# ARAAC: A Rational Allocation Approach in Cloud Data Center Networks
## 1 Introduction and Problem Statement  
The technological era we are living these days in almost all aspects of life necessitates the need of powerful, scalable, highly available, and easily accessible computing environments. In this context, cloud computing has emerged as a promising choice for a computing platform that satisfies the aforementioned requirements, with big savings in cost and power. A clear convergence of such cloud-based computing environments and the advancement in information technologies can be deeplytouched in people's life styles nowadays, especially when it comes to their social aspects and work activities, which tend to be overwhelmed by a completely new smart-space. Moreover, developments in Big-Data and Internet of Things applications have allowed for a huge and smart era in other life aspects, such as economy, health, and education. This implicitly means higher dependencies on the existing communication and computing technologies. Typically, cloud computing environments are hosted in Data Centers (DCs) that interconnect massive amounts of networked computing resources laid in _servers_ to support a huge number of applications. The provisioning process of these kind of applications does not only depend on the computing resources that run the applications, but also on the communication resources offered by the network infrastructures necessary for efficient service delivery [1; 2]. This includes both: (1) the communication between the DC components, and (2) the communication between the DC as an entity and its users. Moreover, through high speed _network infrastructures_, servers of various DCs may get connected together to allow for parallel implementation of cloud-services. Such a combination of networking and cloud computing DC resources is referred to as _cloud Data Center Networking_ (cloud-DCN) [3]. Through this, both network and cloud computing resources are provisioned to the users in the forms of services. Hence, provision of these kinds of networked computing resources may cover both intra- and/or inter-data center networking. However, our study is mainly concerned with the intra-data center networking services. In cloud-DCNs, network and server resources are allocated to the interested users in the form of services (e.g., Infrastructure as a Service (IaaS)). Such allocation scenarios mainly depend on the users reveals for their service requirements (i.e., network and server resources). However, statistics are showing tremendous increases in the traffic every year. To cope with this, sufficient capacities are required in the cloud-DCN infrastructures. Now, with these expectations for huge growth in the global network traffic, and with the absence of an efficient resource allocation model in such scenarios, entering a resource depletion age is becoming inevitable sooner than ever. Proposals for the auction-based resource allocation in the literature are no longer satisfying, as they do not provide real win-win models that consider the interest of both parties, that is, the cloud-DCN providers and their service-tenants. A few proposals provide for _greedy_ profit maximization that targets either the providers or the tenants, but not both. Moreover, such proposals lack efficient policies that stress the issue of resource utilization, which has a direct impact on resultant profit rates/service price units, and resource availability that greatly affects the users' satisfaction rates. In summary, proposals in the literature have the following limitations: (1) they do not provide real profit maximization for the cloud-DCN providers, as they lack the proper mechanisms that create forms of competition among the service tenants; (2) they do not provide the real satisfaction requirements of the service tenants, which are represented by both competing price units and guaranteed resource availability; (3) they do not provide efficient mechanisms that encourage resource utilization behaviors, which are proven to be necessary in such environments.