Structured Peer-to-Peer Overlay Deployment on MANET: A Survey

There are many common characteristics between Peer-to-Peer (P2P) overlay networks and Mobile Ad-hoc Networks (MANET). Self-organization, decentralization, dynamicity and changing topology are the most shared features. Furthermore, when used together, the two approaches complement each other. P2P overlays provide data storage/retrieval functionality, and their routing information can complement that of MANET. MANET provides wireless connectivity between clients without depending on any pre-existing infrastructure. The aim of this paper is to survey current P2P over MANET systems. Specifically, this paper focuses on and investigates structured P2P over MANET. Overall, more than thirty distinct approaches have been classified into groups and introduced in tables providing a structured overview of the area. The survey addresses the identified approaches in terms of P2P systems, MANET underlay systems and the performance of the reviewed systems

Surveying Position Based Routing Protocols for Wireless Sensor and Ad-hoc Networks

A focus of the scientific community is to design network oriented position-based routing protocols and this has resulted in a very high number of algorithms, different in approach and performance and each suited only to particular applications. However, though numerous, very few position-based algorithms have actually been adopted for commercial purposes. This article is a survey of almost 50 position-based routing protocols and it comes as an aid in the implementation of this type of routing in various applications which may need to consider the advantages and pitfalls of position-based routing. An emphasis is made on geographic routing, whose notion is clarified as a more restrictive and more efficient type of position-based routing. The protocols are therefore divided into geographic and non-geographic routing protocols and each is characterized according to a number of network design issues and presented in a comparative manner from multiple points of view. The main requirements of current general applications are also studied and, depending on these, the survey proposes a number of protocols for use in particular application areas. This aims to help both researchers and potential users assess and choose the protocol best suited to their interest

Would Current Ad Hoc Routing Protocols be Adequate for the Internet of Vehicles? A Comparative Study

In recent years we have seen a great proliferation of smart vehicles, ranging from cars to little drones (both terrestrial and aerial), all endowed with sensors and communication capabilities. It is hence easy to foresee a future with even more smart and connected vehicles moving around, occupying space and creating an Internet of Vehicles (IoV). In this IoV, a multitude of nodes (both static and mobile) will generate a continuous multihop flow of local information to support local smart environment applications. Therefore, one interesting environment for the IoV would be in the form of 3-D mobile ad-hoc networks (MANETs). Unfortunately, MANET routing protocols have generally been designed and analyzed keeping in mind a 2-D scenario; there is no guarantee on how they would support a 3-D topology of the IoV. To this end, we have considered routing protocols deemed as the state-of-the-art for classic MANETs and tested them over 3-D topologies to evaluate their assets and technical challenges

Energy Efficient UAV-Assisted Emergency Communication with Reliable Connectivity and Collision Avoidance

Emergency communication is vital for search and rescue operations following natural disasters. Unmanned Aerial Vehicles (UAVs) can significantly assist emergency communication by agile positioning, maintaining connectivity during rapid motion, and relaying critical disaster-related information to Ground Control Stations (GCS). Designing effective routing protocols for relaying crucial data in UAV networks is challenging due to dynamic topology, rapid mobility, and limited UAV resources. This paper presents a novel energy-constrained routing mechanism that ensures connectivity, inter-UAV collision avoidance, and network restoration post-UAV fragmentation while adapting without a predefined UAV path. The proposed method employs improved Q learning to optimize the next-hop node selection. Considering these factors, the paper proposes a novel, Improved Q-learning-based Multi-hop Routing (IQMR) protocol. Simulation results validate IQMRs adaptability to changing system conditions and superiority over QMR, QTAR, and QFANET in energy efficiency and data throughput. IQMR achieves energy consumption efficiency improvements of 32.27%, 36.35%, and 36.35% over QMR, Q-FANET, and QTAR, along with significantly higher data throughput enhancements of 53.3%, 80.35%, and 93.36% over Q-FANET, QMR, and QTAR.Comment: 13 page

A review of Energy Efficient Routing Protocols in Underwater Internet of Things

Oceans, covering 70% of Earth's surface, arelargely unexplored, with about 95% remaining a mystery.Underwater wireless communication is pivotal in various domains,such as real-time aquatic data collection, marine surveillance,disaster prevention, archaeological exploration, andenvironmental monitoring. The Internet of Things has openednew avenues in underwater exploration through the underwaterInternet of Things concept. This innovative technology facilitatessmart ocean research, from small case studies to large-scaleoperations. UIoT networks utilise underwater equipment andsensors to gather and transmit data in aquatic environments.However, the dynamic nature of these environments poseschallenges to the network's structure and communication,necessitating efficient routing solutions. Quality-of-service-awarerouting is vital as it minimises energy usage, extends battery life,and enhances network performance. This paper delves into thechallenges and limitations of UIoT networks, highlighting recentrouting methodologies. It also proposes a comparison frameworkfor routing methods, focusing on the quality of service inunderwater IoT networks, to foster more optimal route selectionand better resource management.Comment: 6 pages, 1 figure, conferenc

Intelligent MANET optimisation system

This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel University.In the literature, various Mobile Ad hoc NETwork (MANET) routing protocols proposed. Each performs the best under specific context conditions, for example under high mobility or less volatile topologies. In existing MANET, the degradation in the routing protocol performance is always associated with changes in the network context. To date, no MANET routing protocol is able to produce optimal performance under all possible conditions. The core aim of this thesis is to solve the routing problem in mobile Ad hoc networks by introducing an optimum system that is in charge of the selection of the running routing protocol at all times, the system proposed in this thesis aims to address the degradation mentioned above. This optimisation system is a novel approach that can cope with the network performance’s degradation problem by switching to other routing protocol. The optimisation system proposed for MANET in this thesis adaptively selects the best routing protocol using an Artificial Intelligence mechanism according to the network context. In this thesis, MANET modelling helps in understanding the network performance through different contexts, as well as the models’ support to the optimisation system. Therefore, one of the main contributions of this thesis is the utilisation and comparison of various modelling techniques to create representative MANET performance models. Moreover, the proposed system uses an optimisation method to select the optimal communication routing protocol for the network context. Therefore, to build the proposed system, different optimisation techniques were utilised and compared to identify the best optimisation technique for the MANET intelligent system, which is also an important contribution of this thesis. The parameters selected to describe the network context were the network size and average mobility. The proposed system then functions by varying the routing mechanism with the time to keep the network performance at the best level. The selected protocol has been shown to produce a combination of: higher throughput, lower delay, fewer retransmission attempts, less data drop, and lower load, and was thus chosen on this basis. Validation test results indicate that the identified protocol can achieve both a better network performance quality than other routing protocols and a minimum cost function of 4.4%. The Ad hoc On Demand Distance Vector (AODV) protocol comes in second with a cost minimisation function of 27.5%, and the Optimised Link State Routing (OLSR) algorithm comes in third with a cost minimisation function of 29.8%. Finally, The Dynamic Source Routing (DSR) algorithm comes in last with a cost minimisation function of 38.3%