In Distributed Hash Table (DHT)-based Mobile Ad Hoc Networks (MANETs), a logical structured network (i.e., follows a tree, ring, chord, 3D, etc., structure) is built over the ad hoc physical topology in a distributed manner. The logical structures guide routing processes and eliminate flooding at the control and the data plans, thus making the system scalable. However, limited radio range, mobility, and lack of infrastructure introduce frequent and unpredictable changes to network topology, i.e., connectivity/dis-connectivity, node/link failure, network partition, and frequent merging. Moreover, every single change in the physical topology has an associated impact on the logical structured network and results in unevenly distributed and disrupted logical structures. This completely halts communication in the logical network, even physically connected nodes would not remain reachable due to disrupted logical structure, and unavailability of index information maintained at anchor nodes (ANs) in DHT networks. Therefore, distributed solutions are needed to tolerate faults in the logical network and provide end-to-end connectivity in such an adversarial environment. This paper defines the scope of the problem in the context of DHT networks and contributes a Fault-Tolerant DHT-based routing protocol (FTDN). FTDN, using a cross-layer design approach, investigates network dynamics in the physical network and adaptively makes arrangements to tolerate faults in the logically structured DHT network. In particular, FTDN ensures network availability (i.e., maintains connected and evenly distributed logical structures and ensures access to index information) in the face of failures and significantly improves performance. Analysis and simulation results show the effectiveness of the proposed solutions.

Security mechanisms recommended by VANET standardization bodies are not sufficient to stop authorized vehicles from sending bogus or fake messages that in the worst cases could put people's life at risk. There are efforts in evaluating the behaviour of the vehicles in VANETs, based on reputation mechanisms. However, the most of them compromise the privacy, the messages are linkable and no anonymous. Our proposal ARS: Anonymous Reputation System for VANET focuses on a centralized reputation system privacy-preserving using pseudonyms and giving reputation level to different behavioral aspects of the vehicle. A reputation server collects feedback from the vehicles through a Road-Side Unit or vehicles with LTE/4G/5G connection and updates the vehicles reputation level by matching the pseudoidentities with its real identity. Considering the amount of negative feedback, ARS defines two security states to adapt the applications to the real security risk. We implement and evaluate the performance of ARS through a set of simulation experiments, based on an opportunistic message forwarding application. Results showed that the calculating reputation level of vehicles could help reduce the dissemination of fake messages.

The integration of Wireless Sensor Networks (WSN) and cloud computing brings several advantages. However, one of the main problems with the existing cloud solutions is the latency involved in accessing, storing, and processing data. This limits the use of cloud computing for various types of applications (for instance, patient health monitoring) that require real-time access and processing of data. To address the latency problem, we proposed a fog-assisted Link Aware and Energy E cient Protocol for Wireless Body Area Networks (Fog-LAEEBA). The proposed solution is based on the already developed state-of-the-art protocol called LAEEBA. We implement, test, evaluate and compare the results of Fog-LAEEBA in terms of stability period, end-to-end delay, throughput, residual energy, and path-loss. For the stability period all nodes in the LAEEBA protocol die after 7445 rounds, while in our case the last node dies after 9000 rounds. For the same number of rounds, the end-to-end delay is 2 seconds for LAEEBA and 1.25 seconds for Fog-LAEEBA. In terms of throughput, our proposed solution increases the number of packets received by the sink node from 1.5 packets to 1.8 packets. The residual energy of the nodes in Fog-LAEEBA is also less than the LAEEBA protocol. Finally, our proposed solution improves the path loss by 24 percent.

Due to widespread availability of WiFi networks in buildings, indoor location based systems become a reality. To provide indoor location based services (LBS), finding the current location of a human, a computer, a mobile device or equipment such as a small UAV (like Quad copter) is of great interest. The most prominent method for this purpose is the received signal strength (RSS)-based location from WiFi Access Points (APs) inside a building. Considerable amount of research is carried out in estimating current location and providing different services based on different wireless technologies. On the other hand, little attention has been paid to study and analyze the behavior of the received signal strength itself. It is challenging because the intensity of signal can change very frequently due to environmental features like topology, temperature, interaction with objects etc. In this paper, we study the behavior of WiFi signals in an indoor environment for RSS based localization by analyzing signals from three different access points by using triangulation technique. Our method is based on fingerprinting method. The experimental results reveal that the behavior of signal changes very frequently. The results lead us to the conclusion that understanding signals behavior is important before estimating current location and providing different LBS.