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Dynamic topology and power-controlled lightweight mobile devices usually affect the performance of wireless ad hoc networks and have always been a major focus of research. Data transmission between a source-destination pair is governed by different types of routing protocols like proactive, reactive, hybrid, geographical, etc. Reactive routing techniques are highly preferred due to on-demand source-based routing with limited space requirements. To get a stable route, the routing process should consider the link availability between the communicating nodes. If any two nodes along the route become unreachable, the communication could be interrupted. This could cause the receiver to lose data and experience longer delays. In this paper, we suggest a way to improve the existing DSR protocol. The focus is on choosing a stable route with less control overhead. During the route request phase, every participating node calculates its link availability time (LAT) for each adjacent link based on the current position of the neighbor and receiving signal strength. Links with lesser LATs than a threshold are not considered for route setup hence the flooding of control packets is reduced. Simulation has been performed over the basic DSR and proposed improvements over DSR in terms of control overhead, successful data transmission rate, and the number of route errors generated in the network. The findings show that previous knowledge of link availability during the routing phase aids in the discovery of more stable routes with lower control overhead, thereby promoting reliable data delivery and improving the overall network performance. [ABSTRACT FROM AUTHOR]

Due to increased traffic pressure, traditional urban rail vehicle–ground communication systems are no longer able to meet the increasing communication requirements. In this paper, ad hoc networks are applied to urban rail transit vehicle–ground communication systems to improve link reliability and reduce transmission delay. In the proposed network, a service-driven routing algorithm is proposed, which considers the distance factor for cluster head selection and optimizes the routing transmission delay by service priority and congestion level. An auxiliary node-based routing maintenance mechanism is also proposed to avoid the problem of frequent breakage of communication links due to the high-speed movement of trains. Through the simulation, the proposed algorithm can effectively reduce the packet loss rate, end-to-end delay, and routing overhead of vehicle–ground communication compared with the traditional routing algorithm, which is more conducive to meeting the next generation of urban rail transit vehicle–ground communication requirements. [ABSTRACT FROM AUTHOR]

In dynamic wireless networks, nodes move in large-scale spaces with different communications scenarios, including network traffic and unpredicted link state change. However, optimizing multi-user access mechanisms in multiple scenarios to maximize aggregate throughput still remains a practically essential and challenging issue. An efficient method to predict channel conditions and adapt to different communication environments for better performance in real-time is necessary. In this paper, we propose a novel Q-learning based MAC protocol using an intelligent backoff selection scheme to adaptively make decisions by evaluating rewards and variable learning parameters. Furthermore, an efficient channel observation scheme is proposed to optimize real-time decision-making more accurately with better assessment of channel states in different communication environments. Two typical wireless networks, i.e., wireless local area networks with dense users as infrastructure networks and mobile ad hoc networks with changing topologies as infrastructureless networks, are taken into account in simulations to show that the proposed protocol achieves significant performance improvement in terms of both aggregate throughput and packet loss rate with strong environmental adaptability. [ABSTRACT FROM AUTHOR]

The utilization of directional antennas for neighbor discovery in wireless ad hoc networks brings notable benefits, such as extended transmission range, reduced transmission interference, and enhanced antenna gain. However, when nodes use directional antennas for neighbor discovery, the communication range is limited, resulting in a lack of knowledge of potential neighbors. Hence, it is necessary to design a special antenna direction switching strategy for neighbor discovery based on directional antennas. Traditional methods of switching antenna directions are often random or follow predefined sequences, overlooking the historical knowledge of sector exploration for antenna directions. In contrast, existing machine learning approaches aim to leverage observed historical knowledge to adjust antenna directions for faster neighbor discovery. Nonetheless, the latency of neighbor discovery is still high because the node cannot fully utilize the observed historical knowledge (i.e.., only using the knowledge observed by the node in transmission mode, ignoring the knowledge observed by the node in reception mode). Meanwhile, the corresponding reward and penalty mechanisms are still not detailed enough (i.e.., these reward and penalty mechanisms only consider the sectors of discovered and undiscovered neighboring nodes, ignoring the scenario of sectors that have been rewarded). In this paper, the neighbor discovery process is modeled as a reinforcement learning-based learning automaton. We propose an enhanced reinforcement learning-based two-way transmit-receive directional antennas neighbor discovery algorithm, called ERTTND. The algorithm consists of a two-way transmit-receive reinforcement learning mechanism (TTRL) and an enhanced reward-and-penalty mechanism (ERAP). This algorithm leverages insights from nodes in transmission and reception modes to refine their tactical decisions. Then, through an enriched reward-and-penalty framework, nodes optimize their strategies, thus expediting neighbor discovery based on directional antennas in wireless ad hoc networks. Simulation results demonstrate that compared to existing representative algorithms, the proposed ERTTND algorithm can achieve over 30% savings in terms of average discovery delay and energy consumption. [ABSTRACT FROM AUTHOR]

Due to increased traffic pressure, traditional urban rail vehicle–ground communication systems are no longer able to meet the increasing communication requirements. In this paper, ad hoc networks are applied to urban rail transit vehicle–ground communication systems to improve link reliability and reduce transmission delay. In the proposed network, a service-driven routing algorithm is proposed, which considers the distance factor for cluster head selection and optimizes the routing transmission delay by service priority and congestion level. An auxiliary node-based routing maintenance mechanism is also proposed to avoid the problem of frequent breakage of communication links due to the high-speed movement of trains. Through the simulation, the proposed algorithm can effectively reduce the packet loss rate, end-to-end delay, and routing overhead of vehicle–ground communication compared with the traditional routing algorithm, which is more conducive to meeting the next generation of urban rail transit vehicle–ground communication requirements.

In wireless ad hoc networks, neighbor discovery is necessary as an initial step. In this work we present LECDH (Low Energy Collision Detection Hello), an energy-aware randomized handshake-based neighbor discovery protocol for static environments. We carried out simulations through Castalia 3.2 simulator and compared LECDH with an existing protocol EAH (Energy Aware Hello) used as reference. We conclude that the proposal outperforms the reference protocol both in one-hop and multi-hop environments in terms of Energy consumption, Discovery time, Number of discovered neighbors, Throughput, and Discoveries per packet sent, for high duty cycles. Moreover, for low number of nodes in LECDH, as the duty cycle is reduced the performance is better according to all 5 metrics in both environments. Overall, we found that our proposal follows more realistic assumptions and still allows nodes to succeed at discovering all their neighbors almost with probability 1. Moreover, a qualitative comparison of the reference solution and our proposal is included in this paper. [ABSTRACT FROM AUTHOR]

In this paper, we propose an analytical model of neighbor election-based distributed slot access by considering the relationship between the age of information (AoI) and the slot access process of nodes in wireless ad hoc networks. A node first maintains the information updates from its neighbors by relaying and receiving messages and determines message transmission slots by holding elections with its relevant competing neighbors. We first find out and analyze the interaction relationship between the transmission probability of nodes, the competing probability of neighbor nodes, and the violation probability that AoI exceeds the timeliness threshold of the neighbor election. Next, we obtain the approximated expression of the competing probability and the age violation probability based on the comprehensive analysis of the neighbor election process. Numerical and simulation results show that our approximation is tighter than the one in the literature and also provides insights into enhancing the design of network-aware distributed multiple access schemes. [ABSTRACT FROM AUTHOR]

Social networks are playing an increasingly important role in information dissemination in wireless ad hoc networks with the wide adoption of the mobile Internet. In particular, in social application scenarios such as Facebook and Twitter, the questions of how to fully consider the social relationships between users to ensure the quality of service (QoS) urgently needs to be explored. This paper investigates an optimal social relay selection scheme with high intimacy requirements to maximize the system throughput for social-physical ad hoc networks with device-to-device (D2D) communication. Different from previous studies, we jointly consider feasible relays and multiuser cooperative mobility with satisfactory link reliability for throughput maximization. On the one hand, we formulate a nonlinear and nonconvex problem, which is typically NP-hard, for throughput optimization. Specifically, this optimization problem is divided into two subproblems: i) selecting the optimal relays and ii) determining the best mobility strategy in terms of throughput. On the other hand, we first convert the relay selection subproblem into an optimal stopping phase problem, and then propose a definition of a graph representing the degrees of interference between physical links, transforming the original optimization problem into a convex problem that is solvable using the Lagrange multiplier method. Based on the above, we propose the Relay selection and Link Interference Degree Graph (RS-LIDG) algorithm to solve the two subproblems. Numerical simulations verify that the proposed RS-LIDG method improves the throughput gain by 26.29%, 123.43%, and 236.47% compared to the intuitive method (IM), the social-trust-based random mobility selection method (STS-RM), and the physical-based random mobility selection method (PHS-RM), respectively.

The ocean is a huge saltwater body that is different from terrestrial environments in terms of deployment circumstance, weather conditions, and user distributions. Therefore, it is difficult to apply terrestrial net-working technologies directly in oceans. The cost-effectiveness of satellites is still an issue to be addressed to increase their popularity due to their high cost in construction, launching, and maintenance and high deployment risks. Such situations stimulate many research efforts on networking technologies in the ocean space consisting of coastline, water surface, sky, and underwater. This article conducts a comprehensive survey on the related issues through reviewing the networking environments and communication networks already operating in the ocean space as well as ongoing R&D activities and results reported in the literature. These systems include coastal networks, water surface networks, sky networks, and underwater networks, which are reviewed and discussed along with summaries on the related topics and research issues necessary for further studies. This article, taking into account maritime communication networks and underwater networking together, aims to provide the reader with an overview on the state of the art and corresponding challenging issues for networking in the ocean space. [ABSTRACT FROM AUTHOR]

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Abstract One formal way of studying cooperation and incentive mechanisms in wireless ad hoc networks is to use game theory. In this respect, simple interaction models such as the forwarder’s dilemma have been proposed and used successfully. However, this type of models is not suited to account for possible fluctuations of the wireless links of the network. Additionally, it does not allow one to study the way a node transmits its own packets. At last, the repeated game models used in the related literature do not allow the important scenario of nodes with partial information (about the link state and nodes actions) to be studied. One of the contributions of the present work is precisely to provide a general approach to integrate all of these aspects. Second, the best performance the nodes can achieve under partial information is fully characterized for a general form of utilities. Third, we derive an equilibrium transmission strategy which allows a node to adapt its transmit power levels and packet forwarding rate to link fluctuations and other node actions. The derived results are illustrated through a detailed numerical analysis for a network model built from a generalized version of the forwarder’s dilemma. The analysis shows in particular that the proposed strategy is able to operate in the presence of channel fluctuations and to perform significantly better than the existing transmission mechanisms (e.g., in terms of consumed network energy).

Neighbor discovery represents a first step after the deployment of wireless ad hoc networks, since the nodes that form them are equipped with limited-range radio transceivers, and they typically do not know their neighbors. In this paper two randomized neighbor discovery approaches, called CDH and CDPRR, based on collision detection for static multi-hop wireless ad hoc networks, are presented. Castalia 3.2 simulator has been used to compare our proposed protocols against two protocols chosen from the literature and used as reference: the PRR, and the Hello protocol. For the experiments, we chose five metrics: the neighbor discovery time, the number of discovered neighbors, the energy consumption, the throughput and the number of discovered neighbors versus packets sent ratio. According to the results obtained through simulation, we can conclude that our randomized proposals outperform both Hello and PRR protocols in the presence of collisions regarding all five metrics, for both one-hop and multi-hop scenarios. As novelty compared to the reference protocols, both proposals allow nodes to discover all their neighbors with probability 1, they are based on collision detection and know when to terminate the neighbor discovery process. Furthermore, qualitative comparisons of the existing protocols and the proposals are available in this paper. Moreover, CDPRR presents better results in terms of time, energy consumption and number of discovered neighbors versus packets sent ratio. We found that both proposals achieve to operate under more realistic assumptions. Furthermore, CDH does not need to know the number of nodes in the network. [ABSTRACT FROM AUTHOR]

This article investigates the basic design principles for a new Wireless Network Operating System (WNOS), a radically different approach to software-defined networking (SDN) for infrastructure-less wireless networks. Departing from well-understood approaches inspired by OpenFlow, WNOS provides the network designer with an abstraction hiding (i) the lower-level details of the wireless protocol stack and (ii) the distributed nature of the network operations. Based on this abstract representation, the WNOS takes network control programs written on a centralized, high-level view of the network and automatically generates distributed cross-layer control programs based on distributed optimization theory that are executed by each individual node on an abstract representation of the radio hardware. We first discuss the main architectural principles of WNOS. Then, we discuss a new approach to automatically generate solution algorithms for each of the resulting subproblems in an automated fashion. Finally, we illustrate a prototype implementation of WNOS on software-defined radio devices and test its effectiveness by considering specific cross-layer control problems. Experimental results indicate that, based on the automatically generated distributed control programs, WNOS achieves 18%, 56% and 80.4% utility gain in networks with low, medium and high levels of interference; maybe more importantly, we illustrate how the global network behavior can be controlled by modifying a few lines of code on a centralized abstraction. [ABSTRACT FROM AUTHOR]

In machine-type communication (MTC) consisting high-mobility machines, such as vehicles, aircrafts, robots, etc., there is a strong demand for fast wireless networking. With radars extensively applied in these machines for environment awareness, radar assisted fast neighbor discovery (ND) for wireless ad hoc networks is proposed to realize fast wireless networking for MTC. Four neighbor discovery algorithms are designed according to the accuracy level of prior information provided by radar. Then, the performance of neighbor discovery algorithms is analyzed theoretically. Simulation results are further provided to compare neighbor discovery algorithms with and without the prior information from radar. The results demonstrate that the time consumption of neighbor discovery is greatly reduced with prior information of radar. Moreover, the time consumption with prior information from radar increases with the number of nodes. However, the increasing speed is much slower than the neighbor discovery without prior information from radar. This paper proves the advantages of radar assisted neighbor discovery, which may motivate the study of radar assisted wireless networking schemes in the future.

Modern life cannot be imagined without wireless ad hoc networks (WANETs). People use, in a daily manner, smart phones, laptops or tablet computers. With an increasing number of users of WANETs, the need for a fast throughput and small delay is increasing as well. One efficient way to provide users with such demands is to find an optimal route between source and destination node. Therefore, many routing protocols and metrics for WANETs are proposed in last decades. It is very important to test performances of the proposed protocols in various network scenarios. The computer simulation is a very efficient way to test routing protocols and to evaluate their significance and practical value. One of the most recent but very frequently used discrete-event network simulators is Network Simulator 3 (NS-3). In order to contribute to the NS-3 simulator development, an implementation of one of the most commonly used metric in WANET protocols the expected transmission count (ETX) is proposed in this paper. ETX metric is implemented within an ad-hoc on demand distance vector (AODV) protocol. The source code of this implementation is publicly available.

In this article, we address the scheduling problem in wireless ad hoc networks by exploiting the computational advantage that comes when scheduling problems can be represented by claw-free conflict graphs where we consider a wireless broadcast medium. It is possible to formulate a scheduling problem of broadcast transmissions as finding the maximum weighted independent set (MWIS) in the conflict graph of the network. Finding the MWIS of a general graph is NP-hard leading to an NP-hard complexity of scheduling. In a claw-free conflict graph, MWIS may be found in polynomial time leading to a throughput-optimal scheduling. We show that the conflict graphs of certain wireless ad hoc networks are claw-free. In order to obtain claw-free conflict graphs in general networks, we suggest introducing additional conflicts (edges) with the aim of keeping the decrease in MWIS size minimal. To this end, we introduce an iterative optimization problem to decide where to introduce edges and investigate its efficient implementation. We conclude that the claw breaking method by adding extra edges can perform very close to optimal scenario and better than the polynomial time maximal independent set scheduling benchmark under the necessary assumptions. [ABSTRACT FROM AUTHOR]

Network coding, as one of the foremost techniques boosting the performance of the wireless networks, has recently acquired notable popularity. As a result, a new category of routing approaches named as the coding-aware routing scheme, has been emerged. In such routing schemes, the possible coding opportunities are identified prior to the path establishment, and paths containing coding opportunities are prioritized to be established. Motivated by the appreciable efficiency of the coding-aware routing schemes, this paper leverages fuzzy logic and proposes a novel coding-aware routing approach alluded to as Fuzzy-logic-based Network Coding-aware Routing (FNCR) protocol. Notwithstanding a number of previously proposed coding-aware routing schemes which merely endeavor to establish paths including more coding opportunities, FNCR suggests embedding a purposefully designed fuzzy system in each node in order to calculate the overall desirability of the nodes in terms of some momentous factors such as the coding capability, the remaining energy, and the workload of the node. In addition to a new routing metric which utilizes the calculated overall desirability, the previously proposed coding conditions are modified such that more possible coding opportunities can now be identified. Simulation results demonstrate that FNCR outperforms the formerly proposed approaches employing network coding, in terms of throughput, end to end delay, packet delivery ratio, and lifetime of the network. [ABSTRACT FROM AUTHOR]

Byzantine attack is a severe security concern in network coding enabled wireless ad hoc networks, because the malicious nodes can easily inject bogus packets into the information flow and cause an epidemic propagation of pollution. In this paper, we address the Byzantine attack by proposing a malicious node identification scheme, which can achieve a high identification accuracy on malicious nodes and protect the benign nodes from being mis-identified as attackers. We consider two practical challenges, namely, 1) only a fraction of the intermediate nodes can be deployed as defenders; and 2) the malicious nodes are intelligent–they pretend to be legitimate nodes probabilistically to reduce the chances of being identified. Theoretical analysis and extensive simulations show that our scheme performs well even under the conditions mentioned above. Furthermore, we conduct a series of comparisons between our scheme and several existing schemes, which show that our scheme outperforms them in both identification accuracy and valid throughput during the identification procedure. Finally, we present a two-player game theory framework to find the optimal strategy for the defender, and also provide a case study of the defender’s strategy optimization. [ABSTRACT FROM AUTHOR]

In wireless ad hoc networks where the energy in each node is limited, the nodes located in the center area usually relay too much data and run out of energy very quickly, and thus cause the energy hole problem. This paper analyzes the optimal coverage radius of each node and the optimal hop distance in terms of energy saving, and provides a crosslayer energy balancing and control strategy. This strategy combines the optimal coverage radius and the location information to solve the energy hole problem. Firstly, we analyzed the impact of the coverage radius on the data transmission and routing process, and discovered the optimal hop distance under a given transmitting signal-to-noise-ratio (SNR). Secondly, to make the network energy efficient, the optimal receiving SNR is designed to help nodes decide whether to resend routing request or not. Finally, we proposed an energy balancing routing method based on the optimal hop distance and receiving SNR, with the objective of reducing the energy consumption of nodes in the center area and improving the network capacity. Simulation results show that the proposed approach outperforms the existed protocols in terms of the number of surviving nodes, network capacity, routing failure and energy balance. [ABSTRACT FROM AUTHOR]

The upper bound capacity based on the SINR model is a very important parameter when evaluating the performance of the multi-hop wireless ad hoc networks. In this paper, a new upper bound capacity algorithm is proposed. Firstly, we analyzed the classical physics SINR model over the Rayleigh fading channels to establish the relationship between density of nodes and path outage probability. Then, we developed the closed-form expression of the upper bound transmission capacity based on the Weber model for the random networks. Finally, we evaluated effects of parameters in the communication range, density, SINR threshold and fading factors, and consequently transmission capacity of the network by sensitivity analysis. The numerical simulation showed that the optimum density of nodes was existed to obtain the upper bound transmission capacity. The capacity increased firstly and then decreased over the density of nodes increasing. It affected by channel fading factor and communication range sensitively. [ABSTRACT FROM AUTHOR]

In this paper, we propose a distributed solution to design a multi-hop ad hoc Internet of Things (IoT) network where mobile IoT devices strategically determine their wireless transmission ranges based on a deep reinforcement learning approach. We consider scenarios where only a limited networking infrastructure is available but a large number of IoT devices are deployed in building a multi-hop ad hoc network to deliver source data to the destination. An IoT device is considered as a decision-making agent that strategically determines its transmission range in a way that maximizes network throughput while minimizing the corresponding transmission power consumption. Each IoT device collects information from its partial observations and learns its environment through a sequence of experiences. Hence, the proposed solution requires only a minimal amount of information from the system. We show that the actions that the IoT devices take from its policy are determined as to activate or inactivate its transmission, i.e., only necessary relay nodes are activated with the maximum transmit power, and nonessential nodes are deactivated to minimize power consumption. Using extensive experiments, we confirm that the proposed solution builds a network with higher network performance than the current state-of-the-art solutions in terms of system goodput and connectivity ratio. [ABSTRACT FROM AUTHOR]

Broadcasting is a fundamental operation which is frequent in wireless ad hoc networks. A simple broadcasting mechanism, known as flooding, is to let every node retransmit the message to all its 1-hop neighbors when receiving the first copy of the message. Despite its simplicity, flooding is very inefficient and can result in high redundancy, contention, and collision. One approach to reducing the redundancy is to let each node forward the message only to a small subset of 1-hop neighbors that cover all of the node's 2-hop neighbors. In this paper we propose two practical heuristics for selecting the minimum number of forwarding neighbors: an O(n log n) time algorithm that selects at most 6 times more forwarding neighbors than the optimum, and an O(n log(2) n) time algorithm with an improved approximation ratio of 3, where n is the number of 1- and 2-hop neighbors. The best previously known algorithm, due to Bronnimann and Goodrich, guarantees O(1) approximation in O(n(3) log n) time.

Accurate link quality estimation is a fundamental building block in quality aware multi hop routing. In an inherently lossy, unreliable and dynamic medium such as wireless, the task of accurate estimation becomes very challenging. Over the years ETX has been widely used as a reliable link quality estimation metric. However, more recently it has been established that under heavy traffic loads ETX performance gets significantly worse. We examine the ETX metric's behavior in detail with respect to the MAC layer and UDP data; and identify the causes of its unreliability. Motivated by the observations made in our analysis, we present the design and implementation of our link quality measurement metric xDDR – a variation of ETX. This article extends xDDR to support network mobility. Our experiments show that xDDR substantially outperforms minimum hop count, ETX and HETX in terms of end-to-end packet delivery ratio in static as well as mobile scenarios.

In the past few years, we have seen a rapid expansion in the field of mobile computing due to the proliferation of inexpensive, widely available wireless devices. However, current devices, applications and protocols are solely focused on cellular or wireless local area networks (WLANs), not taking into account the great potential offered by ad hoc networking. Ad hoc networks are wireless mobile networks that can operate without infrastructure and without centralized network management. In such networks, the wireless mobile nodes may dynamically enter the network as well as leave the network. Mobility and dynamic topology are the main characteristics of ad hoc networks. In the last years, the hundreds of new routing protocols were designed, that are used for the various scenarios of this design space. The routing features in wireless ad hoc networks are described. The corresponding routing protocols are reviewed. The paper proposes a method for selecting the preferred protocol wireless networks using the mathematical tools of neural networks.

Consider a wireless network where each communication link has a minimum bandwidth quality-of-service requirement. Certain pairs of wireless links interfere with each other due to being in the same vicinity, and this interference is modeled by a conflict graph. Given the conflict graph and link bandwidth requirements, the objective is to determine, using only localized information, whether the demands of all the links can be satisfied. At one extreme, each node knows the demands of only its neighbors; at the other extreme, there exists an optimal, centralized scheduler that has global information. The present work interpolates between these two extremes by quantifying the tradeoff between the degree of decentralization and the performance of the distributed algorithm. This open problem is resolved for the primary interference model, and the following general result is obtained: if each node knows the demands of all links in a ball of radius $d$ centered at the node, then there is a distributed algorithm whose performance is away from that of an optimal, centralized algorithm by a factor of at most ${{ (2d+3)}}/{{ (2d+2)}}$. The tradeoff between performance and complexity of the distributed algorithm is also analyzed. It is shown that for line networks under the protocol interference model, the row constraints are a factor of at most 3 away from optimal. Both bounds are best possible. [ABSTRACT FROM AUTHOR]