Fog Computing: A Taxonomy, Survey and Future Directions

In recent years, the number of Internet of Things (IoT) devices/sensors has increased to a great extent. To support the computational demand of real-time latency-sensitive applications of largely geo-distributed IoT devices/sensors, a new computing paradigm named "Fog computing" has been introduced. Generally, Fog computing resides closer to the IoT devices/sensors and extends the Cloud-based computing, storage and networking facilities. In this chapter, we comprehensively analyse the challenges in Fogs acting as an intermediate layer between IoT devices/ sensors and Cloud datacentres and review the current developments in this field. We present a taxonomy of Fog computing according to the identified challenges and its key features.We also map the existing works to the taxonomy in order to identify current research gaps in the area of Fog computing. Moreover, based on the observations, we propose future directions for research

A Taxonomy for Management and Optimization of Multiple Resources in Edge Computing

Edge computing is promoted to meet increasing performance needs of data-driven services using computational and storage resources close to the end devices, at the edge of the current network. To achieve higher performance in this new paradigm one has to consider how to combine the efficiency of resource usage at all three layers of architecture: end devices, edge devices, and the cloud. While cloud capacity is elastically extendable, end devices and edge devices are to various degrees resource-constrained. Hence, an efficient resource management is essential to make edge computing a reality. In this work, we first present terminology and architectures to characterize current works within the field of edge computing. Then, we review a wide range of recent articles and categorize relevant aspects in terms of 4 perspectives: resource type, resource management objective, resource location, and resource use. This taxonomy and the ensuing analysis is used to identify some gaps in the existing research. Among several research gaps, we found that research is less prevalent on data, storage, and energy as a resource, and less extensive towards the estimation, discovery and sharing objectives. As for resource types, the most well-studied resources are computation and communication resources. Our analysis shows that resource management at the edge requires a deeper understanding of how methods applied at different levels and geared towards different resource types interact. Specifically, the impact of mobility and collaboration schemes requiring incentives are expected to be different in edge architectures compared to the classic cloud solutions. Finally, we find that fewer works are dedicated to the study of non-functional properties or to quantifying the footprint of resource management techniques, including edge-specific means of migrating data and services.Comment: Accepted in the Special Issue Mobile Edge Computing of the Wireless Communications and Mobile Computing journa

NDNSD: Service Publishing and Discovery in NDN

Service discovery is one of the crucial components of modern applications. With the advent of several new systems such as IoT, edge, cloud, etc the world is connected more than ever and smart devices are creeping towards every nook and corner of our surroundings. Not only the new systems are emerging but also the communication pattern is evolving i.e. from one-to-one (host-host) to many-to-many (distributed application, IoT). The definition of service has also changed over time. Unlike their meaning in the past as programs running on some machines, services today can be sensor devices collecting data, mobile devices offering computing service, or it can even be a piece of data generated by some system. To satisfy the changing dynamics and heterogeneity of the services and the demand of these evolving architectures several new protocols are developed on top of the TCP/IP stack. Nonetheless, the fundamental weakness of host-centric TCP/IP to support the need for distributed application (IoT, edge) and many-to-many communication (e.g. publisher-subscriber) have induced several weaknesses in the system and have made it more fragile. Named Data Networking (NDN) is an information-centric networking architecture that does the communication over signed, named content objects. Its pub-sub style of communication, data-centric security at the network layer, in-network caching, etc provides numerous benefits to modern systems and tries to overcome the shortcoming of TCP/IP. In this thesis, we propose NDNSD – a fully distributed, scalable, and general-purpose, service discovery protocol for information-centric architecture/NDN. It is developed on top of the synchronization protocol (sync) and offers publisher-subscriber API for service publishing and discovery. We present several design features of NDNSD and also establish how it is best suited for modern systems. We also introduce the concept of service-info and how it can be combined with sync and NDN hierarchical names to make service discovery generic. Finally, To substantiate our argument, we design, implement, and evaluate our protocol, and also provide some use-cases (e.g. Building Management System) to show how service discovery can be beneficial