Endtoend deadlines over dynamic topologies Despite the creativity of the scientific community and the funding agencies, the underlying model of computation behind IoT, WSN, cloud, edge, fog, and mist is fundamentally the same; Computational nodes which are dynamically interconnected to form a system in where both processing capacity and connectivity may vary over time. On top of such a system, we consider applications that need packets to flow along a path and adhere to endtoend deadlines. This application model is motivated by both control and automation systems, as well as telecom systems. The challenge is to guarantee endtoend deadlines when allowing nodes and applications to join or  :102,mainstream, and to some extent natural, approach to this is to relax the stringency of the constraint (e.g. use probabilistic guarantees, soft deadlines). In this paper we take a different approach and keep the endtoend deadlines as hard constraints and instead partially limit the freedom of how nodes and applications are allowed to leave and join. We present a theoretical framework for modeling such systems along with proofs that deadlines are always honored.

Dynamic IoTFog Task Allocation using ManytoOne Shortest Path Algorithm In this paper, we consider a task allocation problem in an IoTfog environment. We need to allocate a task from the IoT device to any fog node that meets the tasku0027s need. A task allocation method must be suitable for the dynamic nature of the network and the fog node condition. Thus, this paper presents an online algorithm and uses the SoftwareDefined Network. It can serially handle task allocation and get a global network and fog node statistics. The network has many fog nodes with many possible paths, it is important to select an optimal combination of them. So, we formulate the allocation decision as a multisource singletarget shortest path problem on a weighted graph. We propose a joint fog nodelink utilization cost and a modified A* algorithm called the ManytoOne Shortest Path algorithm. Our method can give a fast and optimal result. It shows by the experiment result which the proposed method outperforms the previous works.