EdgeDrone: QoS aware MQTT middleware for mobile edge computing in opportunistic Internet of Drone Things Abstract   Internet of Things is a crucial research empire in the current era which enables a wide diversity of applications. One of the emerging classes of technology in recent age dominate the universe of IoT is the concept of the Internet of Drones Thing (IoDT). The following work fundamentally emphasizes the key concepts of the Internet of Drones architecture in the context of the Edge computing perspective. A state of the art xe2x80x9cEdgeDronexe2x80x9d concept has been engineered where the standard message transfer strategy of IoT and the opportunistic AdHoc network have been amalgamated. Parameters like message transfer latency, overhead ratio, message delivery chances under several QoS values and resource usage, energy performance for the protocol have been analyzed. A hardware testbed has been implemented with the JavaScript platform along with the simulation which has been executed after tuning the performance of the protocols. The result shows 30% improvement in average packet delivery for enhanced MQTTSN and about 17% improvement for enhanced MQTT in comparing to standard strategy. The study also reveals the minimum value of the message delivery latency of 15.5 msec for enhanced MQTTSN in QoS1. In memory usage point of view, the result shows that the MQTT broker takes a maximum of 5.6 MB of memory during enhanced MQTTSN takes to publishxe2x80x93subscribe operation which is significantly less. Another two major parameters which report the maximum message transfer bandwidth of 620 msgsec for enhanced MQTTSN at QoS 1 and about 1800 msgsec for QoS 0 as well as the enhanced MQTTSN within 802.15.4 interface ensures minimum energy consumption amongst all other strategies

MQTTbased Middleware for Container Support in Fog Computing Environments Distributed architectures where the Internet of Things (IoT) and the cloud are efficiently integrated play an increasingly important role for IoT solutions. Among these architectures, there is a growing interest in the ones that support the opportunity of functionality offloading towards either intermediate fog nodes or IoT end devices. Relevant existing research work has mainly focused so far on virtual machine and container migration to intermediate fog nodes and on migration of very simple functions to IoT endpoints (to preserve their limited resources available). In this paper, we originally concentrate on the gap associated with benefitting from fog functionality at resourcepowerful IoT endpoints, to create a continuum deployment that glues IoT devices and the cloud. In particular, this paper originally presents a middleware that manages application deployment and lifecycle by simplifying and optimizing management operations such as device configuration and application constraint satisfaction. The proposed solution particularly fits highly articulated scenarios with large numbers of IoT devices and intermediate fog nodes, by supporting the opportunity to offload functionality in a split way between IoT endpoints and edge nodes. The reported experimental results confirm the feasibility of our approach in term of overhead, scalability, and application lifecycle management.