Large-scale Multi-hop Networks Research Articles

A learning-based distributed algorithm for scheduling in multi-hop wireless networks

We address the joint problem of learning and scheduling in multi-hop wireless network without a prior knowledge on link rates. Previous scheduling algorithms need the link rate information, and learning algorithms often require a centralized entity and polynomial complexity. These become a major obstacle to develop an efficient learning-based distributed scheme for resource allocation in large-scale multi-hop networks. In this work, by incorporating with learning algorithm, we develop provably efficient scheduling scheme under packet arrival dynamics without a priori link rate information. We extend the results to distributed implementation and evaluation their performance through simulations.

Cognitive Communications System for Ultra-Low Size, Weight and Power (SWAP) Attributable Platforms

Communications resiliency and data distribution assurance has been compromised in highly competitive, dynamic, and stressing environments with the introduction of off the shelf, high performing jammers. This paper introduces a novel cognitive communications system that can be fielded on small attributable platforms; the architecture amalgamates a highly capable environmentally perceptive aperture, a software defined radio, and sophisticated networking techniques. The proposed cognitive communications system uses the 5G new radio waveform and applies groundbreaking machine learning methods to facilitate systems orchestration amongst its subsystems to transfer information effectively between nodes, and across large-scale multi-hop networks, essential for rapid strike missions. With the challenges imposed by mature and readily available jammers, a cognitive communications system can be used to maintain and sustain continuous communications to provide near real-time surveillance and situational awareness updates. In addition to describing the comprehensive cognitive communications system architecture, a jamming analysis will be presented. Performance results for an operational use case will be compared to existing trite architectures consisting of siloed apertures and standard radio systems to demonstrate an improvement of approximately 10 dB in communications margin with the auspicious technology offering of the cognitive communications system for low size, weight, and power attributable platforms.

Self-organization scheme for balanced routing in large-scale multi-hop networks

We propose a self-organization scheme for cost-effective and load-balanced routing in multi-hop networks. To avoid overloading nodes that provide favourable routing conditions, we assign each node with a cost function that penalizes high loads. Thus, finding routes to sink nodes is formulated as an optimization problem in which the global objective function strikes a balance between route costs and node loads. We apply belief propagation (its min-sum version) to solve the network optimization problem and obtain a distributed algorithm whereby the nodes collectively discover globally optimal routes by performing low-complexity computations and exchanging messages with their neighbours. We prove that the proposed method converges to the global optimum after a finite number of local exchanges of messages. Finally, we demonstrate numerically our framework’s efficacy in balancing the node loads and study the trade-off between load reduction and total cost minimization.

On Enhancing TCP to Deal with High Latency and Transmission Errors in Geostationary Satellite Network for 5G-IoT

The geostationary (GEO) satellite networks have two important influencing factors: high latency and transmission errors. Similarly, they will happen in the large-scale multihop network of the Internet of things (IoT), which will affect the application of 5G- (5th-generation mobile networks-) IoT. In this paper, we propose an enhanced TCP mechanism that increases the amount of data transferred in the slow start phase of TCP Hybla to mitigate the effect of long RTT and incorporates a refined mechanism of TCP Veno, which can distinguish packet loss between random and congestion. This scheme is evaluated and compared with NewReno, Hybla, and Veno by simulation, and the performance improvement of the proposed TCP scheme for GEO satellite network in the presence of random packet losses is demonstrated. At the same time, the enhanced TCP scheme can improve the transmission performance in the future 5G-IoT heterogeneous network with high delay and transmission .

Operation State Scheduling Towards Optimal Network Utility in RF-Powered Internet of Things

RF power transfer is becoming a reliable solution to energy supplement of Internet of Things (IoT) in recent years, thanks to the emerging off-the-shelf wireless charging and sensing platforms. However, as a core component of IoT, sensor nodes mounted with these platforms can not work and harvest energy simultaneously, due to the low-manufacture-cost requirement. This leads to a new design challenge of optimally scheduling sensor nodes’ operation states: working or recharging, to achieve a desirable network utility. In our design, we first consider a single-hop special case of small-scale networks. We transform the operation state scheduling problem into a linear programming problem, and obtain an optimal analytical solution. Then a general case of large-scale multi-hop networks is investigated. The multi-hop operation state scheduling problem is proved to be NP-hard. We show that the spatiotemporal coupling caused by time-varying network topology makes the problem quite challenging. Based on Lyapunov optimization technique, we design a State Scheduling Algorithm (SSA) with a proved performance guarantee. Our algorithm decouples the primal problem by defining a dynamic energy threshold vector, which successfully schedules each sensor node to the desirable state according to its energy level. To verify our design, the SSA is implemented on a Powercast wireless charging and sensing testbed, achieving about 85 percent of the theoretical optimal with quite low time complexity. Furthermore, numerous simulation results demonstrate that the SSA outperforms the baseline algorithms and achieves good performance under different network settings.

Adaptive Joint Lossy Source-Channel Coding for Multihop IoT Networks

We consider monitoring applications in multihop wireless sensor networks (WSNs), where nodes rely on limited batteries so that energy efficiency and reliability are of paramount importance. Typically, lossy compression is aimed at saving transmission energy, yet affects the quality of transmitted data over lossy channels. Accordingly, using error correction coding (ECC) along with compression is required to guarantee both energy efficiency and high-fidelity reconstruction. In this paper, we analyze the energy efficiency of the joint use of lossy compression along with ECC, with the twofold objective of extending the network lifetime and assuring reliability. Specifically, we consider an adaptive joint lossy source-channel coding (JLSCC) system, where the energy efficiency and reliability performances depend on both the compression and the coding rates. Therein, we first carry out a performance analysis of JLSCC, considering realistic models of communication and computational energies, when the communication is performed over a Rayleigh fading channel. Then, we evaluate the performance of the JLSCC system compared to lossy compression and ECC systems in both end-to-end and multihop communications. Our results reveal that an adaptive JLSCC results in substantial energy saving while guaranteeing the required reliability performance, compared to both lossy compression and channel coding systems, that cannot be efficient for both energy and reliability. Instead, the JLSCC system is proved to be energy efficient for small distance end-to-end communication and large-scale multihop network, while leading to satisfactory reliability performance.

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.

Extensions to the IEEE 802.11 TSF for Efficient and Reliable Network Synchronization in Large Scale MANETs

Designing new protocols for Mobile Ad hoc Networks (MANETs) is a great challenge due to their distributed and self organized nature. Though, aspects of approved algorithms for hierarchical topographies may be carried over to these flat networks. The IEEE 802.11 protocol supports ad hoc networks in small scale applications, but its performance in large scale environments is still under investigation. Besides the Distributed Coordination Function (DCF), the Timer Synchronization Function (TSF) can be significantly improved in order to increase the performance in large scale multihop networks. This article presents systematic extensions to the TSF that allow increasing the overall reliability and disburdening the network at the same time. The presented scheme may be tailored to specific applications and even supports mobile stations and herewith MANETs.