The objectives of this survey are to provide an in-depth coverage of a few selected research papers that have made significant contributions to the development of Network Function Virtualization (NFV), and to provide readers insights into the key advantages and disadvantages of NFV and Software Defined Networks (SDN) when compared to traditional networks. The research papers covered are classified into four categories: NFV Infrastructure (NFVI), Network Functions (NFs), Management And Network Orchestration (MANO), and service chaining. The NFVI papers describe “framework” software that implement common functions, such as dynamic scaling and load balancing, required by NF developers. Papers on NFs are classified as offering solutions for software switches or middleboxes. MANO papers covered in this survey are primarily on resource allocation (virtual network embedding), which is an orchestrator function. Finally, service chaining papers that offer examples and extensions are reviewed. Our conclusions are that with the current level of investment in NFV from cloud and Internet service providers, the promised cost savings are likely to be realized, though many challenges remain.

One of the key objectives of 5G is to evolve the current mobile network architecture from “one-fit-all” design model to a more customized and dynamically scaling one that enables the deployment of parallel systems, tailored to the service requirements on top of a shared infrastructure. Indeed, the envisioned 5G services may require different needs in terms of capacity, latency, bandwidth, reliability and security, which cannot be efficiently sustained by the same network infrastructure. Coming to address these customization challenges, network softwarization expressed through Software Defined Networking (SDN) programmable network infrastructures, Network Function Virtualization (NFV) running network functions as software and cloud computing flexibility paradigms, is seen as a possible panacea to addressing the variations in the network requirements posed by the 5G use cases. This will enable network flexibility and programmability, allow the creation and lifecycle management of virtual network slices tailored to the needs of 5G verticals expressed in the form of Mobile Virtual Network Operators (MVNOs) for automotive, eHealth, massive IoT, massive multimedia broadband. In this vein, this paper introduces a potential 5G architecture that enables the orchestration, instantiation and management of end-to-end network slices over multiple administrative and technological domains. The architecture is described from both the management and the service perspective, underlining the common functionality as well as how the response to the diversified service requirements can be achieved through proper software network components development.

Cloud bursting temporarily expands the capacity of a cloud-based service hosted in a private data center by renting public data center capacity when the demand for capacity spikes. To determine the optimal resources of a business-critical web system deployed over private and public data centers, this paper presents a cloud bursting approach based on long- and short-term predictions of requests to the system. In a private data center, a dedicated pool of virtual machines (VMs) is assigned to the web system on the basis of one-week predictions. Moreover, in both private and public data centers, VMs are activated on the basis of one-hour predictions. We formulate a problem that includes the total cost and response time constraints and conduct numerical simulations. The results indicate that our approach is tolerant of prediction errors and only slightly dependent on the processing power of a single VM. Even if the website receives bursty requests and one-hour predictions include a mean absolute percentage error (MAPE) of 0.2, the total cost decreases to half the existing cost of provisioning in the private date center alone. At the same time, 95% of response time is kept below 0.15s.

The heart of Network Functions Virtualization (NFV) is both the softwarization of existing network middleboxes as Virtual Network Functions (VNFs) and the Service Function Chaining (SFC), also known as Service Chaining of them. Most existing VNFs are realized as VM-based general purpose appliances and shared by multiple user VMs. However, the cover range of VNF can be extended to directly reinforce network functionality of user VMs by introducing VM-specific VNFs. In this study, we propose micro-VNFs (µVNFs) and a VM-specific service chaining framework (vNFChain). Micro-VNFs are VM-specific lightweight VNFs that directly attach to a user VM, and can support not only traditional L2-L4 protocols but also stateful custom L7 protocols. The vNFChain framework constructs local service chains of µVNFs and transparently attaches the chain to the VM. Importantly, our framework achieves zero touch configuration for user VMs as well as no modification for existing system environments, such as virtual switch, hypervisor, and OS. In this paper, we describe architectural design and implementation of the framework. In addition, we evaluate the proposed approach in terms of throughput and CPU usage by comparing it with a DPDK-enabled VM-based µVNF model.

Wireless technologies that offer high data rate are generally energy-consuming ones while low-energy technologies commonly provide low data rate. Both kinds of technologies have been integrated in a single mobile device for different services. Therefore, if the service does not always require high data rate, the low energy technology, i.e., Bluetooth, can be used instead of the energy-consuming one, i.e., Wi-Fi, for saving energy. It is obvious that energy savings are maximized by turning the unused technology off. However, when active sessions of ongoing services migrate between different technologies, the network-layer connectivity must be maintained, or a vertical handover (VHO) between different networks is required. Moreover, when the networks are not interconnected, the VHO must be fully controlled by the device itself. The device typically navigates traffic through the firmware of the wireless network interface cards (WNIC) using their drivers, which are dependent on the vendors. To control the traffic navigation between WNICs without any modification of the WNICs' drivers, Software-Defined Networking (SDN) can be applied locally on the mobile device, the so called local SDN. In the local SDN architecture, a local SDN controller (SDNC) is used to control a virtual OpenFlow switch, which turns WNICs into its switch ports. Although the SDNC can navigate the traffic, it lacks the global view of the network topology. Hence, to correctly navigate traffic in a VHO process, an extended SDN controller (extSDNC) was proposed in a previous work. With the extSDNC, the SDNC can perform VHO based on a link layer trigger but with a significant packet loss rate. Therefore, in this paper, a framework named esVHO is proposed that executes VHO at the network layer to reduce the packet loss rate and reduce energy consumption. Experiments on VHO performance prove that esVHO can reduce the packet loss rate considerably. Moreover, the results of an energy saving experiment show that esVHO performs high energy saving up to 4.89 times compared to the others.

Internet of Things (IoT) devices deployed in urban areas are seen as data sources for urban sensing IoT applications. Since installing cellular interfaces on a huge number of IoT devices is expensive, we propose to use a user equipment (UE) device with a local wireless interface as a mobile IoT gateway for fixed IoT devices. In this paper, we design a new mobile architecture based on cellular networks to accommodate non-cellular fixed IoT devices by UE devices working as IoT gateways. One key feature is that our architecture leverages proximity services (ProSe) to discover relay UE devices with low overhead in terms of discovery messages. Through simulation studies, we clarify the feasibility of our architecture including the relay UE discovery mechanism in urban areas.

Network traffic forecasts, as it is well known, can be useful for network resource optimization. In order to minimize the forecast error by maximizing information utilization with low complexity, this paper concerns the difference of traffic trends at large time scales and fits a dual-related model to predict it. First, by analyzing traffic trends based on user behavior, we find both hour-to-hour and day-to-day patterns, which means that models based on either of the single trends are unable to offer precise predictions. Then, a prediction method with the consideration of both daily and hourly traffic patterns, called the dual-related forecasting method, is proposed. Finally, the correlation for traffic data is analyzed based on model parameters. Simulation results demonstrate the proposed model is more effective in reducing forecasting error than other models.

This paper proposes an iterative cancellation technique for adjacent channel interference (ACI), induced by amplifier nonlinearity in millimeter wave (mmW) communication systems. In mmW communications, a large spectrum leak is expected because of the amplifier nonlinearity, and such a spectrum leak disturbs multichannel utilization. In order to mitigate the ACI, iterative interference cancellation in the receiver side is designed in this paper. Typically, iterative interference cancellation is conducted by generating a soft replica of interference from the feedback of the decoder, and subtracting the replica from the received signals. In this case, the canceller must know the amplifier nonlinearity in order to regenerate a soft replica of ACI. In this paper, amplifier nonlinearity is estimated by subjecting the received pilot signals to polynomial regression. We reveal that using only pilot signals in estimating amplifier nonlinearity is insufficient for guaranteeing replica accuracy. To address this issue, the proposed scheme exploits the detected data sequence in the regression analysis. We demonstrate that the proposed ACI cancellation technique can effectively mitigate ACI in multichannel utilization.

Mobility management is very important in mobile cellular networks, since to connect incoming calls, the network must maintain the locations of the mobiles. This study considers the zone-based registration methods that most mobile cellular networks have adopted. We focus on two special zone-based registration methods, called two-zone registration (2Z), and two-zone registration with implicit registration by outgoing calls (2Zi). Although some mathematical models for their performances have been presented, they still cannot accurately estimate 2Zi performance. We provide a new and simple mathematical model based on Markov chain theory that can accurately analyze the performances of 2Z and 2Zi. We also explain the propositions underlying the explicit expressions adopted by our model. We finally present various numerical results, to compare the performance of 2Zi with those of 2Z and one-zone registration (1Z), and show that in every case, 2Zi is superior to 2Z, and in most practical cases, to 1Z.

In this paper, we propose a relaying strategy for single-carrier relay networks with frequency selective channels, where each relay node delays its received signal before amplify-and-forward processing it. We propose a computationally efficient delay design method which reduces the number of delay candidates. To further reduce computational complexity, we develop a simplified delay design method which reduces the number of weight computations. Also, we extend the design method to the case where only partial channel state information of relay-to-destination channels is available. Simulation results show that the proposed relaying strategy outperforms a conventional amplify-and-forward relaying strategy and achieves the performance close to that of a more complex filter-and-forward relaying strategy. It is also shown that the proposed delay design method achieves near-optimum performance.

Microwave imaging techniques, in particular, synthetic aperture radar (SAR), are promising tools for terrain surface measurement, irrespective of weather conditions. The coherent change detection (CCD) method is being widely applied to detect surface changes by comparing multiple complex SAR images captured from the same scanning orbit. However, in the case of a general damage assessment after a natural disaster such as an earthquake or mudslide, additional about surface change, such as surface height change, is strongly required. Given this background, the current study proposes a novel height change estimation method using a CCD model based on the Pauli decomposition of fully polarimetric SAR images. The notable feature of this method is that it can offer accurate height change beyond the assumed wavelength, by introducing the frequency band-divided approach, and so is significantly better than InSAR based approaches. Experiments in an anechoic chamber on a 1/100 scaled model of the X-band SAR system, show that our proposed method outputs more accurate height change estimates than a similar method that uses single polarimetric data, even if the height change amount is over the assumed wavelength.