Due to the development of the Internet and the smart end systems such as smartphones, portable laptop, and other smart mobile devices, as well as the emergence of concepts such as cloud computing, social networks, and Internet of Things, 4G and 5G have changed network requirements. A software-defined network (SDN) is a new architecture to support new network requirements. This architecture is composed of three layers, data, control, and application plane. A lot of papers have been published in well-known journals to improve network performance, so we classify the solutions for performance improvement based on three SDN layers and three SDN-based spheres which are (a) SDN-data center, (b) wireless networks, and (c) software-defined wide area network. This paper surveys the articles which have been published by Springer, IEEE, Elsevier, and ACM. We extract the performance improvement solutions and resources which are required for performance control and the metrics to evaluate the network performance. This article can help network enthusiasts to better understand, investigate, and improve the performance of SDN-based networks.

Performance issues and solutions in SDN-based data center: a survey

The main drivers for the mobile core network evolution is to serve the future challenges and set the way to 5G networks with need for high capacity and low latency. Different technologies such as Network Functions Virtualization (NFV) and Software Defined Networking (SDN) are being considered to address the future needs of 5G networks. However, future applications such as Internet of Things (IoT), video services and others still unveiled will have different requirements, which emphasize the need for the dynamic scalability of the network functionality. The means for efficient network resource operability seems to be even more important than the future network element costs. This paper provides the analysis of different technologies such as SDN and NFV that offer different architectural options to address the needs of 5G networks. The options under consideration in this paper may differ mainly in the extent of what SDN principles are applied to mobile specific functions or to transport network functions only.

SDN and NFV integration in generalized mobile network architecture

Summary
The world of telecommunication is witnessing a swift metamorphosis towards fifth generation cellular networks. Particularly, the rapid shift from a user centric to a device centric communication has created a tremendous impact on service complexity and network requirements. The future networks present requisite needs in ubiquitous throughput, low latency, and high reliability. They are also envisioned to provide energy efficiency, spectrum reuse, network scalability, and robustness as well as improved quality of user experience, which proves to be of ultimate importance. Accordingly, government, academic, and industrial institutions are working together to fulfill these challenging goals. Their research efforts have been extensively reported in various topics and directions, such as heterogeneous small cell networks, millimeter wave communication, massive multiple input multiple output, network function virtualization, software-defined network, and device-to-device communication. More interestingly, a revolutionary network architecture based on cloud computing and centralized processing is adopted as one of the best candidates for fifth generation. It is denoted Cloud Radio Access Network (CRAN) and (H-CRAN) in heterogeneous networks. An upgraded version, namely, Fog RAN (F-RAN), with caching and fog computing capabilities is also presented. Environmental friendly, it ensures flexibility and scalability with reduced expenditures. This paper presents the aforementioned key technological functionalities and surveys the benefits and challenges of CRAN, H-CRAN, and F-RAN.

CRAN, H-CRAN, and F-RAN for 5G systems: Key capabilities and recent advances

Ever since the commercial offerings of the Cloud started appearing in 2006, the landscape of cloud computing has been undergoing remarkable changes with the emergence of many different types of service offerings, developer productivity enhancement tools, and new application classes as well as the manifestation of cloud functionality closer to the user at the edge. The notion of utility computing, however, has remained constant throughout its evolution, which means that cloud users always seek to save costs of leasing cloud resources while maximizing their use. On the other hand, cloud providers try to maximize their profits while assuring service-level objectives of the cloud-hosted applications and keeping operational costs low. All these outcomes require systematic and sound cloud engineering principles. The aim of this paper is to highlight the importance of cloud engineering, survey the landscape of best practices in cloud engineering and its evolution, discuss many of the existing cloud engineering advances, and identify both the inherent technical challenges and research opportunities for the future of cloud computing in general and cloud engineering in particular.

On the Future of Cloud Engineering

Cloud computing enables service operators to efficiently and flexibly utilize resources offered by third party providers instead of having to maintain their own infrastructure. As such, cloud computing offers many advantages over the traditional service delivery model, e.g., failure safety, scalability, cost savings, and a high ease of use. Not only service operators, but also their users benefit from these advantages. As a result, cloud computing has revolutionized service delivery and we observe a tremendous trend for moving services to the cloud. However, this trend of outsourcing services and data to the cloud is limited by serious privacy challenges as evidenced by recent security breaches and privacy incidents such as the global surveillance disclosures. These privacy challenges stem from the technical complexity and missing transparency of cloud computing, opaque legislation with respect to the jurisdiction that applies to users’ data, the inherent centrality of the cloud computing market, and missing control of users over the handling of their data. Overcoming these privacy challenges is key to enable corporate and private users to fully embrace the advantages of cloud computing and hence secure the success of the cloud computing paradigm. Indeed, we observe that cloud providers already account for selected privacy requirements, e.g., by opening special data centers in countries with strict data protection and privacy legislation. Likewise, researchers propose technical approaches to enforce certain privacy requirements either from the client side, e.g., using encryption, or from the service side, e.g., based on trusted hardware. Despite these ongoing efforts, the necessary technical means to fully account for privacy in the cloud computing landscape are still missing. In this dissertation, we approach the pressing problem of privacy in cloud computing from a different direction: Instead of focusing on single actors, we are convinced that overcoming the inherent privacy challenges of cloud computing requires cooperation between the various actors in the cloud computing landscape, i.e., users, service providers, and infrastructure providers. All these different actors have clear incentives to care for privacy and, with the contributions presented in this dissertation, we provide technical approaches that enable each of them to account for privacy. As our first contribution to support users in exercising their privacy, we raise awareness for their exposure to cloud services in the context of email services as well as smartphone apps and enable them to anonymously compare their cloud usage to their peers. With privacy requirements-aware cloud infrastructure as our second contribution, we realize user-specified per-data item privacy policies and enable infrastructure providers to adhere to them. We furthermore support service providers in building privacy-preserving cloud services for the Internet of Things in the context of our third contribution by enabling the transparent processing of protected data and by introducing a distributed architecture to secure the control over devices and networks. Finally, with our fourth contribution, we propose a decentralized cloud infrastructure that enables users who strongly distrust cloud providers to completely shift certain services away from the cloud by cooperating with other users. The contributions of this dissertation highlight that it is both promising and feasible to apply cooperation of different actors to strengthen users’ privacy and consequently enable more corporate and private users to benefit from cloud computing.

Accounting for privacy in the cloud computing landscape

This paper provides an overview of the current LTE architecture and the proposed solutions to integrate Software Defined Network (SDN) technology. The integration of SDN into mobile networks become Software Defined Mobile Network (SDMN), which provides new benefits such as dynamic and efficient caching. Firstly, the paper proposes the integration of SDN in LTE networks on disruptive approach that replaces current mobile transport with SDN based network. Secondly, the benefits of SDN integration to provide optimized content caching is presented. This paper presents a concrete advantage of SDMN for content delivery. Thus, the paper describes the benefits from operator and end user points of view based on a simple scenario of content delivery using dynamic caching reallocation.

SDN optimized caching in LTE mobile networks

Cloud federation is receiving increasing attention due to the benefits of resilience and locality it brings to cloud providers and users. Our analysis of three diverse use cases shows that existing solutions are not addressing the federation needs of such use case applications. In this paper, we present an alternative approach to network federation, providing a model based on cloud-to-cloud agreements. In our scenarios, companies hosting their own OpenStack clouds need to run machines transparently in another cloud, provided by a company they have an agreement with. Our solution provides multiple benefits to cloud providers and users detailed in this paper. Our implementation outperforms the VPNaaS solution in OpenStack in terms of throughput.

/pdf/network-expansion-in-openstack-cloud-federations-bsb64ctyno.pdf

Network expansion in OpenStack cloud federations

Data consumption is increasing rapidly in mobile networks. The cost of the network infrastructure is increasing, which leads to an "end of profit" within next few years. Thus, mobile operators require a new technology that allows increasing the network capacity within low network costs. Therefore, using caching is the most evident solution to be used in their backhaul networks. However, the current architecture of LTE network does not provide sufficient flexibility to place the caches in the most optimal locations. The current work on Software-Defined Networking in Evolved Packet Core virtualization has enabled us to integrate dynamically the caching functionality in a LTE network and improve the caching system performances. In this paper, we will present the solution we designed for this aim based on Software Defined Networking technology. Moreover, we developed a testbed for the proof-of-concept and we will present the results and analyze the performances of this solution.

/pdf/caching-using-software-defined-networking-in-lte-networks-2c3f7kq3bq.pdf

Caching using software-defined networking in LTE networks

Cloud computing offers the potential to store, manage, and process data in highly available, scalable, and elastic environments. Yet, these environments still provide very limited and inflexible means for customers to control their data. For example, customers can neither specify security of inter-cloud communication bearing the risk of information leakage, nor comply with laws requiring data to be kept in the originating jurisdiction, nor control sharing of data with third parties on a fine-granular basis. This lack of control can hinder cloud adoption for data that falls under regulations. In this paper, we show in six use cases how cloud environments can be enriched with policy language support to give customers control over cloud data. Our use cases are based on realizing policy language support in all three cloud environment layers, i.e., IaaS, PaaS, and SaaS. Specifically, we present policy-aware resource management (with OpenStack) and dynamic network configuration. With CERN's big data storage and the in-memory database Hyrise, we show realization for storage and further exemplify policy-aware cloud processing by network function virtualization which enables Orange to offload customer home gateways to the cloud. Finally, we discuss benefits of policy support in F-Secure's Security Cloud. These use cases show the feasibility of realizing customer control with policy support in the cloud. Thus, our work enables customers with regulated data to tap cloud benefits and significantly broadens the market for cloud providers.

Giving Customers Control Over Their Data: Integrating a Policy Language into the Cloud

Mobile data volume is growing with an annual compound rate of 61% between 2014 and 2019. To cope with the data volume growth, a more dynamic and flexible network is needed. Caching has been deployed by both mobile network operators and content providers to reduce the load on centralized data centers and gateways. In addition, software-defined networking SDN is a prominent solution to more flexibly and efficiently utilize the available network resources, especially in the mobile backhaul. However, installation of cache servers into the network means additional capital expenditure CAPEX and their daily operations incur operational expenses OPEX. Thus, the change in cost of deploying and operating in-network caching compared with data center caching is modeled in this paper using a Finnish Long-Term Evolution reference network. In addition, this paper simulates both the SDN-optimized in-network caching system and data center caching, the results of which are utilized in the cost model. The simulation results show that, on average, in-network caching compared with caching only in data centers reduces traffic load by 45% in the network and 6% in the gateways. The cost modeling indicates that in-network caching reduces network-related CAPEX by 1.53% and OPEX by 0.49% compared with caching only in data centers. Copyright © 2015 John Wiley & Sons, Ltd.

Cost efficiency of mobile in-network caching

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