Softwarization of Mobile Network Functions towards Agile and Energy Efficient 5G Architectures: A Survey <s> Introduction <s> This whitepaper proposes OpenFlow: a way for researchers to run experimental protocols in the networks they use every day. OpenFlow is based on an Ethernet switch, with an internal flow-table, and a standardized interface to add and remove flow entries. Our goal is to encourage networking vendors to add OpenFlow to their switch products for deployment in college campus backbones and wiring closets. We believe that OpenFlow is a pragmatic compromise: on one hand, it allows researchers to run experiments on heterogeneous switches in a uniform way at line-rate and with high port-density; while on the other hand, vendors do not need to expose the internal workings of their switches. In addition to allowing researchers to evaluate their ideas in real-world traffic settings, OpenFlow could serve as a useful campus component in proposed large-scale testbeds like GENI. Two buildings at Stanford University will soon run OpenFlow networks, using commercial Ethernet switches and routers. We will work to encourage deployment at other schools; and We encourage you to consider deploying OpenFlow in your university network too <s> BIB001 </s> Softwarization of Mobile Network Functions towards Agile and Energy Efficient 5G Architectures: A Survey <s> Introduction <s> As one of the fundamental infrastructures for cloud computing, data center networks (DCN) have recently been studied extensively. We currently use pure software-based systems, FPGA based platforms, e.g., NetFPGA, or OpenFlow switches, to implement and evaluate various DCN designs including topology design, control plane and routing, and congestion control. However, software-based approaches suffer from high CPU overhead and processing latency; FPGA based platforms are difficult to program and incur high cost; and OpenFlow focuses on control plane functions at present. ::: ::: In this paper, we design a ServerSwitch to address the above problems. ServerSwitch is motivated by the observation that commodity Ethernet switching chips are becoming programmable and that the PCI-E interface provides high throughput and low latency between the server CPU and I/O subsystem. ServerSwitch uses a commodity switching chip for various customized packet forwarding, and leverages the server CPU for control and data plane packet processing, due to the low latency and high throughput between the switching chip and server CPU. ::: ::: We have built our ServerSwitch at low cost. Our experiments demonstrate that ServerSwitch is fully programmable and achieves high performance. Specifically, we have implemented various forwarding schemes including source routing in hardware. Our in-network caching experiment showed high throughput and flexible data processing. Our QCN (Quantized Congestion Notification) implementation further demonstrated that ServerSwitch can react to network congestions in 23us. <s> BIB002 </s> Softwarization of Mobile Network Functions towards Agile and Energy Efficient 5G Architectures: A Survey <s> Introduction <s> MPLS was an attempt to simplify network hardware while improving the flexibility of network control. Software-Defined Networking (SDN) was designed to make further progress along both of these dimensions. While a significant step forward in some respects, it was a step backwards in others. In this paper we discuss SDN's shortcomings and propose how they can be overcome by adopting the insight underlying MPLS. We believe this hybrid approach will enable an era of simple hardware and flexible control. <s> BIB003 </s> Softwarization of Mobile Network Functions towards Agile and Energy Efficient 5G Architectures: A Survey <s> Introduction <s> The idea of programmable networks has recently re-gained considerable momentum due to the emergence of the Software-Defined Networking (SDN) paradigm. SDN, often referred to as a "radical new idea in networking", promises to dramatically simplify network management and enable innovation through network programmability. This paper surveys the state-of-the-art in programmable networks with an emphasis on SDN. We provide a historic perspective of programmable networks from early ideas to recent developments. Then we present the SDN architecture and the OpenFlow standard in particular, discuss current alternatives for implementation and testing of SDN-based protocols and services, examine current and future SDN applications, and explore promising research directions based on the SDN paradigm. <s> BIB004 </s> Softwarization of Mobile Network Functions towards Agile and Energy Efficient 5G Architectures: A Survey <s> Introduction <s> As 4G wireless networks are vastly and rapidly deployed worldwide, 5G with its advanced vision of all connected world and zero distance communications is already at the corner. Along with the super quality of user experience brought by these new networks, the shockingly increasing energy consumption of wireless networks has become a worrying economic issue for operators and a big challenge for sustainable development. Green Transmission Technologies (GTT) is a project focusing on the energy-efficient design of physical-layer transmission technologies and MAC-layer radio resource management in wireless networks. In particular, fundamental tradeoffs between spectrum efficiency and energy efficiency have been identified and explored for energy-efficiency-oriented design and optimization. In this article, four selected GTT solutions are introduced, focusing on how they utilize the degrees of freedom in different resource domains, as well as how they balance the tradeoff between energy and spectrum efficiency. On top of the elaboration of separated solutions, the GTT toolbox is introduced as a systematic tool and unified simulation platform to integrate the proposed GTT solutions together. <s> BIB005 </s> Softwarization of Mobile Network Functions towards Agile and Energy Efficient 5G Architectures: A Survey <s> Introduction <s> This article explores network densification as the key mechanism for wireless evolution over the next decade. Network densification includes densification over space (e.g, dense deployment of small cells) and frequency (utilizing larger portions of radio spectrum in diverse bands). Large-scale cost-effective spatial densification is facilitated by self-organizing networks and intercell interference management. Full benefits of network densification can be realized only if it is complemented by backhaul densification, and advanced receivers capable of interference cancellation. <s> BIB006 </s> Softwarization of Mobile Network Functions towards Agile and Energy Efficient 5G Architectures: A Survey <s> Introduction <s> In this article, we cover eco-friendly cellular networks, discussing the benefits that ambient energy harvesting offers in terms of energy consumption and profit. We advocate for future networks where energy harvesting will be massively employed to power network elements; even further, communication networks will seamlessly blend with future power grids. This vision entails the fact that future base stations may trade some of the excess energy they harvest so as to make a profit and provide ancillary services to the electricity grid. We start by discussing recent developments in the energy harvesting field, and then deliberate on the way future energy markets are expected to evolve and the new fundamental trade-offs that arise when energy can be traded. Performance estimates are given throughout to support our arguments, and open research issues in this emerging field are discussed. <s> BIB007
The evolution towards a softwarized evolved packet core (EPC) is expected to solve current mobile networks (MNs) challenges and set the way for high data rate and low latency 5G networks. Such changes should make it possible to effectively cope with the anticipated mobile data traffic explosion that will be mostly generated by smartphones, portable devices, and new traffic types, such as machine-tomachine (M2M) applications. Traditionally, as new services are introduced into the mobile space, operators upgrade the network infrastructure for a better management, while at the same time still guaranteeing a target quality of service (QoS) to their users. This introduces network complexity, as new specific hardware is usually deployed into the network for these purposes. The possibility of running network functions (NFs) in software, instead of hardware devices, is seen as a promising solution towards network complexity reduction. This technique will permit dynamically scaling the network resources for a more efficient network management. Current research focusing on virtualizing the EPC functions is surveyed in this article. Here, we review existing EPC architectural proposals, paying attention to the different strategies involved in virtualizing the EPC functions, the adopted virtualization technology, open issues, and related challenges. Also, we discuss the current technological trends, their advantages, and drawbacks and, when possible, analyze their differences. Softwarization and virtualization of resources and services are undoubtedly among the main drivers of 5G and beyond 5G networks, as they will provide flexibility and adaptability and will facilitate network maintenance and the update of all network functions. However, to reap the full benefits of a virtualized architecture, this technology must be combined with intelligent mechanisms for handling network resources. For this reason, in this paper we also address several optimization means, including machine learning and data mining tools, and discuss how these can be employed within a virtualized mobile network. Vendors and researchers are targeting different approaches to use virtualization within EPC architectures, such 2 Wireless Communications and Mobile Computing as grouping the NFs, running the virtualized functions on clouds, partitioning the NFs into slices, and redesigning the network to only use network function virtualization (NFV) technology. All these techniques are here discussed, emphasizing the offered advantages, the existing similarities among them, and the road ahead. In addition, we elaborate on using energy harvesting (EH) hardware to make future 5G networks as much as possible energy neutral and discuss how EH technology can be integrated into future softwarized mobile systems. Software defined networking (SDN) is an emerging virtualization technology, which supports programmable interfaces to provide flexibility and agility on the network control management BIB003 BIB004 BIB002 . It basically consists of a number of network nodes such as switches, virtual switches, routers, and firewalls, which are automated, controlled, and reprogrammed through software commands. Open source software such as Open Flow BIB001 can be used to dynamically reconfigure network elements, through an SDN controller which can handle multiple network switches at a time. An SDN-based architecture allows dynamic and flexible network operations by decoupling the network control plane from the data plane, leveraging standard protocols which enable remote management and operation. The SDN controller can run on a commodity hardware and gives logically centralized control towards multiple switches. This enables accurate monitoring and control of traffic load within the network and is also expected to minimize operational cost, while improving load balancing and data traffic handling at the edge, through the use of generic hardware  . Another virtualization technology is NFV, which has recently emerged to virtualize the EPC network functions and move them from proprietary to commodity hardware platforms, as the use of specialized hardware devices has been one of the limiting factors towards mobile evolution and the fast deployment of new services within the mobile space  . Network functions may be firewalls, domain name servers (DNS), network address translation (NAT) services, intrusion detection systems, caching services, and so forth. These functions, which are of prime importance for the accurate operation of any network, are migrated into software and ran on top of general purpose servers. NFV is complementary to SDN but the two technologies can coexist within the same network: SDN tries to achieve a centralized control approach on switching and routing elements, thus allowing programmability of the network, while NFV moves NFs out of dedicated hardware into software that is imported into general purpose hardware. While these technologies do not possess any intrinsic cognition, they will give rise to more flexible networks, where resources could be controlled and combined in a flexible manner. This is expected to facilitate network management and to make it more efficient, moving the intelligence that is required to manage network resources, such as load balancing, intrusion detection algorithms, and firewalls into NFs. Since SDN and NFV are drivers for 5G networks, it is crucial to look at their applications within these systems. As dictated by mobile edge computing (MEC), an emerging architectural paradigm for the design and implementation of communication networks through NFV, the virtualized network functions (VNFs) can then be deployed at the BS, that is, at a MEC platform colocated with the BS, or at an aggregation point (a central point that manages a set of BSs located close to each other). MEC effectively moves the network intelligence towards the network edge: the VNFs are instantiated and executed over a hosting environment, and the combination of NFV and MEC can help achieve dynamic resource/service management and configuration. These new network technologies, SDN, NFV, and MEC, are expected to improve the quality of experience (QoE) of users, while at the same time making legacy and current MNs more flexible, quickly reprogrammable, and energy efficient BIB005 . As a last consideration, 5G technology is currently adopting a so-called network densification approach, which involves the deployment of a large number of base stations (BSs), to increase the network coverage and provide higher throughput to the users. This however results in higher energy consumption, which is expected to considerably contribute to carbon emissions into the atmosphere BIB006  . In order to minimize the carbon footprint of 5G MNs, we advocate for the integration of energy harvesting (EH) into future base stations (especially small cells). This brings the notion of energy harvesting BS (EHBS) and energy harvesting-powered MEC (EH-MEC) systems to reduce the dependence of MNs on the electricity grid. Besides helping to minimize the operational expenses (OPEX), in terms of annual electricity bills, the use of renewable energy will help extend network coverage to areas where there is insufficient electricity, or to assist during the case of a natural disaster scenario, where the conventional electricity grid may become unavailable. At the same time, the deployment of EH technology (batteries, solar cells, etc.) entails a certain capital expenditure (CAPEX) and whether or not this is convenient depends on the return of investment time. Nevertheless, current trends in battery and solar module costs are promising and suggest that in the future this equipment will be cheap enough. Further discussion and results on these aspects can be found in BIB007 . We stress that energy efficiency is a key consideration in future networks and can be addressed as follows. First, the network procedures have to be streamlined and carefully orchestrated, and here is where virtualization technology (also entailing new architectural designs) will play a crucial role. This will allow for a more energy efficient network operation. Second, a modern and flexible management can be combined with EH technology to reduce the carbon footprint of communication networks. In this paper, current softwarization technologies, architectures, and trends are reviewed with a special focus on energy efficiency. The rest of the paper is structured as follows. In Section 2 we discuss the existing EPC architectural proposals, analyzing the following virtualization techniques: (A) grouping EPC functional entities (Section 2.1), (B) NFV-enabled network clouds (Section 2.2), (C) network slicing (Section 2.3), and (D) mobile edge computing (Section 2.4). In Section 3, we discuss the use of machine learning, data mining, and context-awareness within softwarized 5G networks. In Section 4, we outline some challenges and open issues related to the EPC and MEC proposals in the state of the art and, lastly, in Section 5 we provide some final considerations.