A Survey on Mobility-Induced Service Migration in the Fog, Edge, and Related Computing Paradigms <s> Platforms <s> Geo-distributed Situation Awareness applications are large in scale and are characterized by 24/7 data generation from mobile and stationary sensors (such as cameras and GPS devices); latency-sensitivity for converting sensed data to actionable knowledge; and elastic and bursty needs for computational resources. Fog computing [7] envisions providing computational resources close to the edge of the network, consequently reducing the latency for the sense-process-actuate cycle that exists in these applications. We propose Foglets, a programming infrastructure for the geo-distributed computational continuum represented by fog nodes and the cloud. Foglets provides APIs for a spatio-temporal data abstraction for storing and retrieving application generated data on the local nodes, and primitives for communication among the resources in the computational continuum. Foglets manages the application components on the Fog nodes. Algorithms are presented for launching application components and handling the migration of these components between Fog nodes, based on the mobility pattern of the sensors and the dynamic computational needs of the application. Evaluation results are presented for a Fog network consisting of 16 nodes using a simulated vehicular network as the workload. We show that the discovery and deployment protocol can be executed in 0.93 secs, and joining an already deployed application can be as quick as 65 ms. Also, QoS-sensitive proactive migration can be accomplished in 6 ms. <s> BIB001 </s> A Survey on Mobility-Induced Service Migration in the Fog, Edge, and Related Computing Paradigms <s> Platforms <s> In recent years, the development of the Internet of Things (IoT) has largely been supported by the parallel development of the Cloud computing capacities. Cloud computing offered elastic and on-demand computing power able to host and support crucial IoT functions. However, the proliferation of connected objects poses the problem of the confidentiality of the data produced. This proliferation also threatens the performances of the supporting networks. To tackle those problems, the research community has recently turned to Fog Computing. In this paper, we present CIoud4IoT, a platform able to perform horizontal (roaming) and vertical (offloading) migration of IoT functions. We implement our demonstration using a Kubernetes cIuster organised in three tiers: Cloud, Edge and IoT gateways. Our first use cases shows how IoT function roaming can be used in the context of health care data exploitation. The second use case exploits the IoT offloading capacity of our platform to optimize the remote diagnostic of mechanical engines. <s> BIB002 </s> A Survey on Mobility-Induced Service Migration in the Fog, Edge, and Related Computing Paradigms <s> Platforms <s> The smart city is one of the prominent applications of the Internet of Things (IoT) and offers innovative services to its citizens. It can be viewed as segmented network in which different networks communicate via gateways through the global Internet. However, for the provision of services anywhere in a dense and heterogeneous IoT environment, this remote cloud infrastructure has limitations for scalability and is prone to long transmission latency. A decentralized architecture, such as fog computing, can efficiently minimize latency and support scalability by executing services to close proximity of objects. Physical proximity is not fixed and extends from gateways to dedicated service objects anywhere in the IoT. Therefore, an efficient platform is indispensable that improves network performance for scalability and low latency through service migration. We propose a service management platform under fog computing architecture that supports migrating services. The proposed service management platform reduces communication latency between service and object as compared to services on gateways or in remote cloud infrastructure. <s> BIB003 </s> A Survey on Mobility-Induced Service Migration in the Fog, Edge, and Related Computing Paradigms <s> Platforms <s> In a world where the number of smart cities is growing exponentially, there is a myriad of IoT devices which are generating immense data, 24×7. Centralized cloud data centers responsible for handling this huge data are being rapidly replaced with distributed edge nodes which move the computation closer to the users to provide low latencies for real-time applications. The proposed enhancements capitalizes on this design and proposes an effective way to achieve fault tolerance in the system. The concept of docker container migration is used to provide a near-zero downtime system on a distributed edge cloud architecture. An intuitively simple and visually attractive dashboard design is also being presented in this paper to remotely access the edge cloud management services. <s> BIB004
Apart from architectures, multiple platforms have been developed to validate different migration approaches. One such platform is Foglets, presented in BIB001 . Foglets provides APIs for application development as well as mechanisms for application component deployment. Additionally, QoS-sensitive and workload-sensitive migration mechanisms are proposed to deal with mobility and application dynamics. The obtained results show that QoS-sensitive proactive migration can be accomplished in 6ms in an emulated environment. The authors in BIB002 introduce Cloud4IoT as a "platform able to containerize IoT functions and optimize their placement." Both gateway-to-gateway (i.e., horizontal) and cloud/edge-to-gateway (i.e., vertical) migrations are included. To fully support its envisioned functionalities, Cloud4IoT uses relevant state-of-the-art tools such as Openstack [68] and Kubernetes  for cloud and container management. The authors in BIB003 propose a "service management platform that supports migrating IoT services" in a fog computing architecture. Its evaluation has been carried out in an emulated setup that showed a latency reduction compared to static edge-or cloud-based service placements. Finally, the authors in BIB004 present an edge computing platform based on Openstack++  . The proposed platform orchestrates container migration using MQTT and then uses CRIU [26] for the effective migration. The use of MQTT is justified by its ability to perform asynchronous communications, thus achieving minimal usage of the network bandwidth as needed in an edge environment.