Fog-computing is a new network architecture and computing paradigm that uses user or near-users devices (network edge) to carry out some processing tasks. Accordingly, it extends the cloud computing with more flexibility the one found in the ubiquitous networks. A smart city based on the concept of fog-computing with flexible hierarchy is proposed in this paper. The aim of the proposed design is to overcome the limitations of the previous approaches, which depends on using various network architectures, such as cloud-computing, autonomic network architecture and ubiquitous network architecture. Accordingly, the proposed approach achieves a reduction of the latency of data processing and transmission with enabled real-time applications, distribute the processing tasks over edge devices in order to reduce the cost of data processing and allow collaborative data exchange among the applications of the smart city. The design is made up of five major layers, which can be increased or merged according to the amount of data processing and transmission in each application. The involved layers are connection layer, real-time processing layer, neighborhood linking layer, main-processing layer, data server layer. A case study of a novel smart public car parking, traveling and direction advisor is implemented using IFogSim and the results showed that reduce the delay of real-time application significantly, reduce the cost and network usage compared to the cloud-computing paradigm. Moreover, the proposed approach, although, it increases the scalability and reliability of the users’ access, it does not sacrifice much time, nor cost and network usage compared to fixed fog-computing design.

<p class="Abstract">Abstract—The process of finding a route between the transmitter and the receiver node in the Mobile Adhoc Networks (MANets) is a renewed issue that is becoming more and more interesting to the researchers as this type of networks  grow and expand. The dynamic nature of MANET and the limited capabilities of wireless nodes in terms of memory size and battery charge are the most important obstacles to the routing (path-finding) process between nodes. In this research, we introduced a new protocol based on the well-known DSR protocol to add a mechanism that controls the RREQ Flooding process, which aims to reach more stable (life-long) routes while reducing the overhead of routing process caused by link breakage between nodes and reduce the overhead of network flooding with RREQ messages with each attempt to find a path. In this proposed mechanism, a specific group is selected from within the devices adjacent to the transmitter to be sent RREQ so that these devices are selected based on the stability evaluation criterion. The stability criterion is calculated based on three weighted factors: the speed of the node, the out-degree value (the number of adjacent nodes), and the number of tracks stored in the device memory. The proportion of devices selected is automatically changed adaptively to ensure that the expected throughput of this network is achieved. The proposed protocol was tested using simulation where results showed that ASDSR proved an enhancement in route stability about (0.13), and a decrease in the number of deleted routes by (9%), while maintaining the expected packet delivery ratio of the original DSR by about (0.86).</p>

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