A Survey on Mobility-Induced Service Migration in the Fog, Edge, and Related Computing Paradigms <s> Proactive Actions. <s> With the proliferation of mobile devices and sensors, mobile situation awareness is becoming an important class of applications. The key requirement of this class of applications is low-latency processing of events stemming from sensor data in order to provide timely situational information to mobile users. To satisfy the latency requirement, we propose an opportunistic spatio-temporal event processing system that uses prediction-based continuous query handling. Our system predicts future query regions for moving consumers and starts processing events early so that the live situational information is available when the consumer reaches the future location. In contrast to existing systems, our system provides timely information about a consumer's current position by hiding computation latency for processing recent events. To evaluate our system, we measure the quality of results and timeliness of live situational information with various query parameters. Our evaluation shows that we can achieve highly meaningful query results with near-zero latency in most cases. <s> BIB001 </s> A Survey on Mobility-Induced Service Migration in the Fog, Edge, and Related Computing Paradigms <s> Proactive Actions. <s> Follow me cloud (FMC) is one of the solutions to the limitations of the service quality and type of functionality due to the inherent constraints of mobility management. In this paper, we address the tradeoff between the overhead and Quality of Experience (QoE) by proposing a mobility-based services migration prediction (MSMP). The aim of MSMP is to plan, for a given service, the sequence of data to transfer from distinct micro data centers (MDC) to the user according to his mobility pattern and the estimated load of data centers. MSMP consists of (1) a data transfer throughput estimation scheme, called DTT, that aims to estimate, in advance, the throughput that the user could receive; (2) MDC service area handoff time estimation scheme, called AHT, that aims to estimate the time windows when the user will perform MDC service area handoffs; and (3) service migration management scheme, called SMM, that aims to select optimal MDCs in terms of offered throughput and to split user requested service into several portions to be processed by these MDCs. We evaluate MSMP and compare it against the most recent related approaches; the simulation results show that MSMP outperforms existing approaches in terms of data latency. <s> BIB002 </s> A Survey on Mobility-Induced Service Migration in the Fog, Edge, and Related Computing Paradigms <s> Proactive Actions. <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> Proactive Actions. <s> This article proposes an approach to enhance users' experience of video streaming in the context of smart cities. The proposed approach relies on the concept of MEC as a key factor in enhancing QoS. It sustains QoS by ensuring that applications/services follow the mobility of users, realizing the "Follow Me Edge" concept. The proposed scheme enforces an autonomic creation of MEC services to allow anywhere anytime data access with optimum QoE and reduced latency. Considering its application in smart city scenarios, the proposed scheme represents an important solution for reducing core network traffic and ensuring ultra-short latency through a smart MEC architecture capable of achieving the 1 ms latency dream for the upcoming 5G mobile systems. <s> BIB004 </s> A Survey on Mobility-Induced Service Migration in the Fog, Edge, and Related Computing Paradigms <s> Proactive Actions. <s> Equipped with easy-to-access micro computation access points, the fog computing architecture provides low-latency and ubiquitously available computation offloading services to many simple and cheap Internet of Things devices with limited computing and energy resources. One obstacle, however, is how to seamlessly hand over mobile IoT devices among different computation access points when computation offloading is in action so that the offloading service is not interrupted -- especially for time-sensitive applications. In this article, we propose Follow Me Fog (FMF), a framework supporting a new seamless handover timing scheme among different computation access points. Intrinsically, FMF supports a job pre-migration mechanism, which pre-migrates computation jobs when the handover is expected to happen. Such expectations can be indicated by constantly monitoring received signal strengths. Then we present the design and a prototype implementation of FMF. Our evaluation results demonstrate that FMF can achieve a substantial latency reduction (36.5 percent in our experiment). In conclusion, the FMF design clears a core obstacle, allowing fog computing to provide interruption-resistant services to mobile IoT devices. <s> BIB005 </s> A Survey on Mobility-Induced Service Migration in the Fog, Edge, and Related Computing Paradigms <s> Proactive Actions. <s> Mobile edge computing platforms, such as cloudlets, bring computation resources closer to mobile users, as compared to the cloud, which decreases the end-to-end network latency. This benefit enables a myriad of real-time mobile applications, especially augmented reality (AR), that require low latency and high computation power. However, when mobile users move away from the attached cloudlet, the offloaded services have to be migrated or rebuilt on a new nearby cloudlet. However, this service rebuilding process takes a lot of time and may deteriorate user experience. In this paper, we propose a smart service rebuilding scheme which seamlessly restores the offloading services on the target cloudlet while the mobile user is moving. The service rebuilding process includes the radio handoff stage and service handoff stage. A seamless service rebuilding process is achieved via predicting user's target cloudlet before being triggered a radio handoff, by leveraging extracted features from the captured frames of the mobile user's camera. Furthermore, based on the proposed service rebuilding scheme, we design a feature mapping algorithm to achieve a high prediction precision and a short prediction latency. We implement our scheme on a testbed and conduct experiments using real world AR applications. The experimental results show that our proposed scheme decreases the service rebuilding latency by around 65.8%, as compared to the conventional rebuilding process. In addition, we conduct extensive simulations to evaluate the performance of our proposed feature mapping algorithm. Simulation confirms that our algorithm is robust and can predict users' target cloudlet with high precision and low latency. <s> BIB006 </s> A Survey on Mobility-Induced Service Migration in the Fog, Edge, and Related Computing Paradigms <s> Proactive Actions. <s> Fog computing is a promising solution to provide low-latency and ubiquitously available computation offloading services to widely distributed Internet of Things (IoT) devices with limited computing capabilities. One obstacle, however, is how to seamlessly hand over mobile IoT devices among different fog nodes to avoid service interruption. In this paper, we propose seamless fog (sFog), a new framework supporting efficient congestion control and seamless handover schemes. Intrinsically, sFog improves system performance during handovers (achieved by the handover scheme), and guarantees the performance does not degrade when handovers do not occur (achieved by the congestion control scheme). Through the congestion control scheme, jobs are efficiently offloaded without causing unnecessary system idling; through the handover scheme, jobs are pre-migrated to the target fog node when a handover is about to occur, in order to reduce migration delay. In order to evaluate the performance of sFog, we propose a theoretical framework and establish a real-world prototype. Both the theoretical and experimental results show that sFog achieves substantial delay reductions compared with traditional benchmark handover schemes. <s> BIB007 </s> A Survey on Mobility-Induced Service Migration in the Fog, Edge, and Related Computing Paradigms <s> Proactive Actions. <s> Mobile Edge Computing (MEC) will play a key role in next-generation mobile networks to extend the range of supported delay-sensitive applications. Furthermore, an increasing attention is paid to provide user-centric services, to better address the strict requirements of novel immersive applications. In this scenario, MEC solutions need to efficiently cope with user mobility, which requires fast relocation of service instances to guarantee the desired Quality of Experience. However, service migration is still an open issue, especially for resource-constrained edge nodes interconnected by high-latency and low-bandwidth links. In this paper, by leveraging the potential of lightweight container-based virtualization techniques, we investigate a novel approach to support service provisioning in dynamic MEC environments. In particular, we present a framework where proactive service replication for stateless applications is exploited to drastically reduce the time of service migration between different cloudlets and to meet the latency requirements. The performance evaluation shows promising results of our approach with respect to classic reactive service migration. <s> BIB008 </s> A Survey on Mobility-Induced Service Migration in the Fog, Edge, and Related Computing Paradigms <s> Proactive Actions. <s> We consider the migration of virtualized services (VSs) in Mobile Edge Computing (MEC), so as to facilitate server maintenance, load balancing under mobility, improved energy efficiency and resource utilization, and incident response. We consider a set of VSs that has to be migrated from a source placement to a target placement, while maintaining service continuity as much as possible. We formulate the VS migration problem as an integer programming problem, and analyze its complexity. We propose an efficient iterative algorithm for computing when and in what order the VSs shall be migrated among the MEC nodes. We evaluate the proposed solution in terms of total service value, efficiency, and scalability. Extensive simulations show that our algorithm is computationally effective, and performs close to optimal. <s> BIB009
Reducing migration latency has also been addressed in the literature by proactively taking actions to prepare the migration environment or by planning the migration execution. The relevant contributions in this category are described next and summarized in Table 8 . The authors in BIB003 enhance the Elijah edge computing platform  with a proactive service migration implementation. Within this implementation, users' movements are predicted using a regression model. Then, when the user is predicted to be changing its serving MEC, the target MEC is requested to initiate the migration procedure. Authors obtained a VM downtime of 1.60s thanks to the proactive approach. Aligned with this idea, the "follow me edge" (FME) concept has been introduced in BIB004 with an aim to "ensure that the user is always serviced from the closest edge." Within FME, the user's location is used to estimate the latency to both the serving and the target edge servers, and if appropriate, migration is triggered proactively. In BIB006 , a different approach is taken to reduce service migration latency across cloudlets. The proposed approach considers the case of an AR application and therefore leverages the features extracted from the user's camera to predict the target cloudlet prior to the radio handoff. Experiments conducted on a testbed show around 65% reduction in migration latency compared to the reactive scheme. The authors in BIB001 consider mobile situation awareness applications that require low-latency processing of sensor data events so that live situational information can be delivered to users in time. To meet such low-latency requirements, the proposed system ensures that sensor events are proactively processed in those regions along the user's mobility path where the request for situational information is likely to occur. Simulations confirm that doing so significantly reduces the perceived latency. The Follow Me Fog (FMF) framework has been proposed in BIB005 . In FMF, computation jobs are premigrated from one fog node to the other, prior to the wireless handover. Results obtained from a prototype implementation show that substantial latency reductions are achieved with the FMF premigration strategy. Building on FMF, sFog has been proposed in BIB007 , where a more detailed handover protocol, the corresponding theoretical framework, as well as a congestion control scheme were added compared to FMF. In BIB008 , a proactive service migration framework has been designed, with a specific focus on stateless applications in MEC environments. The main idea consists of placing service replicas in neighboring edge nodes so that service instances are ready to be used by the user when the handover occurs. Emulation shows that this proactive approach has a shorter migration time and a reduced amount of transferred data compared to its reactive counterpart. As opposed to approaches listed in Section 5.1.2, where planning migrations ahead of time had the objective of reducing the number of costly migrations, we identify in the following some works where migrations are planned beforehand for time-saving purposes. These include the "mobilitybased services migration prediction (MSMP)" scheme proposed in BIB002 . MSMP takes into account the user's mobility pattern as well as the expected load of the MDCs and then plans the processing and migration of the different portions of the service within MDCs in the user's path. Latency reductions have been observed in simulations thanks to the efficient planning achieved through the MSMP scheme. On the other hand, the authors in BIB009 consider an MEC scenario where the Virtualized Services (VSs) migration problem has been formulated as an integer programming problem with an objective to maximize the service availability while keeping the migration time below a predefined value. A low-complexity heuristic has been proposed to calculate the migration schedules. Simulations show that the proposed heuristic was effectively able to obtain a nearoptimal performance.