A Survey on Mobility-Induced Service Migration in the Fog, Edge, and Related Computing Paradigms <s> Architectures <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> Architectures <s> In the current mobile network architecture, network traffic between user equipment (UE) and services deployed on the public cloud is tromboned towards the anchor point which could lead to network congestion. Deploying services closer to the UE, for example near the eNodeB, is a potential solution. The services are deployed on small scale data centers connected to, or collocated with the eNodeB, called 'eNodeB-Cloud' (eNBC). Mobility of UEs presents a challenge for deploying services in an eNBC. When the UE is handed over from one eNodeB to another, seamless migration of UE context between the service instances running in different eNBCs needs to be ensured. In this paper, we propose a Platform as a Service framework to enable UE context migration between eNBCs. The architecture consists of handover signaling mechanism, TCP session migration technology, context transfer protocol and a set of APIs towards the service. An evaluation of the prototype implementation shows that on an average the time taken to migrate a UE context between two eNBCs is in the order of 12 ms, which is within the limit of handover interruption time between two eNodeBs. <s> BIB002 </s> A Survey on Mobility-Induced Service Migration in the Fog, Edge, and Related Computing Paradigms <s> Architectures <s> To kickstart the process of morphing Messina into a "smart" city, an explicit mission for the crowdfunded #SmartME project, it is essential to set up an infrastructure of smart devices embedding sensors and actuators, to be scattered all over the urban area. An horizontal framework coupled with the Fog computing approach, by moving logic toward the "extreme" edge of the Internet where data needs to be quickly elaborated, decisions made, and actions performed, is a suitable solution for data- intensive services with time-bound constraints as those usually required by citizens. This is especially true in the context of IoT and Smart City where thousands of smart objects, vehicles, mobiles, people interact to provide innovative services. We thus designed Stack4Things as an OpenStack-based framework spanning the Infrastructure-as-a-Service and Platform-as-a-Service layers. We present some of the core Stack4Things functionalities implementing a Fog computing approach towards a run- time "rewireable" Smart City paradigm, by outlining node management and contextualization mechanisms, also describing its usage in terms of already supported and developed verticals, as well as a specific example related to environmental data collection through #SmartME. <s> BIB003 </s> A Survey on Mobility-Induced Service Migration in the Fog, Edge, and Related Computing Paradigms <s> Architectures <s> New services and applications become part of our daily activities as we evolve into new solutions supported by cutting-edge paradigms, like the Internet of Things and Smart Cities. In order to properly achieve the benefits theoretically provided by these models, new kinds of services must be designed. These new services have special requirements, as well as the users that access to them. One of these requirements is low latency levels, since a delayed reply could render to chaos for applications such as eHealth and public safety. The communication infrastructure must cope with these challenges by offering innovative solutions. One of these solutions is a smart service placement system that facilitates the location of services in the proper position according to specific needs. On this paper, a service placement architecture for the Internet of Things is proposed, with especial emphasis in its main module, the Service Orchestrator, for which implementation details are provided, including a model for the service placement task. Furthermore, technologies to implement the modules from the architecture are suggested. This proposal, as well as its validation, is framed within the scope of the SusCity project. <s> BIB004 </s> A Survey on Mobility-Induced Service Migration in the Fog, Edge, and Related Computing Paradigms <s> Architectures <s> Due to their intrinsic resource constraints, the mobile Internet of Things (IoT) devices are not able to provide intensive services by just relying on their own facilities. Fog Computing effectively helps overcome this hurdle. Indeed, it extends the Cloud toward the network edge, distributing resources and services of computing, storage, and networking close to the end devices. This topological proximity is the key enabler of several advantages that are essential in many emerging ICT domains. Nonetheless, the mobility of an IoT device compromises such benefits as it increases the topological distance to the serving Fog node. Therefore, the Fog service has to be migrated in order to be always close enough to the served IoT device. We name this Companion Fog Computing (CFC), since the Fog service behaves as a "companion" of the correspondent application on the mobile device. In this paper, we present a Fog Computing Platform that performs stateful container (i.e., Fog service) migrations in order to enable CFC. Specifically, we introduce a CFC model from which we derive a reference architecture comprising all the functionalities required in a platform to make migration decisions and carry them out. Moreover, we demonstrate the soundness of the proposed reference architecture by discussing a proof-of-concept implementation based on the Stack4Things (S4T) platform, and we report a set of conducted experiments to show the feasibility of stateful container migrations. <s> BIB005 </s> A Survey on Mobility-Induced Service Migration in the Fog, Edge, and Related Computing Paradigms <s> Architectures <s> Recently, Mobile Edge Computing (MEC) is proposed to deploy with cellular base stations (BSs) to reduce the offloading delay and to provide computational resources and storage to nearby mobile users. However, the deployment of MEC with a BS introduces special challenges to mobility management. First, a MEC can only be accessed within the coverage area of its BS. Therefore, a user needs to perform both a radio handoff (HO) and a service migration when moving out of the cell coverage range. Second, as MECs have limited computational resource and storage, the target MEC may not have sufficient available resources to support new users. Therefore, a user with computation task may be forced to perform a radio HO to a different target BS in order to successfully migrate the service. These cause unnecessary HOs in cellular networks, especially when MECs are deployed with small cells, e.g., femtocells. These unnecessary HOs and service migrations incur a large signaling and migration cost. In this paper, we first propose a novel architecture, SharedMEC, to support user mobility. In addition, we propose a service HO decision algorithm and an analytical model to analyze the total cost which considers the total HO signaling cost, total migration signaling cost, and total migration cost. Simulation results show that our proposed architecture and service HO decision algorithm can significantly reduce the total cost. To the best of our knowledge, this is the first work that considers HO and migration issues together and analyzes the total cost in MEC systems. <s> BIB006 </s> A Survey on Mobility-Induced Service Migration in the Fog, Edge, and Related Computing Paradigms <s> Architectures <s> The upcoming fifth generation (5G) of mobile communications brings new paradigms, such as network slicing and automation, to the forefront. Cloud computing and network function virtualization (NFV) constitute two fundamental key enablers towards the implementation of these new paradigms. On the one hand, computational functionalities are no longer limited to distant servers, but they are coming closer to the end user through Multi-access Edge Computing (MEC) technology, thus creating a multi-tier cloud architecture in modern networks. On the other hand, going beyond the existing rigid architectures, NFV enables the flexible and on-the-fly creation and placement both of application and network functions, aiming at satisfying the diverse application requirements and optimizing the management of the heterogeneous (network, computational and storage) resources. In this paper, we discuss the challenges that arise in a MEC-enabled 5G architecture that supports the flexible placement/migration of network and application virtual network functions (VNFs), orchestrated by an NFV Orchestrator (NFVO) with admission management functionalities, able to manage on-the-fly the network functions and resources. Finally, we describe in detail a MECenabled testbed architecture that facilitates the development and testing of such solution in the context of 5G networks. <s> BIB007 </s> A Survey on Mobility-Induced Service Migration in the Fog, Edge, and Related Computing Paradigms <s> Architectures <s> Driven by the vision of edge computing and the success of rich cognitive services based on artificial intelligence, a new computing paradigm, edge cognitive computing (ECC), is a promising approach that applies cognitive computing at the edge of the network. ECC has the potential to provide the cognition of users and network environmental information, and further to provide elastic cognitive computing services to achieve a higher energy efficiency and a higher Quality of Experience (QoE) compared to edge computing. This paper firstly introduces our architecture of the ECC and then describes its design issues in detail. Moreover, we propose an ECC-based dynamic service migration mechanism to provide an insight into how cognitive computing is combined with edge computing. In order to evaluate the proposed mechanism, a practical platform for dynamic service migration is built up, where the services are migrated based on the behavioral cognition of a mobile user. The experimental results show that the proposed ECC architecture has ultra-low latency and a high user experience, while providing better service to the user, saving computing resources, and achieving a high energy efficiency. <s> BIB008
One of the early architectures for VM migration in fog computing has been proposed in BIB001 . One key functionality within this architecture is the "mobility behavior and handoff analysis," which determines the right time to perform a migration as well as the migration target based on users' movement. This is further facilitated by the actual VM/container migration module as well as the cloudlet discovery module, where the fog topology is constructed. The authors in BIB004 present an architecture for service placement in the IoT. In fact, after the initial placement, services can be continuously migrated to cope with changing users' and network conditions. An ILP formulation is proposed with the aim of minimizing (1) the hop count between users' and serving nodes, (2) the hop count between nodes in case services need to communicate due to dependencies linking them, and finally (3) the number of migrations to reduce oscillations in the system. More recently, companion fog computing (CFC) has been proposed in BIB005 to enforce that a container running a fog service always remains topologically close to the mobile IoT device. A reference architecture along with its migration-related functionalities are described. An implementation based on the S4T platform BIB003 is provided and performance metrics including the downtime, the migration time, and the memory footprint of the container states were derived. Considering a cellular network context instead, the authors in BIB002 define an architecture for service mobility between two eNodeB-clouds, leveraging standard protocols. A prototype implementation of this architecture is developed and reasonable context migration times were observed. The authors in BIB006 consider the problem of the costs incurred by frequent handovers and service migrations when considering densely deployed femtocells having MEC capabilities. The authors first propose an architecture that introduces a SharedMEC entity that facilitates sharing of migration information among a group of Femto-BSs. Then, this shared information is leveraged by a service handover decision algorithm to make the appropriate migration decisions. A set of simulations have been conducted and the use of the SharedMEC entity along with the service handover algorithm was shown to achieve the desired cost reductions. The authors in BIB007 consider an MECenabled 5G architecture. An NFV Orchestrator (NFVO) entity ensures that application and network virtual network functions are properly migrated. A testbed implementation is introduced to prove the feasibility of the considered architecture. Finally, the work in BIB008 introduces an architecture named edge cognitive computing (ECC) that "combines edge computing and cognitive computing," where cognitive computing provides machines with "'brain-like' cognitive intelligence." Within this context, the authors propose a reinforcement-learning-based service migration mechanism that addresses the tradeoff of cost minimization and QoE improvement. Experimental results show that the proposed ECC architecture can provide higher QoE compared to scenarios where cognition is not considered.