A Survey on Mobility-Induced Service Migration in the Fog, Edge, and Related Computing Paradigms <s> Predictions and Monitoring. <s> As the density of wireless networks continues to grow with more clients, more base stations, and more traffic, designing cost-effective wireless solutions with efficient resource usage and ease to manage is an increasing challenging task due to the overall system complexity. A number of vendors offer scalable and high-performance wireless networks but at a high cost and commonly as a single-vendor solution, limiting the ability to innovate after roll-out. Recent Software-Defined Networking (SDN) approaches propose new means for network virtualization and programmability advancing the way networks can be designed and operated, including user-defined features and customized behaviour even at run-time. However, means for rapid prototyping and experimental evaluation of SDN for wireless environments are not yet available. This paper introduces Mininet-WiFi as a tool to emulate wireless OpenFlow/SDN scenarios allowing high-fidelity experiments that replicate real networking environments. Mininet-WiFi augments the well-known Mininet emulator with virtual wireless stations and access points while keeping the original SDN capabilities and the lightweight virtualization software architecture. We elaborate on the potential applications of Mininet-Wifi and discuss the benefits and current limitations. Two use cases based on IEEE 802.11 demonstrate available functionality in our open source developments. <s> BIB001 </s> A Survey on Mobility-Induced Service Migration in the Fog, Edge, and Related Computing Paradigms <s> Predictions and Monitoring. <s> In order to overcome the scalability problem of the traditional Internet of Things architecture (i.e., data streams generated from distributed IoT devices are transmitted to the remote cloud via the Internet for further analysis), this article proposes a novel approach to mobile edge computing for the IoT architecture, edgeIoT, to handle the data streams at the mobile edge. Specifically, each BS is connected to a fog node, which provides computing resources locally. On the top of the fog nodes, the SDN-based cellular core is designed to facilitate packet forwarding among fog nodes. Meanwhile, we propose a hierarchical fog computing architecture in each fog node to provide flexible IoT services while maintaining user privacy: each user's IoT devices are associated with a proxy VM (located in a fog node), which collects, classifies, and analyzes the devices' raw data streams, converts them into metadata, and transmits the metadata to the corresponding application VMs (which are owned by IoT service providers). Each application VM receives the corresponding metadata from different proxy VMs and provides its service to users. In addition, a novel proxy VM migration scheme is proposed to minimize the traffic in the SDNbased core. <s> BIB002 </s> A Survey on Mobility-Induced Service Migration in the Fog, Edge, and Related Computing Paradigms <s> Predictions and Monitoring. <s> Mobile Cloud Computing enables resource limited mobile devices to support rich application services. Among three types of cloud services, Infrastructure-as-a-Service (IaaS) clouds provides compute infrastructure for mobile applications on demand. In IaaS-based mobile clouds, latency and bandwidth requirements can considered as critical factors impacting Quality of Service (QoS). Opposed to centralized clouds, geographically distributed clouds realize higher QoS benefiting the proximity to the end user. In this paper, we propose an IaaS framework with regional datacenters for mobile clouds. With the benefits of software-defined networking (SDN), we address impacts on QoS during mobility by serving mobile user via the optimum datacenter. A test-bed was developed to measure the performance of service allocation and relocation in proposed framework. <s> BIB003 </s> A Survey on Mobility-Induced Service Migration in the Fog, Edge, and Related Computing Paradigms <s> Predictions and Monitoring. <s> The emerging real-time and computation-intensive services driven by the Internet of Things, augmented reality, automatic driving, and so on, have tight quality of service and quality of experience requirements, which can hardly be supported by conventional cloud computing. Fog computing, which migrates the features of cloud computing to the network edge, guarantees low latency for location-aware services. However, due to the locality feature of fog computing, maintaining service continuity when mobile users travel across different access networks has become a challenging issue. In this article, we propose a novel software-defined-networking-based fog computing architecture by decoupling mobility control and data forwarding. Under the proposed architecture, we design efficient signaling operations to provide seamless and transparent mobility support to mobile users, and present an efficient route optimization algorithm by considering the performance gain in data communications and system overhead in mobile fog computing. Numerical results from extensive simulations have demonstrated that the proposed scheme can not only guarantee service continuity, but also greatly improve handover performance and achieve high data communication efficiency in mobile fog computing. <s> BIB004
A different approach for evaluating the tradeoff can be found in some contributions where the benefit-cost information is derived from predictions, generally based on historical data or retrieved from a monitoring module that is constantly updating the relevant state information. This can be seen in BIB004 , where the authors propose to leverage SDN principles to decouple mobility control and data forwarding to achieve service continuity for fog computing users. In fact, the SDN controller installs the new mobility logic either proactively or reactively on the SDNenabled fog servers. The optimal path to the new fog server is calculated based on the performance gain and system cost, taking into account the predicted user's residence time within the FS's area. Simulations performed using Mininet-Wi-Fi BIB001 demonstrate the ability of the proposed scheme to improve the handover performance and the data communication efficiency. Also leveraging the SDN paradigm, the authors in BIB002 propose a VM migration scheme, which compares the estimated profit resulting from migrating/not migrating the VM in terms of the amount of traffic reduction in the network core. In fact, the traffic caused by the migration can be predicted based on the average bandwidth available for migration, the average data rate between the user and its VM (both to be obtained from historical traces), the generation rate of dirty memory pages, the VM memory size, and the threshold for stopping the iterative copying. On the other hand, the traffic generated from keeping the VM in its originally serving node depends on the average data rate between the user and its VM and the BS retention time, which is also predictable. Trace-based emulation shows that the proposed dynamic migration reduces the network traffic compared to the static VM deployment. A different approach is provided in BIB003 , where the impact of mobility on QoS in a distributed Regional Data Center (RDC) context is addressed. More specifically, the authors propose an algorithm that evaluates the costs for migrating/not migrating the VM based on information collected from a monitoring module, so that the costs are minimized and the QoS is maintained. Simulations conducted using Mininet show that migrations are not performed by the proposed algorithm when the QoS is met. Table 5 summarizes the contributions presented in this section, highlighting their main objectives, the approach used to find the optimal solution, the evaluation type, and, in the simulation case, whether mobility was based on real-world (RW) mobility traces or synthetic (S) ones, and finally the different factors considered in the migration process.