The Internet has led to the creation of a digital society, where (almost) everything is connected and is accessible from anywhere. However, despite their widespread adoption, traditional IP networks are complex and very hard to manage. It is both difficult to configure the network according to predefined policies, and to reconfigure it to respond to faults, load, and changes. To make matters even more difficult, current networks are also vertically integrated: the control and data planes are bundled together. Software-defined networking (SDN) is an emerging paradigm that promises to change this state of affairs, by breaking vertical integration, separating the network's control logic from the underlying routers and switches, promoting (logical) centralization of network control, and introducing the ability to program the network. The separation of concerns, introduced between the definition of network policies, their implementation in switching hardware, and the forwarding of traffic, is key to the desired flexibility: by breaking the network control problem into tractable pieces, SDN makes it easier to create and introduce new abstractions in networking, simplifying network management and facilitating network evolution. In this paper, we present a comprehensive survey on SDN. We start by introducing the motivation for SDN, explain its main concepts and how it differs from traditional networking, its roots, and the standardization activities regarding this novel paradigm. Next, we present the key building blocks of an SDN infrastructure using a bottom-up, layered approach. We provide an in-depth analysis of the hardware infrastructure, southbound and northbound application programming interfaces (APIs), network virtualization layers, network operating systems (SDN controllers), network programming languages, and network applications. We also look at cross-layer problems such as debugging and troubleshooting. In an effort to anticipate the future evolution of this new paradigm, we discuss the main ongoing research efforts and challenges of SDN. In particular, we address the design of switches and control platforms—with a focus on aspects such as resiliency, scalability, performance, security, and dependability—as well as new opportunities for carrier transport networks and cloud providers. Last but not least, we analyze the position of SDN as a key enabler of a software-defined environment.

https://publications.uni.lu/bitstream/10993/20596/1/survey_on_SDN.pdf

Software-Defined Networking: A Comprehensive Survey

Driven by the visions of Internet of Things and 5G communications, recent years have seen a paradigm shift in mobile computing, from the centralized mobile cloud computing toward mobile edge computing (MEC). The main feature of MEC is to push mobile computing, network control and storage to the network edges (e.g., base stations and access points) so as to enable computation-intensive and latency-critical applications at the resource-limited mobile devices. MEC promises dramatic reduction in latency and mobile energy consumption, tackling the key challenges for materializing 5G vision. The promised gains of MEC have motivated extensive efforts in both academia and industry on developing the technology. A main thrust of MEC research is to seamlessly merge the two disciplines of wireless communications and mobile computing, resulting in a wide-range of new designs ranging from techniques for computation offloading to network architectures. This paper provides a comprehensive survey of the state-of-the-art MEC research with a focus on joint radio-and-computational resource management. We also discuss a set of issues, challenges, and future research directions for MEC research, including MEC system deployment, cache-enabled MEC, mobility management for MEC, green MEC, as well as privacy-aware MEC. Advancements in these directions will facilitate the transformation of MEC from theory to practice. Finally, we introduce recent standardization efforts on MEC as well as some typical MEC application scenarios.

A Survey on Mobile Edge Computing: The Communication Perspective

Driven by the visions of Internet of Things and 5G communications, recent years have seen a paradigm shift in mobile computing, from the centralized Mobile Cloud Computing towards Mobile Edge Computing (MEC). The main feature of MEC is to push mobile computing, network control and storage to the network edges (e.g., base stations and access points) so as to enable computation-intensive and latency-critical applications at the resource-limited mobile devices. MEC promises dramatic reduction in latency and mobile energy consumption, tackling the key challenges for materializing 5G vision. The promised gains of MEC have motivated extensive efforts in both academia and industry on developing the technology. A main thrust of MEC research is to seamlessly merge the two disciplines of wireless communications and mobile computing, resulting in a wide-range of new designs ranging from techniques for computation offloading to network architectures. This paper provides a comprehensive survey of the state-of-the-art MEC research with a focus on joint radio-and-computational resource management. We also present a research outlook consisting of a set of promising directions for MEC research, including MEC system deployment, cache-enabled MEC, mobility management for MEC, green MEC, as well as privacy-aware MEC. Advancements in these directions will facilitate the transformation of MEC from theory to practice. Finally, we introduce recent standardization efforts on MEC as well as some typical MEC application scenarios.

Software-Defined Networking (SDN) is an emerging paradigm that promises to change this state of affairs, by breaking vertical integration, separating the network's control logic from the underlying routers and switches, promoting (logical) centralization of network control, and introducing the ability to program the network. The separation of concerns introduced between the definition of network policies, their implementation in switching hardware, and the forwarding of traffic, is key to the desired flexibility: by breaking the network control problem into tractable pieces, SDN makes it easier to create and introduce new abstractions in networking, simplifying network management and facilitating network evolution. In this paper we present a comprehensive survey on SDN. We start by introducing the motivation for SDN, explain its main concepts and how it differs from traditional networking, its roots, and the standardization activities regarding this novel paradigm. Next, we present the key building blocks of an SDN infrastructure using a bottom-up, layered approach. We provide an in-depth analysis of the hardware infrastructure, southbound and northbound APIs, network virtualization layers, network operating systems (SDN controllers), network programming languages, and network applications. We also look at cross-layer problems such as debugging and troubleshooting. In an effort to anticipate the future evolution of this new paradigm, we discuss the main ongoing research efforts and challenges of SDN. In particular, we address the design of switches and control platforms -- with a focus on aspects such as resiliency, scalability, performance, security and dependability -- as well as new opportunities for carrier transport networks and cloud providers. Last but not least, we analyze the position of SDN as a key enabler of a software-defined environment.

Network function virtualization (NFV) has drawn significant attention from both industry and academia as an important shift in telecommunication service provisioning. By decoupling network functions (NFs) from the physical devices on which they run, NFV has the potential to lead to significant reductions in operating expenses (OPEX) and capital expenses (CAPEX) and facilitate the deployment of new services with increased agility and faster time-to-value. The NFV paradigm is still in its infancy and there is a large spectrum of opportunities for the research community to develop new architectures, systems and applications, and to evaluate alternatives and trade-offs in developing technologies for its successful deployment. In this paper, after discussing NFV and its relationship with complementary fields of software defined networking (SDN) and cloud computing, we survey the state-of-the-art in NFV, and identify promising research directions in this area. We also overview key NFV projects, standardization efforts, early implementations, use cases, and commercial products.

/pdf/network-function-virtualization-state-of-the-art-and-29gg3feprt.pdf

Network Function Virtualization: State-of-the-Art and Research Challenges

With the growth of data volumes and variety of Internet applications, data centers (DCs) have become an efficient and promising infrastructure for supporting data storage, and providing the platform for the deployment of diversified network services and applications (e.g., video streaming, cloud computing). These applications and services often impose multifarious resource demands (storage, compute power, bandwidth, latency) on the underlying infrastructure. Existing data center architectures lack the flexibility to effectively support these applications, which results in poor support of QoS, deployability, manageability, and defence against security attacks. Data center network virtualization is a promising solution to address these problems. Virtualized data centers are envisioned to provide better management flexibility, lower cost, scalability, better resources utilization, and energy efficiency. In this paper, we present a survey of the current state-of-the-art in data center networks virtualization, and provide a detailed comparison of the surveyed proposals. We discuss the key research challenges for future research and point out some potential directions for tackling the problems related to data center design.

Data Center Network Virtualization: A Survey

Virtualizing data center networks has been considered a feasible alternative to satisfy the requirements of advanced cloud services. Proper mapping of virtual data center (VDC) resources to their physical counterparts, also known as virtual data center embedding, can impact the revenue of cloud providers. Similar to virtual networks, the problem of mapping virtual requests to physical infrastructures is known to be NPhard. Although some proposals have come up with heuristics to cope with the complexity of the embedding process focusing on virtual machine placement, these solutions ignore the correlation among other data resources, such as switches and storage. In this paper, we propose a new embedding solution for data centers that, in addition to virtual machine placement, explicitly considers the relation between switches and links, allows multiple resources of the same request to be mapped to a single physical resource, and reduces resource fragmentation in terms of CPU. Simulations show that our solution results in high acceptance ratio of VDC requests, improves utilization of the physical substrate, and generates increased revenue for infrastructure providers.

/pdf/on-tackling-virtual-data-center-embedding-problem-khbiufk5lc.pdf

On tackling virtual data center embedding problem

Data center networks are characterized by high link speeds, low propagation delays, small switch buffers, and temporally clustered arrivals of many concurrent TCP flows fulfilling data transfer requests. However, the combination of these features can lead to transient buffer overflow and bursty packet losses, which in turn lead to TCP retransmission timeouts that degrade the performance of short-lived flows. This so-called TCP-incast problem can cause TCP throughput collapse. In this paper, we explore an application-level approach for solving this problem. The key idea of our solution is to coordinate the scheduling of short-lived TCP flows so that no data loss happens. We develop a mathematical model of lossless data transmission, and estimate the maximum good put achievable in data center networks. The results indicate non-monotonic good put that is highly sensitive to specific parameter configurations in the data center network. We validate our model using ns-2 network simulations, which show good correspondence with the theoretical results.

/pdf/solving-the-tcp-incast-problem-with-application-level-1jyruczq9j.pdf

Solving the TCP-Incast Problem with Application-Level Scheduling

While Transmission Control Protocol (TCP) variants with delay-based congestion control (e.g., TCP Vegas) provide low queueing delay and low packet loss, the key problem with their deployment on the Internet is their relative performance when competing with traditional TCP variants with loss-based congestion control (e.g., TCP NewReno). In particular, the more aggressive loss-based flows tend to dominate link buffer usage and degrade the throughput of delay-based flows. In this paper, we study a novel approach for achieving fair sharing of the network resources among TCP variants, using Rate-Delay (RD) Network Services. In particular, loss-based and delay-based flows are isolated from each other and served via different queues. Using extensive ns-2 network simulation experiments, we show that our approach is effective in providing fairness between loss-based NewReno and delay-based Vegas flows.

http://elisa.cpsc.ucalgary.ca/pubs/2010/Podlesny_IWQoS_2010.pdf

Providing fairness between TCP NewReno and TCP Vegas with RD network services

Data centers have become very popular for storing large volumes of data. In particular, companies like Amazon, Google, and Yahoo! routinely use data centers for storage, Web search, and large-scale computations. The main characteristics of a data center network are high-speed links, low propagation delays, and limited-size switch buffers. In addition, the data for a given client application are usually striped (spread) over many servers, for increased reliability and performance (i.e., parallelism). Recent research efforts have resulted in several architectures of data centers [1].

Maxim Podlesny

Papers

Data Center Network Virtualization: A Survey

On tackling virtual data center embedding problem

Solving the TCP-Incast Problem with Application-Level Scheduling

Providing fairness between TCP NewReno and TCP Vegas with RD network services

An application-level solution for the TCP-incast problem in data center networks