<p>Energy efficiency, which has emerged as a top priority in cloud ecosystems, is the outcome of appropriate pricing mechanisms and resource allocations. Static pricing mechanisms are the most dominant approaches, which are simple to implement for the service providers and easy to understand for the service users. Inaccurate price calculation and low efficient resource allocation in static pricing mechanisms made researchers discover other solutions to overcome these issues. Double auction mechanisms are among the most appropriate dynamic models. The main challenge of conventional double auction mechanisms is not considering the cloud ecosystems’ specifications, such as dynamic online features. The term dynamic refers to the variable parameters in cloud ecosystems that constantly change. In dynamic online methods, we customize our pricing models</p> <p>based on ever-changing and current parameters. Moreover, we continuously optimize these methods to attain optimal results. In the thesis, firstly, we define a  Dynamic Online Double Auction Mechanism (DODAM) for the IaaS environment, which covers a broader range of IaaS parameters by considering the dynamic online features of such markets. DODAM provides an appropriate price scheduling for service providers and service users by considering cloud dynamic online features. Cloud secondary market is a new paradigm in IaaS ecosystems. In these markets, brokers and reseller buyers have attained their resources from service providers of the cloud primary markets in the form of timed packages and repackage them into smaller chunks. As unsold packages do not transfer to the next intervals, brokers and reseller  buyers need to sell their packages as much as possible. We develop a mechanism design that includes a market-based pricing model and a resource allocation algorithm in such markets as our second contribution. By formulating the inherent competitive features in cloud secondary markets in the third contribution, we improve the pricing and resource allocation mechanisms in such competitive ecosystems. In the last contribution, we proposed a  Priority-based Dynamic Online Double Auction Model (PB- DODAM), considering the perishability and time constraints of traded resources in IaaS secondary markets. The provided experimental results show that all proposed mechanisms drastically increase resource  utilization and the overall utility.</p>

<p>Energy efficiency, which has emerged as a top priority in cloud ecosystems, is the outcome of appropriate pricing mechanisms and resource allocations. Static pricing mechanisms are the most dominant approaches, which are simple to implement for the service providers and easy to understand for the service users. Inaccurate price calculation and low efficient resource allocation in static pricing mechanisms made researchers discover other solutions to overcome these issues. Double auction mechanisms are among the most appropriate dynamic models. The main challenge of conventional double auction mechanisms is not considering the cloud ecosystems’ specifications, such as dynamic online features. The term dynamic refers to the variable parameters in cloud ecosystems that constantly change. In dynamic online methods, we customize our pricing models</p> <p>based on ever-changing and current parameters. Moreover, we continuously optimize these methods to attain optimal results. In the thesis, firstly, we define a  Dynamic Online Double Auction Mechanism (DODAM) for the IaaS environment, which covers a broader range of IaaS parameters by considering the dynamic online features of such markets. DODAM provides an appropriate price scheduling for service providers and service users by considering cloud dynamic online features. Cloud secondary market is a new paradigm in IaaS ecosystems. In these markets, brokers and reseller buyers have attained their resources from service providers of the cloud primary markets in the form of timed packages and repackage them into smaller chunks. As unsold packages do not transfer to the next intervals, brokers and reseller  buyers need to sell their packages as much as possible. We develop a mechanism design that includes a market-based pricing model and a resource allocation algorithm in such markets as our second contribution. By formulating the inherent competitive features in cloud secondary markets in the third contribution, we improve the pricing and resource allocation mechanisms in such competitive ecosystems. In the last contribution, we proposed a  Priority-based Dynamic Online Double Auction Model (PB- DODAM), considering the perishability and time constraints of traded resources in IaaS secondary markets. The provided experimental results show that all proposed mechanisms drastically increase resource  utilization and the overall utility.</p>