A Survey on Mobility-Induced Service Migration in the Fog, Edge, and Related Computing Paradigms <s> A VIEW ON THE DIVERSITY IN THE MIGRATION SCENARIOS LANDSCAPE <s> Handoff mechanisms allow mobile users to move across multiple wireless access points while maintaining their voice and/or data sessions. A traditional handoff process is concerned with smoothly transferring a mobile device session from its current access point (or cell) to a target access point (or cell). These handoff characteristics are sufficient for voice calls and background data transfers, however nowadays many mobile applications are heavily based on data and processing capabilities from the cloud. Such applications, especially those that require greater interactivity, often demand not only a smooth session transfer, but also the maintenance of quality of service requirements that impact a user's experience. In this context, the Fog Computing paradigm arises to overcome delays encountered when applications need low latency to access data or offload processing to the cloud. Fog computing introduces a distributed cloud layer, composed of cloudlets (i.e., "small clouds" with lower computational capacity), between the user and the cloud. Cloudlets allow low latency access to data or processing capabilities, which can be accomplished by offering a VM to the user. An overview of Fog computing is first providing, relating it to general concepts in Cloud-based systems, followed by a general architecture to support virtual machine migration in this emerging paradigm -- discussing both the benefits and challenges associated with such migration. <s> BIB001 </s> A Survey on Mobility-Induced Service Migration in the Fog, Edge, and Related Computing Paradigms <s> A VIEW ON THE DIVERSITY IN THE MIGRATION SCENARIOS LANDSCAPE <s> In this paper, we propose virtualization based cyber-functions for mobile cyber-physical systems (CPSs). If a physical object of a CPS has a high level of mobility, and as the network path length from the cyber-function box gets larger, it becomes very difficult to satisfy the data exchange delay requirement. The proposed scheme can perform the migration of the cyber-functions to an appropriate location on the cyber-infrastructure using virtualization techniques. <s> BIB002 </s> A Survey on Mobility-Induced Service Migration in the Fog, Edge, and Related Computing Paradigms <s> A VIEW ON THE DIVERSITY IN THE MIGRATION SCENARIOS LANDSCAPE <s> First research activities are starting to recognize the suitability of edge computing approaches in several Internet-of-Things (IoT) and Cyber-Physical Systems (CPS) application domains, for instance, to better address scalability issues and to improve reactivity via local control decisions and actuation. The paper originally proposes the design and implementation of an extended edge computing platform, specifically designed for the support of mobile services when provisioned in so-called hostile environments. In particular, our original platform is capable of proactive migration of virtualized functions in response to provision-time device mobility. The paper provides a practical contribution in terms of design and implementation of proactive migration as an extension of the Elijah platform, available for the community of researchers/practitioners in the field. In addition, the paper contributes with lessons learnt from deployment and experimentation, including experimental results about the performance achievable when adopting simple but effective strategies for proactive migration. <s> BIB003 </s> A Survey on Mobility-Induced Service Migration in the Fog, Edge, and Related Computing Paradigms <s> A VIEW ON THE DIVERSITY IN THE MIGRATION SCENARIOS LANDSCAPE <s> The upcoming Cloud-Fog interplay is expected to grant service providers more degrees of freedom in the implementation and management of their service portfolios. However, recent advances in Mobile Internet have developed a growing need to support user mobility - as users move, the Fog counterparts of services that require close proximity may call for migration(s) to meet the desired quality of service (QoS). With the state-of-the-art virtualization technologies, next-generation Cloud/Fog services are being implemented in modular software (i.e., as a graph/chain of portable virtual objects (VOs)) that can be migrated around the Telco infrastructure, and yet scalability is still an open issue, especially with the inter-datacenter bulk live migration of VOs. In this perspective, a VO clustering and migration policy that jointly considers user proximity and inter-VO affinity is proposed to scalably support user mobility, while allowing service differentiation among users. Results confirm that introducing migrations improve the QoS to always meet or exceed the requirements, as compared to static service placement, and considering VO clusters as aggregate entities will initiate around 40% less migrations, on average - an improvement that increases with inter-VO affinity and could potentially simplify service management when supporting user mobility. <s> BIB004 </s> A Survey on Mobility-Induced Service Migration in the Fog, Edge, and Related Computing Paradigms <s> A VIEW ON THE DIVERSITY IN THE MIGRATION SCENARIOS LANDSCAPE <s> One of the key targets of the upcoming 5G system is to build a mobile network architecture that supports not only classical mobile broadband applications (i.e., Internet and IMS), but also vertical industry services, such as those of automotive systems, e-health, public safety, and smart grid. Vertical industry is known to have specific needs that cannot be sustained by the current cellular networks. More notably, automotive systems require strict quality of service in terms of ultrashort latency for vehicle-to-infrastructure/network (V2I/N) communications. In this paper, we introduce the Follow Me edge-Cloud (FMeC) concept, leveraging the mobile edge computing (MEC) architecture to sustain requirements of the 5G automotive systems. Assuming that automotive services are deployed on MEC entities, FMeC ensures low-latency access to these services by guaranteeing that vehicles (i.e., as well as user equipment on board vehicles) always connect to nearest automotive service. Besides the FMeC architecture, our contribution in this paper consists in presenting a projection of the FMeC solution on an automated driving use case that integrates automotive and Telco infrastructures, to realize the vision of future 5G automotive systems. We introduce the envisioned software defined networking/OpenFlow-based architecture and our mobility-aware framework based on a set of building blocks that permit achieving the automated driving requirements within 5G network. The evaluation results, obtained conjointly through theoretical analysis and computer simulation, show that our proposed solution outperforms baseline approaches in meeting the automated driving latency requirement and minimizing the incurred global cost. <s> BIB005
In this section, a high-level classification showing the general characteristics of the migration contexts is presented with the aim of calling attention to the contexts that have been explored the least in the literature. A different classification of the proposed migration approaches focusing on their main objectives will be provided in Section 5. The first characteristic that we examine is the migration element-that is, "what is to be migrated?". Different migration elements have been considered in the literature, each having a different granularity level. More specifically, a service, 2 which is the most commonly used term in the literature, has the highest granularity in most of the cases, whereas more fine-grained migration elements such as operators, application components, or virtual objects can be combined to create more complex services. In the latter case, they might need to be jointly migrated to meet their dependency requirements. Table 2 captures the different terms used in the literature to refer to the migration element, their definitions, and their corresponding examples. The migration of the generic elements shown in Table 2 is often interchangeably used to refer to the migration of the virtual environment in which they run, such as VMs or containers. On the other hand, some works, listed in Table 3 , primarily focus on the migration of the virtual environment itself. As can be seen, VM migration has been extensively studied in the literature; however, increasing interest is being shown to more lightweight alternatives such as containers or processes in more recent works. A Survey on Mobility-Induced Service Migration 90:7 Apart from the diversity affecting the migration elements, a variety of considerations have been taken regarding the migration scenarios, which may in some cases be due to the characteristics of the corresponding research area. We particularly identify the five following considerations: • (C1) Mobility: As mobility may affect both end-users (U) and fog nodes (FN) (e.g., bus-based, vehicle-based, robot-based), we classify works according to whether they consider users' mobility only, fog node mobility only, or both at the same time. • (C2) FN-Radio Access mapping (applicable in the case of user mobility): -(1-1): One FN within each radio access area; it could be the same node providing radio access and fog node capabilities. In this case, both radio handover and service migration will take place when the user moves across radio access areas (see Mg1 and Mg2 in Figure 1 ). -(N-1): Multiple FNs per radio access area. This is usually a characteristic of a dense deployment. When the user moves across areas, in addition to the radio handover, a selection of the FNs to migrate to out of all the FNs in the area will take place. -(1-N): One FN is shared among multiple radio access coverage areas. In this case, as the user moves across these coverage areas, only the radio handover will occur, and thus migration is not needed (as depicted in the lower right part of Figure 1 ). • (C3) Migration scope: This differentiates between the case where the migration has to be maintained within the same area (SA); this can be found in particular in a vehicular cloud scenario (see Mg3 in Figure 1 ) or among nearby areas (AA, see Mg1 and Mg2 in Figure 1 ). • (C4) Migration timing: We distinguish migrations that start proactively (P), before the radio handover, while the user is still at the current area, and migrations that are performed reactively (R), after the radio handover. • (C5) Migration elements to move at a given time: Single (S) (e.g., a single self-contained service) or multiple (M) components with dependencies between them. In the latter case, the components having a high interdependency rate need to be comigrated together to the same locality as suggested in BIB004 . It is worth noting that there are some works that consider migrating multiple elements without explicit consideration of the aforementioned "comigration" issue. BIB005 A look at Table 4 , where the considered literature has been classified according to the aforementioned criteria, allows us to draw the following observations: • With regard to (C1), there are a few works considering the case of a mobile FN, and even fewer considering both users' and FNs' mobility. • As for (C2), the migration within the same area is not commonly tackled, except in the case of a vehicular scenario. • For (C3), authors usually consider a 1-1 mapping between the FN and the radio access technology it is associated to, especially in the case of MEC. However, with the advent of the [110] --Others BIB002 network densification trend, more instances of the N-1 mapping may be observed in the future. • Both proactive and reactive approaches have been almost equally studied in the literature (C4). Choosing one approach over the other depends on many considerations. For instance, while in BIB001 , the authors recommend the proactive approach to deal with delays that may be experienced in the reactive approach if the amount of data to be transferred is high, the authors in BIB003 consider the reactive approach as a backup mechanism to the cases of unexpected or unpredictable mobility. Indeed, in some contributions, the use of both approaches is envisioned. • Finally, regarding (C5), there has not been much attention on the migration of interdependent elements, which may be needed in real-world scenarios to support complex services.