Cross-layer Balanced and Reliable Opportunistic Routing Algorithm for Mobile Ad Hoc Networks

For improving the efficiency and the reliability of the opportunistic routing algorithm, in this paper, we propose the cross-layer and reliable opportunistic routing algorithm (CBRT) for Mobile Ad Hoc Networks, which introduces the improved efficiency fuzzy logic and humoral regulation inspired topology control into the opportunistic routing algorithm. In CBRT, the inputs of the fuzzy logic system are the relative variance (rv) of the metrics rather than the values of the metrics, which reduces the number of fuzzy rules dramatically. Moreover, the number of fuzzy rules does not increase when the number of inputs increases. For reducing the control cost, in CBRT, the node degree in the candidate relays set is a range rather than a constant number. The nodes are divided into different categories based on their node degree in the candidate relays set. The nodes adjust their transmission range based on which categories that they belong to. Additionally, for investigating the effection of the node mobility on routing performance, we propose a link lifetime prediction algorithm which takes both the moving speed and moving direction into account. In CBRT, the source node determines the relaying priorities of the relaying nodes based on their utilities. The relaying node which the utility is large will have high priority to relay the data packet. By these innovations, the network performance in CBRT is much better than that in ExOR, however, the computation complexity is not increased in CBRT.Comment: 14 pages, 17 figures, 31 formulas, IEEE Sensors Journal, 201

Recent Developments on Mobile Ad-Hoc Networks and Vehicular Ad-Hoc Networks

This book presents collective works published in the recent Special Issue (SI) entitled "Recent Developments on Mobile Ad-Hoc Networks and Vehicular Ad-Hoc Networks”. These works expose the readership to the latest solutions and techniques for MANETs and VANETs. They cover interesting topics such as power-aware optimization solutions for MANETs, data dissemination in VANETs, adaptive multi-hop broadcast schemes for VANETs, multi-metric routing protocols for VANETs, and incentive mechanisms to encourage the distribution of information in VANETs. The book demonstrates pioneering work in these fields, investigates novel solutions and methods, and discusses future trends in these field

V2V Routing in VANET Based on Fuzzy Logic and Reinforcement Learning

To ensure the transmission quality of real-time communications on the road, the research of routing protocol is crucial to improve effectiveness of data transmission in Vehicular Ad Hoc Networks (VANETs). The existing work Q-Learning based routing algorithm, QLAODV, is studied and its problems, including slow convergence speed and low accuracy, are found. Hence, we propose a new routing algorithm FLHQRP by considering the characteristics of real-time communication in VANETs in the paper. The virtual grid is introduced to divide the vehicle network into clusters. The node’s centrality and mobility, and bandwidth efficiency are processed by the Fuzzy Logic system to select the most suitable cluster head (CH) with the stable communication links in the cluster. A new heuristic function is also proposed in FLHQRP algorithm. It takes cluster as the environment state of heuristic Q-learning, by considering the delay to guide the forwarding process of the CH. This can speed up the learning convergence, and reduce the impact of node density on the convergence speed and accuracy of Q-learning. The problem of QLAODV is solved in the proposed algorithm since the experimental results show that FLHQRP has many advantages on delivery rate, end-to-end delay, and average hops in different network scenarios

Fuzzy Logic Based Geocast Routing in Vehicular Ad Hoc Network

1002-1010The purpose of vehicular ad hoc network (VANET) is timely, effectively and efficiently transmission of urgent messages from source to destination. These objectives can be solved effectively with geocast routing approaches in VANETs as the most of the intelligent transportation system (ITS) applications require sending information to the vehicles belonging to a particular geographic region. In this paper an attempt has been made to develop the geocast routing protocols using fuzzy logic. The fuzzy logic routing (FLR) approach is used to implement the protocols. Three membership functions for each input distance, direction, speed and five membership functions for output (chance) with Mamdani fuzzy inference system (FIS) are used. MATLAB R2015a has been used to analyze the performance of developed protocols and compared with other fuzzy routing protocols in terms of PDR and delay. It has been observed that fuzzified geocast protocols developed with FLR approach outperform fuzzy based unicast protocols reported by other authors

Routing schemes in FANETs: a survey

Flying ad hoc network (FANET) is a self-organizing wireless network that enables inexpensive, flexible, and easy-to-deploy flying nodes, such as unmanned aerial vehicles (UAVs), to communicate among themselves in the absence of fixed network infrastructure. FANET is one of the emerging networks that has an extensive range of next-generation applications. Hence, FANET plays a significant role in achieving application-based goals. Routing enables the flying nodes to collaborate and coordinate among themselves and to establish routes to radio access infrastructure, particularly FANET base station (BS). With a longer route lifetime, the effects of link disconnections and network partitions reduce. Routing must cater to two main characteristics of FANETs that reduce the route lifetime. Firstly, the collaboration nature requires the flying nodes to exchange messages and to coordinate among themselves, causing high energy consumption. Secondly, the mobility pattern of the flying nodes is highly dynamic in a three-dimensional space and they may be spaced far apart, causing link disconnection. In this paper, we present a comprehensive survey of the limited research work of routing schemes in FANETs. Different aspects, including objectives, challenges, routing metrics, characteristics, and performance measures, are covered. Furthermore, we present open issues

A Survey and Future Directions on Clustering: From WSNs to IoT and Modern Networking Paradigms

Many Internet of Things (IoT) networks are created as an overlay over traditional ad-hoc networks such as Zigbee. Moreover, IoT networks can resemble ad-hoc networks over networks that support device-to-device (D2D) communication, e.g., D2D-enabled cellular networks and WiFi-Direct. In these ad-hoc types of IoT networks, efficient topology management is a crucial requirement, and in particular in massive scale deployments. Traditionally, clustering has been recognized as a common approach for topology management in ad-hoc networks, e.g., in Wireless Sensor Networks (WSNs). Topology management in WSNs and ad-hoc IoT networks has many design commonalities as both need to transfer data to the destination hop by hop. Thus, WSN clustering techniques can presumably be applied for topology management in ad-hoc IoT networks. This requires a comprehensive study on WSN clustering techniques and investigating their applicability to ad-hoc IoT networks. In this article, we conduct a survey of this field based on the objectives for clustering, such as reducing energy consumption and load balancing, as well as the network properties relevant for efficient clustering in IoT, such as network heterogeneity and mobility. Beyond that, we investigate the advantages and challenges of clustering when IoT is integrated with modern computing and communication technologies such as Blockchain, Fog/Edge computing, and 5G. This survey provides useful insights into research on IoT clustering, allows broader understanding of its design challenges for IoT networks, and sheds light on its future applications in modern technologies integrated with IoT.acceptedVersio