiència (fins i tot sent eficaces), mentre que alts nivells, estaria associats a una alta eficiència. Tots dos factors són considerades en aquesta tesi, en primer lloc, de forma aïllada, mitjançant revisions sistemàtiques de la literatura que permeten identificar què se sap en la literatura sobre la relació existent entre les variables que conformen cada factor. En segon lloc, en aquesta tesi, es realitza una anàlisi explicativa en què es considera l'efecte de Lean Production, i la seua relació amb cadascun dels factors, la qual cosa estaria associat a uns alts nivells d'eficiència en la Cadena de Subministrament, i s'analitza com l'efecte conjunt de Lean Production i cadascun dels factors (variables) considerades afecta als resultats de l'empresa. Finalment, en aquesta tesi es consideren totes les variables de forma conjunta (tots dos factors i l'efecte de Lean Production, actuant sobre els resultats empresarials), en un model holístic que utilitza la simulació per a analitzar el comportament del model. El valor d'aquesta tesi és que acadèmics i gerents de negocis poden tindre evidència de suport sobre el paper que juguen Cloud Computing, Integració de la Cadena de Subministrament, Flexibilitat de la Cadena de Subministrament, Personalització en massa i Lean Production, vinculades operativa i estratègicament, i com aquesta combinació podria transformar-se en un millor acompliment empresarial. El millor coneixement d'aquestes relacions pot afectar la manera en què investigadors i directius aborden aquests recursos de gestió, sent més conscients de l'important paper de la Cadena de Subministrament en la competitivitat. Aquest treball es diferencia de les aportacions anteriors per proporcionar enfocaments teòrics i empírics de les possibles interrelacions entre les variables abans esmentades. Els resultats d'aquest estudi, per tant, podrien ser molt útils en el disseny de futurs esforços d'investigació en aquesta àrea. / [EN] Supply Chain Management is defined as a set of actions that allow companies to manage, plan and control their operations as a way to facilitate collaboration between Supply Chain members. To be more effective and efficient, companies are increasingly willing to redesign their Supply Chain Management strategies and adopt management practices. This doctoral thesis analyses how some variables related to effectiveness and efficiency in Supply Chain Management are interrelated, and the possible impact of these interrelations on business performance. Specifically, we delve into the relationships between Cloud Computing, Supply Chain Integration, Supply Chain Flexibility, Mass Personalization and Lean Production (which are variables associated with the effectiveness and efficiency in the Supply Chain) and their role in business performance. In this doctoral thesis, we initially considered two important factors to achieve effectiveness and efficiency in the Supply Chain. A first factor would be the interrelation between the use of Cloud Computing, a new paradigm in the interpretation of Information Technologies, and Supply Chain Integration. Low levels in this factor will allow companies to achieve their goals (be effective) but using many more resources (less efficient) than high values in this factor. A second factor is the interrelationship of Supply Chain Flexibility and Mass Personalization. Similar to the previous factor, low levels of this factor would be associated with lower efficiency (even if effective), while high levels would be associated with high efficiency. Both factors are considered in this thesis, in the first place, in an isolated way, by means of systematic literature reviews that allow identifying what is known in the literature about the existing relation between the variables that conform each factor. Secondly, an explanatory analysis is made in which the effect of Lean Production is considered, and its relation with each one of the factors, which would be associated with high levels of efficiency in the Supply Chain, and it is analysed how the joint effect of Lean Production and each one of the factors (variables) considered affects business performance. Finally, this thesis considers all variables together (both factors and the effect of Lean Production, acting on business performance), in a holistic model that uses simulation to analyse the model's behaviour. The value of this doctoral thesis is that academics and business managers can have supporting evidence on the role played by Cloud Computing, Supply Chain Integration, Supply Chain Flexibility, Mass Personalization and Lean Production, operationally and strategically linked, and how this combination could be transformed into better business performance. The better knowledge of these relationships can affect the way researchers and managers approach these management resources, being more aware of the important role of the Supply Chain in competitiveness. This work differs from previous contributions in that it provides theoretical and empirical approaches to the possible interrelations between the variables mentioned above. The results of this study, therefore, could be very useful in the design of future research efforts in this area. / This doctoral thesis has been developed thanks to the support of the Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) of Brazil and the Spanish Ministry of Economy and Competitiveness Research Project ECO2015-65874-P. / Romualdo Novais, L. (2019). CLOUD COMPUTING, SUPPLY CHAIN INTEGRATION, SUPPLY CHAIN FLEXIBILITY AND MASS PERSONALIZATION: INTERRELATIONSHIPS WITH LEAN PRODUCTION AND PERFORMANCE [Tesis doctoral]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/121460

Yes / Government organisations have been shifting to cloud-based services in order to reduce their total investments in IT infrastructures and resources (e.g. data centers), as well as capitalise on cloud computing’s numerous rewards. However, just like any other technology investments there are also concerns over the potential risks of implementing cloud-based technologies. Such concerns and the paucity of scholarly literature focusing on cloud computing from a governmental context confirm the need for exploratory research and to draw lessons for government authorities and others in order to ensure a reduction in costly mistakes. This paper therefore investigates the implementation of cloud computing in both a practical setting and from an organisational user perspective via three UK local government authorities. Through the qualitative case study enquiries, the authors are able to extrapolate perceived rewards and risks factors which are mapped against the literature so that emergent factors can be identified. All three cloud deployments resulted in varying outcomes which included key rewards such as improved information management, flexibility of work practices and also posed risks such as loss of control and lack of data ownership to the organisations. These findings derived from the aggregated organisational user perspectives will be of benefit to both academics and practitioners engaged in cloud computing research and its strategic implementation in the public sector.

Yes / This study seeks to investigate the effectiveness of Cloud Computing Utilization (CCU) in the mitigation of informational and marketing barriers for SMEs from the Emerging Market-Countries (EM-SMEs). A quantitative-research methodology was applied to collect data by using self-administered questionnaires from top managers of 227 SMEs based in Iran and Turkey. The study contributes theoretically to both small business and international business literature by developing a new classification of the internationalization barriers that EM-SMEs face, and proposing a series of cloud computing (CC) solutions for mitigating these barriers, resulting in the creation and testing of a new model. The empirical findings confirm that CCU can help EM-SMEs to mitigate a series of informational and marketing barriers. The key practical contributions of the study offer insights to both EM-SMEs and Cloud-Service-Providers (CSPs) on the extent to which CCU is effective in mitigating the internationalization barriers faced by EM-SMEs.

Yes / Fault tolerance is the ability of a system to respond swiftly to an unexpected failure. Failures in a cloud computing environment are normal rather than exceptional, but fault detection and system recovery in a real time cloud system is a crucial issue. To deal with this problem and to minimize the risk of failure, an optimal fault tolerance mechanism was introduced where fault tolerance was achieved using the combination of the Cloud Master, Compute nodes, Cloud load balancer, Selection mechanism and Cloud Fault handler. In this paper, we proposed an optimized fault tolerance approach where a model is designed to tolerate faults based on the reliability of each compute node (virtual machine) and can be replaced if the performance is not optimal. Preliminary test of our algorithm indicates that the rate of increase in pass rate exceeds the decrease in failure rate and it also considers forward and backward recovery using diverse software tools. Our results obtained are demonstrated through experimental validation thereby laying a foundation for a fully fault tolerant IaaS Cloud environment, which suggests a good performance of our model compared to current existing approaches. / Petroleum Technology Development Fund (PTDF)