Large-scale Multihop Wireless Networks Research Articles

An intelligent access algorithm for large scale multihop wireless networks based on mean field game

In a distributed wireless network with a large number of nodes, competitive access of nodes may result in the deterioration of throughput and energy. Therefore, in this paper we propose an intelligent access algorithm based on the mean field game (MFG). First, we formulate the competitive access process between nodes as a game Query ID="Q1" Text="Please check and confirm that the authors and their respective affiliations have been correctly identified and amend if necessary." process by a stochastic differential game model, which maximizes the energy efficiency of nodes and obtain the optimal behavior strategy while meeting the requirements of channel access. However, as the number of nodes increases, the dimension of the matrix used to characterize the interaction between nodes becomes too large, which increases the complexity of the solution procedure. Therefore, we introduce the MFG and the interaction between nodes can be approximately transformed into the interaction between nodes and the mean field, which not only reduces the complexity, but also reduces the computational overhead. In addition, the HJB-FPK equation is solved to obtain the Nash equilibrium of the MFG. Finally, a backoff strategy based on the Markov model is proposed, and the node obtains the corresponding backoff strategy according to the network situation and its own state. Simulation results show that the proposed algorithm has good performances on optimizing network throughput and energy efficiency for a large scale multi-hop wireless network.

The impacts of weak links on topology discovery process in large-scale wireless multi-hop networks

In wireless multi-hop networks, especially large-scale wireless multi-hop networks, obtaining the network topology is of vital significance. In fact, in both proactive and reactive routing protocols, before establishing an appropriate end-to-end route, the source node needs to obtain the global or local topology. Our previous research has studied the impacts of weak links on reactive routing protocols, which can also be considered as local topology discovery process. In this article, in order to get insight of the impacts of weak links on topology discovery process, especially the global topology discovery on which the proactive routing protocols rely, we apply a Markov chain to model the most common used topology discovery process in large-scale wireless multi-hop networks. Considering the fading characteristics of wireless channel, we analyze the impacts of weak links on topology discovery algorithms. Simulation and theoretical results show that, with the increase in the network scale, the weak links have great impacts on the stability and even on the feasibility of wireless multi-hop networks.

Understanding Path Reconstruction Algorithms in Multihop Wireless Networks

Low-power and multihop wireless networking is envisioned as a promising technology to achieve both energy efficiency and easy deployment for many Internet of Things (IoT) applications. Measuring packet-level path is crucial for managing large-scale multihop wireless networks. Packet-level path information encodes the routing path, a packet that takes through a network. The availability of packet-level path information can greatly facilitate many network management tasks. It is challenging to reconstruct packet-level paths using a small overhead, especially for large-scale networks. While there is a long list of existing path reconstruction algorithms, these algorithms focus on specific network scenarios, e.g., periodic monitoring networks or event detection networks. There lacks a unified model for systematically understanding and comparing the performance of these algorithms in different network scenarios. In this paper, we fill this gap by proposing an abstract model. Using this model, it is possible to derive a decision space for selecting the best algorithm for different networks. Furthermore, this model also guides us to devise better path reconstruction algorithms (cPath <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">τ,</sub> cPath <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">s,</sub> and cPath <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">sT</sub> ) with respect to path reconstruction ratio. Extensive experiments demonstrate the prediction power of our model as well as the advantages of our proposed algorithms. The results show that our algorithm (cPath <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">sT</sub> ) improves a path reconstruction ratio from 94.4%, 34.3%, and 30.8% to 98.9%, 99.9%, and 60.1% on average in three network scenarios, respectively, compared with the best state-of-the-art algorithms.

The Impacts of Weak Links on Routing Process in Large Scale Multi-Hop Networks

In wireless multi-hop networks, especially large scale wireless multi-hop networks, the feasibility of routing strategies is of vital significance. However, the basic function of routing strategies, the ability of finding a path from source to destination, is seldom researched. In this paper, we apply a Markov chain to model the routing discovery process of wireless multi-hop networks with arbitrary routing strategies. Taking the fading characteristics of wireless channel into consideration, we analyze the impacts of weak links on routing algorithms in wireless multi-hop networks. The probability of routing success and the distribution of hop count are discussed in detail and their close-form solutions are given. Simulation and theoretical results show that, with the increase of the network scale, the impact of weak links gets stronger and even makes the routing strategies unusable. Our research has pointed out the relations between the performance of routing strategies and the network scale under the impact of weak links. The results have important significance for routing strategy designing and network planning.

Node Density and Delay in Large-Scale Wireless Networks With Unreliable Links

We study the delay performance in large-scale wireless multihop networks with unreliable links from percolation perspective. Previous works have showed that the end-to-end delay scales linearly with the source-to-destination distance, and thus the delay performance can be characterized by the delay-distance ratio γ. However, the range of γ, which may be the most important parameter for delay, remains unknown. We expect that γ may depend heavily on the node density λ of a wireless multihop network. In this paper, we investigate the fundamental relationship between γ and λ. Obtaining the exact value of γ(λ) is extremely hard, mainly because of the dynamically changing network topologies caused by the link unreliability. Instead, we provide both upper bound and lower bound to the delay-distance ratio γ(λ). Simulations are conducted to verify our theoretical analysis.

Towards Achieving Linear Capacity Scaling in Wireless Networks through Directed Energy Links

Large-scale multi-hop wireless networks have many important applications. However, Gupta and Kumar showed that the capacity of multi-hop wireless networks decreases as the number of nodes in the network increases. Subsequent research efforts to achieve linear capacity scaling have significant limitations such as long latency, high technical complexity, restricted traffic pattern, or infrastructure requirement. We propose to achieve close-to-linear (CTL) capacity scaling through the use of directed energy (DE) links such as laser communications links or highly directional pencil beam links in the EHF band in a hybrid network that also contains traditional omni-directional (OD) antenna links. Our approach has none of limitations mentioned earlier. We show that when the probability distribution of DE links follows the inverse-square law, a distributed scheme with local routing information suffice to achieve CTL capacity scaling.

A-GR: A novel geographical routing protocol for AANETs

With the rapid growth of general aircraft and lack of ground facilities, air traffic control and aeronautical communication system face huge pressure, especially in low-altitude airspace. Aeronautical ad hoc networks (AANETs) are large scale multi-hop wireless network of aircraft, which could provide direct air-to-air communication between aircraft without ground infrastructures. However, the features of aircraft node present a great challenge to provide efficient and reliable data packet delivery in AANETs. In this paper, we present an Automatic dependent surveillance-broadcast (ADS-B) system aided geographic routing protocol (called A-GR) for AANETs. The proposed A-GR uses the position and velocity of aircraft provided by airborne ADS-B system to eliminate the traditional routing beaconing and presents a velocity-based metric for next hop selection, which could adaptively cope with the fast moving of aircraft and dynamic changes of network topology. Many simulations are performed and the results show that the proposed A-GR can effectively decrease the routing overhead, improve the packet delivery ratio and make good use of the network resources.

Critical Density for Connectivity in 2D and 3D Wireless Multi-Hop Networks

In this paper we investigate the critical node density required to ensure that an arbitrary node in a large-scale wireless multi-hop network is connected (via multi-hop path) to infinitely many other nodes with a positive probability. Specifically we consider a wireless multi-hop network where nodes are distributed in ℝ <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> (d = 2, 3) following a homogeneous Poisson point process. The establishment of a direct connection between any two nodes is independent of connections between other pairs of nodes and its probability satisfies some intuitively reasonable conditions, viz. rotational and translational invariance, nonincreasing monotonicity, and integral boundedness. Under the above random connection model we first obtain analytically the upper and lower bounds for the critical density. Then we compare the new bounds with other existing bounds in the literature under the unit disk model and the log-normal model which are special cases of the random connection model. The comparison shows that our bounds are either close to or tighter than the known ones. To the best of our knowledge, this is the first result for the random connection model in both 2D and 3D networks. The result is of practical use for designing large-scale wireless multihop networks such as wireless sensor networks.

Scalable multi-hop routing in wireless networks

Infrastructure-less wireless multi-hop networks have long been proposed for natural disaster and warfare scenarios. However, the current demand of such networks has been towards social networking, gaming and ultimately, ubiquitous computing. In fact, the increasing number of users that own wireless capable devices is taking these networks to an entirely different scale. Existing routing protocols do not scale and do not consider the context wherein services operate. By presenting an alternative routing scheme that appropriately handles mobility of users among different contexts, large-scale clustered wireless networks are designed, using an efficient gateway selection with load-balancing capabilities. This approach uses a virtual hierarchy of clusters to explore the contextual-proximity of nodes, while reducing the total overhead of routing traffic even when compared with other cluster-based approaches. Moreover, it is capable of predicting gateway link disconnections, increasing the total amount of delivered data. The obtained results reveal that this routing scheme outperforms existing routing protocols regardless of the mobility pattern being used, being consistently lighter in overhead and delivering up to 50% more data traffic. These results motivate a new era of large-scale wireless multi-hop networks suitable for hand-held devices exchanging data amongst themselves.

Centrality-based power control for hot-spot mitigation in multi-hop wireless networks

When shortest path routing is employed in large scale multi-hop wireless networks such as sensor networks, nodes located near the center of the network have to perform disproportionate amount of relaying for others. Nodes in such traffic hot-spots deplete their batteries faster than others due to their high relay load. These traffic hot-spots also adversely affect the network capacity due to increased congestion in the regions. To solve the problem, various divergent routing schemes are used which route the data on center-avoiding divergent routing paths. Though they achieve better load balancing, overall relaying is increased significantly due to their longer routing paths. In this paper, we propose power control as a way for balancing relay load and mitigating hot-spots in wireless sensor networks. Using a heuristic based on the concept of centrality, we show that if we increase the power levels of only the nodes which are expected to relay more packets, significant relay load balancing can be achieved even with shortest path routing. Different from divergent routing schemes, such load balancing strategy is applicable to any arbitrary topology and traffic pattern. With extensive simulations, we show that centrality based power control can drastically increase the network lifetime of sensor networks. We compare its performance with other divergent routing schemes and multiple battery level assignment strategy. Also, it is shown that centrality based power control results into better throughput capacity in many different topologies.

Building New Reliable Wireless Network by Using Distributed Control

With the development of the pioneering deployments in multi-hop wireless networks, although the relative research have not proven successful. The performance of routing and transport is often unstable due to contention induced packet losses, especially when the network is large and the offered load is high. A reliable wireless network architecture by using distributed control for large-scale multi-hop wireless networks has been present in this paper, The design objective is to optimize the control performance. This control performance is a complex function of the network parameters, such as throughput, packet delay and packet loss probabilities. The goal of optimizing the control performance imposes implicit tradeoffs on the wireless network design as opposed to the explicit tradeoffs typical in wireless data and voice applications. Our analysis suggests that our approach will deliver improved service to users while greatly reducing support effort and cost.

Toward robust multi-hop data forwarding in large scale wireless networks

Design of robust network topology is an essential issue in large-scale multi-hop wireless networks since data packets are forwarded through intermediate nodes between source and destination, especially in the presence of non-cooperative nodes. Traditionally, topology design aims at generating network topology with high node degree, maximum throughput, and mitigation of malicious attacks. In this paper, we formulate a novel topology control problem as achieving optimal topology which maximizes network robustness against data forwarding distortion (DFD) in which a relay node may be compliant in route discovery, but drop or delay packets as non-cooperative nodes. Such node misbehavior can degrade network performance dramatically, without being detected by routing protocols and countermeasures. Therefore, we propose to design a network topology and data forwarding algorithms, namely PROACtive, in order to distribute data packets among cooperative nodes only, subject to k-connectivity constraint. Through analysis and simulations, we show that there exists a trade-off between achieving network robustness and k-connected with high probability (w.h.p.). By using distributed measurement schemes, data packets can be forwarded with low message complexity Θ( N), and improves network goodput significantly in different network scenarios.

The Limit of Information Propagation Speed in Large-Scale Multihop Wireless Networks

This paper investigates the speed limit of information propagation in large-scale multihop wireless networks, which provides fundamental understanding of the fastest information transportation and delivery that a wireless network is able to accommodate. We show that there exists a unified speed upper bound for broadcast and unicast communications in large-scale wireless networks. When network connectivity is considered, this speed bound is a function of node density. If the network noise is constant, the bound is a constant when node density exceeds a threshold; if the network noise is an increasing function of node density, the bound decreases to zero when node density approaches infinity. As achieving the speed bound places strict requirements on node locations, we also quantify the gap between the actual achieved speed and the desired bound in random networks in which the relay nodes are not located as desired. We find that the gap converges to zero exponentially as node density increases to infinity.

Self-organizing fault-tolerant topology control in large-scale three-dimensional wireless networks

Topology control protocol aims to efficiently adjust the network topology of wireless networks in a self-adaptive fashion to improve the performance and scalability of networks. This is especially essential to large-scale multihop wireless networks (e.g., wireless sensor networks). Fault-tolerant topology control has been studied recently. In order to achieve both sparseness (i.e., the number of links is linear with the number of nodes) and fault tolerance (i.e., can survive certain level of node/link failures), different geometric topologies were proposed and used as the underlying network topologies for wireless networks. However, most of the existing topology control algorithms can only be applied to two-dimensional (2D) networks where all nodes are distributed in a 2D plane. In practice, wireless networks may be deployed in three-dimensional (3D) space, such as under water wireless sensor networks in ocean or mobile ad hoc networks among space shuttles in space. This article seeks to investigate self-organizing fault-tolerant topology control protocols for large-scale 3D wireless networks. Our new protocols not only guarantee k -connectivity of the network, but also ensure the bounded node degree and constant power stretch factor even under k −1 node failures. All of our proposed protocols are localized algorithms, which only use one-hop neighbor information and constant messages with small time complexity. Thus, it is easy to update the topology efficiently and self-adaptively for large-scale dynamic networks. Our simulation confirms our theoretical proofs for all proposed 3D topologies.

Distributed and Cooperative Link Scheduling for Large-Scale Multihop Wireless Networks

A distributed and cooperative link-scheduling (DCLS) algorithm is introduced for large-scale multihop wireless networks. With this algorithm, each and every active link in the network cooperatively calibrates its environment and converges to a desired link schedule for data transmissions within a time frame of multiple slots. This schedule is such that the entire network is partitioned into a set of interleaved subnetworks, where each subnetwork consists of concurrent cochannel links that are properly separated from each other. The desired spacing in each subnetwork can be controlled by a tuning parameter and the number of time slots specified for each frame. Following the DCLS algorithm, a distributed and cooperative power control (DCPC) algorithm can be applied to each subnetwork to ensure a desired data rate for each link with minimum network transmission power. As shown consistently by simulations, the DCLS algorithm along with a DCPC algorithm yields significant power savings. The power savings also imply an increased feasible region of averaged link data rates for the entire network.