Multi-hop Transmission Research Articles

Mobile routing algorithm with dynamic clustering for energy large‐scale wireless sensor networks

The clustering technique is a key routing method for large-scale wireless sensor networks (WSNs), which strongly extends the network's lifetime and scalability. The fundamental protocol of this technique, which is called low energy adaptive clustering hierarchy (LEACH), is proved as a solution that offers good energy efficiency and consequently expands the network lifetime. As the energy efficiency is deteriorated with the network size, LEACH improvements are becoming so substantial to support the scalability in the large-scale WSNs. The authors propose a new dynamic multi-hop clustering protocol. It exploits both the mobility and the multi-hop communication to prolong the lifetime of the mobile WSN. The proposed protocol, called dynamic multi-hop LEACH (DMH-LEACH), combines the dynamic clustering, multi-hop transmissions, and node mobility to improve the energy efficiency of LEACH. They also study the effect of the traffic and energy heterogeneity on the proposed protocol. Finally, they simulate DMH-LEACH protocol for both homogeneous and heterogeneous scenarios. The simulation results show that the proposed protocol allows to better balance the energy consumption for all sensor nodes and considerably extends the network's lifetime.

Energy-Efficient Data Collection for IoT Networks via Cooperative Multi-Hop UAV Networks

In this paper, we study the network of unmanned aerial vehicles (UAVs) which acts as a relay between a base station, and remotely deployed Internet of Things devices. UAVs have received much attention for connecting remotely located networks/objects, but there is a lack of study on multi-hop relay transmission schemes over UAV networks. It is particularly challenging because of the their high mobility, and limited resources, to name a few. In this regard, we propose an energy-efficient, cooperative multi-hop relay scheme for UAVs. We formulate the optimal multi-hop transmission scheduling problem to minimizes the power consumption of UAVs without violating the given time constraint. We convert the initial formulation into a low-complex iterative algorithm, making it suitable for an online scheduling. Also, we propose a buffer prediction, and correction scheme to initiate the multi-hop transmission scheduling without having the perfect buffered data information. Evaluation results show that the proposed scheme can energy-efficiently schedule the multi-hop transmissions over dynamic UAVs without violating the time constraints.

Multi-user Shared Access (MUSA) procedure for device discovery in D2D communication

In a wireless self-organizing and the network-assisted Device-to-Device (D2D) network, proximal Device Discovery (DD) plays a noteworthy role. It is the foundation for self-governing, coverage expansion and performance improvement for example, cooperative and multi-hop transmission. Energy efficiency and discovery accuracy are critical performance measures for proximal DD. A novel DD procedure using Non-orthogonal Multiple Access based Multi-user Shared Access (MUSA) is proposed in this article for network-assisted D2D communication. The proposed shared access scheme uses a complex spreading pattern to accommodate dense device discovery and enhance discovery distance in the cellular systems. A discovery signal shared access method with supplementary schemes for multi-user detection is also designed. With MUSA and its spreading pattern demodulation, 12% enhanced energy efficiency, and 98% overall improved accuracy is achieved contrasted with the customary DD methods.

Latency and Reliability of mmWave Multi-Hop V2V Communications Under Relay Selections

Timely and reliable information sharing among autonomous vehicles (AVs) provides a promising approach for reducing traffic congestion and improving traffic efficiency in future intelligent transportation systems. In this paper, we consider millimeter-wave (mmWave) based multi-hop vehicle-to-vehicle (V2V) communications to facilitate ultra-reliable low-latency information sharing among AVs. We propose a novel framework for performance analysis and design of relay selection schemes in mmWave multi-hop V2V communications, while taking into account the mmWave signal propagation characteristics, road topology, and traffic conditions. In particular, considering the minimum tracking distance requirement of road traffic, the headway, i.e., the distance between adjacent AVs, is modeled as shifted-exponential distribution. Moreover, we model the communication path losses using the Manhattan distance metric in the taxicab geometry, which can more accurately capture the characteristics of mmWave signal propagation in urban grid roads than conventional Euclidean distance geometry. Based on the proposed model, we investigate the latency and reliability of mmWave multi-hop V2V communications for three widely adopted relay selection schemes, i.e., random with forward progress (RFP), most forward with fixed radius (MFR), and nearest with forward progress (NFP), respectively. Furthermore, we propose a novel relay selection scheme for joint optimization of the single-hop forward progress (FP) and single-hop latency according to the AVs' instantaneous locations and an estimate of the residual multi-hop latency. Simulation results show that, by balancing the current single-hop latency and the residual multi-hop latency for the multi-hop V2V network, the proposed relay selection scheme significantly outperforms the MFR, NFP and RFP in both multi-hop transmission latency and reliability of mmWave V2V communications.

Bioinspired Cooperative Wireless Energy Transfer for Lifetime Maximization in Multihop Networks

To extend the lifetime of a multihop network by addressing energy shortages in wireless nodes, we apply wireless energy transfer (WET) technology to the multihop transmission. Considering a linear multihop topology, we establish a system model for a WET-enabled multihop transmission and formulate an optimization problem that obtains the optimal WET time of each node to maximize the lifetime of multihop networks. To solve this problem, we adopt a flocking model inspired by the similarity between flocking behaviors and WET-enabled multihop transmissions. Applying the underlying principles of the flocking model, we propose a bioinspired cooperative WET (BiCoWET) algorithm, in which each node adjusts its own WET time to equalize the lifetime of all nodes in a distributed manner. Theoretical analysis verifies that the proposed BiCoWET algorithm achieves optimality with exponential convergence. The intensive simulation shows that the proposed BiCoWET outperforms the conventional multihop transmission methods without WET and maximizes the network lifetime by equalizing the lifetime of all nodes.

Power-Efficient Trajectory Adjustment and Temporal Routing for Multi-UAV Networks

This work proposes power-efficient trajectory adjustment and temporal routing algorithms for a network of fixed-wing unmanned aerial vehicles (UAV) deployed to gather data from underlying sensors in the field. To stay afloat, each UAV follows a circular trajectory above its responsible service area with a radius that can be adjusted to reduce its propulsion energy consumption. The data gathered by the UAVs are sent to the data-gathering node using multihop transmissions over other circulating UAVs. First, given the multihop transmission paths from all UAVs to the data-gathering node, power-efficient flight-radius adjustment strategies are proposed based on the total power minimization and lifetime maximization criteria while maintaining connectivity over the multihop paths. Then, by establishing the relationship between routing in UAV networks and that in general temporal graphs, we propose a power-efficient (PE) temporal path algorithm based on the minimization of the total pair-wise flight power consumption among consecutive UAVs on the path. Finally, we propose an iterative procedure to refine the initial phases of the UAVs’ circular trajectories to further improve the power efficiency. Computer simulations are provided to demonstrate the effectiveness of the proposed schemes in terms of both total power minimization and lifetime maximization.

Area double cluster head APTEEN routing protocol-based particle swarm optimization for wireless sensor networks

APTEEN is a typical routing protocol for wireless sensor networks, but when clustering, cluster heads are randomly selected, which makes it easy to select nodes with low residual energy as cluster heads, thus forming network holes. At the same time, in multi hop transmission, the cluster head near the sink node is overloaded due to forwarding a large amount of data. Aiming at these problems, this paper introduces PSO algorithm and proposes ADCH-EPE-APTEEN routing protocol. In order to make the particle swarm optimization algorithm more suitable for routing protocol, this paper first proposes DCA-PSO based on particle swarm optimization algorithm. DCA-PSO uses the classification adaptive change inertia weight for different states of particles in the optimization process. At the same time, dynamic learning factor is used to improve the influence of particle experience and other particle experience on convergence speed and to improve the optimization accuracy and speed of the algorithm. Secondly, when APTEEN routing protocol is networked, the cluster head is selected by DCA-PSO, in which the residual energy of nodes, the location of nodes, and the energy distribution around nodes are fully taken into consideration. Thirdly, considering the distance between nodes and the sink node, the residual energy and the energy distribution around nodes, a front area is set up in the cluster located in the upper half and the assistant cluster head is selected in the front area through the DCA-PSO algorithm. The simulation results show that the DCA-PSO algorithm can significantly improve the search speed and precision compared with the PSO algorithm. Compared with APTEEN routing protocol, the ADCH-EPE-APTEEN routing protocol can reduce the network energy consumption rate and extend network lifetime by 173%.

A Novel Relay Selection Scheme Based on Q-Learning in Multi-Hop Wireless Networks

In wireless communication systems, reliability, low latency and power are essential in large scale multi-hop environment. Multi-hop based cooperative communication is an efficient way to achieve goals of wireless networks. This paper proposes a relay selection scheme for reliable transmission by selecting an optimal relay. The proposed scheme uses a signal-to-noise ratio (SNR) based Q-learning relay selection scheme to select an optimal relay in multi-hop transmission. Q-learning consists of an agent, environment, state, action and reward. When the learning is converged, the agent learns the optimal policy which is a rule of the actions that maximize the reward. In other words, the base station (BS) knows the optimal relay to select and transmit the signal. At this time, the cooperative communication scheme used in this paper is a decode-and-forward (DF) scheme in orthogonal frequency division multiplexing (OFDM) system. The Q-learning in the proposed scheme defines an environment to maximize a reward which is defined as SNR. After the learning process, the proposed scheme finds an optimal policy. Furthermore, this paper defines a reward which is based on the SNR. The simulation results show that the proposed scheme has the same bit error rate (BER) performance as the conventional relay selection scheme. However, this paper proposes an advantage of selecting fewer relays than conventional scheme when the target BER is satisfied. This can reduce the latency and the waste of resources. Therefore, the performance of the multi-hop transmission in wireless networks is enhanced.

Traffic Differentiated Clustering Routing in DSRC and C-V2X Hybrid Vehicular Networks

Vehicles equipped with sensors can participate in mobile crowdsourcing applications. Vehicular Ad Hoc Networks (VANETs) based on Dedicated Short Range Communication (DSRC) are used to carry sensing data. However, multi-hop transmissions for gathering data to Road Side Units (RSUs) in VANETs suffer from low data rate and long end-to-end delay, which can hardly meet the QoS requirements of delay-sensitive services. This triggers the consideration of constituting a DSRC and Cellular-Vehicle-to-Everything (C-V2X) hybrid vehicular network. Nevertheless, using cellular links to carry traffic can cause high cellular bandwidth costs. In this paper, we propose a Traffic Differentiated Clustering Routing (TDCR) mechanism in a Software Defined Network (SDN)-enabled hybrid vehicular network. The proposed mechanism includes a centralized one-hop clustering approach and a data delivery optimization method. Particularly, the optimization is to make a tradeoff between cellular bandwidth cost and end-to-end delay, for Cluster Heads (CHs) delivering their aggregated data either by multi-hop Vehicle-to-Vehicle (V2V) transmissions or by cellular networks. Since the problem is proven to be NP-hard, a two-stage heuristic algorithm is designed. We carry out simulations to evaluate the performance of our data collection scheme and the results show that it performs better than traditional mechanisms.

Krill herd based TSP approach for mobile sink path optimization in large scale wireless sensor networks

In wireless sensor networks (WSN), the establishment of large-scale sensor networks has always needed attention. One of the many challenges is to set up an architecture that is different from the rest and find mechanisms that can efficiently scale up with the growing number of nodes that may be ess ential to ensure sufficient coverage of large areas under study. Concurrently, these new architectures and mechanisms are supposed to maintain low power consumption per node to comply with energy guaranty acceptable network lifetime. The researchers utilized numerous Data collection techniques for the prompt data aggregation, yet still those outcomes the node with path failures. To solve this issue, the mobile sink is being extensively used for data aggregation in large scale wireless sensor networks (WSNs). This technique avoids imbalances in energy consumption due to multi-hop transmission but might lead to extended delay time. In this paper, our focus is on shortening the length of the mobile sink’s travelling path to reduce the delay time during data gathering in large scale WSN. To achieve this, the mobile sink visits the cluster heads in an optimized path instead of sensors one by one. Here Hierarchical clusters are efficiently formed by modified K- means with outlier elimination and node proximity and residual energy based second level clustering algorithm. Next, we determine the optimal path for the mobile sink by formulating KH based Travelling Salesman Problem solving optimization algorithm. This technique proposed reduces not only the length of the path travelled by the mobile sink but also lessens the computational effort that is required for travelling-path planning and enhances the lifetime of nodes. And to ensure aggregation accuracy in cluster heads iterative filtering is implemented. Our experimental results show the proposed algorithm shortens the tour length by 40–60 percent compared to Bacterial foraging optimization-based TSP algorithm. Also delivers better results compared to other’s in terms of the computational effort, time, energy use, and enhances the network lifetime.

An urban expressway forwarding scheme for cognitive Internet of vehicles

The Internet of vehicles is an essential component for building smart cities that can improve traffic safety and provide multimedia entertainment services. The cognitive radio–enabled Internet of vehicles was proposed to resolve the conflict between the increasing demand of Internet of vehicles applications and the limited spectrum resources. The multi-hop transmission is one of the most important issues in cognitive radio–enabled Internet of vehicles networks. Nevertheless, most existing forwarding solutions designed for the cognitive radio–enabled Internet of vehicles did not consider the urban expressway scenario, where primary base stations are densely installed with small coverage areas. In this case, it is difficult to ensure that the sender and the receiver of the same cognitive radio link have similar channel availability statistics, which makes cognitive radio links more likely to be interrupted. To address this challenge, we develop a multi-hop forwarding scheme to minimize the end-to-end delay for such networks. We first formulate the delay minimization problem as a non-linear integer optimization problem. Then, we propose an approach to select the relay candidates by jointly considering the high mobility of vehicles and the unique cognitive radio spectrum usage distributions in urban expressway scenarios. Finally, we propose the low-latency forwarding strategies by considering the channel availability and the delay cost of different situations of relay candidates. Simulations show the advantages of our proposed scheme, compared with state-of-art methods.

E‐TDGO: An encrypted trust‐based dolphin glowworm optimization for secure routing in mobile ad hoc network

SummaryMobile ad hoc networks (MANETs) are independent networks, where mobile nodes communicate with other nodes through wireless links by multihop transmission. Security is still an issue to be fixed in MANETs. Hence, a routing protocol named encrypted trust‐based dolphin glowworm optimization (DGO) (E‐TDGO) is designed using Advanced Encryption Standard‐128 (AES‐128) and trust‐based optimization model for secure routing in MANET. The proposed E‐TDGO protocol includes three phases, namely, k‐path discovery, optimal path selection, and communication. At first, k paths are discovered based on the distance and the trust level of the nodes. From the k paths discovered, the optimal path is selected using a novel algorithm, DGO, which is developed by combining glowworm swarm optimization (GSO) algorithm and dolphin echolocation algorithm (DEA). Once the optimal path is selected, communication begins in the network such that E‐TDGO protocol ensures security. The routing messages are encrypted using AES‐128 with shared code and key to offer security. The experimental results show that the proposed E‐TDGO could attain throughput of 0.11, delay of 0.01 second, packet drop of 0.44, and detection rate of 0.99, at the maximum number of rounds considered in the network of 75 nodes with attack consideration.

Novel fountain data estimation scheme by exploiting Bayesian model classification in wireless sensor networks

The crucial goal of fountain codes is to reduce the use of a feedback channel. Their roll-out is limited by multi-hops transmission. With the multi-hops transmission, fountain codes raise the problem of overflow engendering a waste of energy. The number of encoded packets generated is significantly reduced and the residual energy can be preserved with a clustered architecture and classification technique. In this paper, we consider a distributed estimation scheme comprising a sensor member and a fusion centre. To reduce the number of useless encoded packets and the number of transmissions, we determine the number of encoded packets to recover data. We adopt fountain codes for data encoding. Then, packets are assembled at the Cluster Head (CH). Each CH provides a final estimation using a classification. We prove the power of fountain codes and training machine learning models to exactly calculate the estimate and to preserve residual energy.

Novel fountain data estimation scheme by exploiting Bayesian model classification in wireless sensor networks

The crucial goal of fountain codes is to reduce the use of a feedback channel. Their roll-out is limited by multi-hops transmission. With the multi-hops transmission, fountain codes raise the problem of overflow engendering a waste of energy. The number of encoded packets generated is significantly reduced and the residual energy can be preserved with a clustered architecture and classification technique. In this paper, we consider a distributed estimation scheme comprising a sensor member and a fusion centre. To reduce the number of useless encoded packets and the number of transmissions, we determine the number of encoded packets to recover data. We adopt fountain codes for data encoding. Then, packets are assembled at the Cluster Head (CH). Each CH provides a final estimation using a classification. We prove the power of fountain codes and training machine learning models to exactly calculate the estimate and to preserve residual energy.

Node Energy Consumption Balanced Multi-Hop Transmission for Underwater Acoustic Sensor Networks Based on Clustering Algorithm

With the advancement and implementation of marine strategies in various countries, it is of great significance to collect marine data by using underwater acoustic sensor networks (UWA-SNs). Due to the difficulties in charging or replacing batteries, how to prolong the lifetime of underwater sensor nodes is one of the key problems to be solved. In this paper, we propose a new energy consumption balanced protocol, named as dynamic clustering K-means (DC-K-means) based simplified balanced energy adaptive routing (S-BEAR), to prolong the lifetime of a UWA-SN by balancing the energy consumption of underwater sensor nodes and avoiding the energy hole. First, by considering the residual energy of the underwater sensor nodes, we propose the DC-K-means algorithm to cluster the underwater sensor nodes and optimize the topology of data transmission among underwater sensor nodes so that the overall energy consumption of the system can be reduced and the problem of energy consumption balance of underwater sensor nodes can be solved. Then, the S-BEAR protocol is designed for multi-hop transmissions, where the data collected by each cluster head is transmitted to the surface receiving terminal equipment, and thus further balances and saves the energy consumption of the system. The simulation results demonstrate that the proposed DC-K-means based S-BEAR scheme has the advantages of more balanced energy consumption among sensor nodes and higher overall residual energy as compared to the state-of-the-art schemes.

Energy Efficiency in Multihop Wireless Networks with Unreliable Links

Due to the increasing number of wireless devices, the issue of energy efficiency that requires high data rate with reliability has spawned tremendous research interests in recent years. In wireless networks, major problem that needs to be addressed is that multihop transmission, though requiring lower transmit power, incurs more circuit energy consumption than that of single-hop transmission and leads to more bit errors. Thus we are motivated to study the energy efficiency of multihop wireless networks with unreliable links, where such a problem is even more serious. Specifically, with a flat Rayleigh fading channel, our network model jointly considers the transmit energy and circuit energy, and characterizes the unreliability caused by the wireless nature with the assumption of probabilistic links. Based on that, we formulate our problems of energy consumption normalized by the source-destination (S-D) path loss, and derive the optimal set of signal-to-noise ratios in each hop to minimize the normalized energy consumption. In addition, our theoretical results exhibit a clear relation between the normalized energy consumption and the delay constraint, and meanwhile disclose the crucial impact that the circuit energy has on the monotonicity of the normalized energy consumption. More specifically, we find that the normalized total energy consumption with the delay constraint decreases as the number of hops increases when the number of hops is small, and increases as the number of hops increases when it is large. Extensive simulations confirm the theoretical results. Our findings shed light on the design, implementation, and operation of real-world energy-efficient multihop wireless networks.

The Method of Data Collection Based on Multiple Mobile Nodes for Wireless Sensor Network

In traditional wireless sensor networks (WSN), data is transmitted to base stations through multiple-hop. However, multi-hop transmission will cause problems such as energy holes, uneven energy consumption, and unreliable data transmission. Aiming at the defects of traditional networks, this paper proposes a scheme for collaborative data collection using multiple mobile nodes (MN) as sink nodes. In this scenario, an important issue is how to reasonably plan the data collection path of each mobile node under a series of constraints such as energy. This paper studies routing strategy and path planning. Firstly, a dynamic clustering algorithm is used to cluster the randomly arranged sensor nodes, and then a sensor node with higher energy is manually arranged at the virtual cluster center generated by the clustering algorithm as a cluster head node to establish a data collection cluster. Then the monitoring area is divided into several parts according to the number of MN, so that the MN traverses the cluster head nodes in the respective monitoring areas for data collection. At the same time, in order to enable the MN to complete data collection within the energy limit and improve the path balance, a path-based path equalization algorithm (PEABR) is proposed to adjust the path of the MN, further reduce and equalize the path length of the MN to satisfy the constraint conditions, and optimize the path planning scheme. Finally, simulation was carried out by using Matlab simulator, and the simulation experiments which were performed in a laboratory environment verified the feasibility and effectiveness of the algorithm.

An adaptive and cooperative MAC protocol in vehicular ad hoc network: design and performance analysis

Vehicular ad hoc network is the key technology to enable the intelligent transportation system. VANET should provide reliable broadcasting to support the safety-related application. It is also required to effectively transmit service-related data. With the rapid development of the internet of vehicles, medium access control (MAC) protocols for VANET are expected to be more adaptive and scalable to the network size; so that the MAC protocol can operate effectively in supporting the massive number of connections. This paper proposes a multi-channel MAC protocol, namely AC-MAC, that enables multi-hop transmission of safety application data leveraging cooperation among vehicles. The proposed MAC protocol ensures the reliability of safety message transmission and the effective utilisation of channel resources. Moreover, the MAC mechanism also has the ability to adapt to different network conditions.

An adaptive and cooperative MAC protocol in vehicular ad hoc network: design and performance analysis

Vehicular ad hoc network is the key technology to enable the intelligent transportation system. VANET should provide reliable broadcasting to support the safety-related application. It is also required to effectively transmit service-related data. With the rapid development of the internet of vehicles, medium access control (MAC) protocols for VANET are expected to be more adaptive and scalable to the network size; so that the MAC protocol can operate effectively in supporting the massive number of connections. This paper proposes a multi-channel MAC protocol, namely AC-MAC, that enables multi-hop transmission of safety application data leveraging cooperation among vehicles. The proposed MAC protocol ensures the reliability of safety message transmission and the effective utilisation of channel resources. Moreover, the MAC mechanism also has the ability to adapt to different network conditions.

Self-Forming Multiple Sub-Nets Based Protocol for Tactical Networks Consisting of SDRs

The paper presents a novel approach for tactical networks in which radios form self-regulatory virtual sub-nets on the basis of control messages. The design uses hybrid of frequency division multiple access (FDMA) and time division multiple access (TDMA) approaches with less call setup delays and increases in network throughput. This multiple sub-nets based distributed algorithm exploits available spectrum resources, provides collision-free simultaneous transmissions and autonomous selection of time slots over different frequency sub-bands with self-organizing and self-forming network capabilities. We propose two schemes which provide multi-channel medium access control with autonomous scheduling of time slots for software-defined radios (SDRs). The schemes use request and acknowledgment frames as control messages to devise a distributed solution. These control messages alone help to form virtual sub-nets, preserve frequency channels and schedule transmissions over multiple time slot intervals, depend on the type of data messages. In order to demonstrate the behavior of sub-nets for tactical networks, theoretical findings are exploited with experimental analysis to provide practical implementation of schemes using contention-free time slotted common control channel for nodes coordination and time slotted collision-free multi-channel environment for data transmissions. The results show the effective coexistence of multiple transmissions in a network with increase in network throughput and lower the data latency up-to 76.8%, when compare to conventional MAC protocols. The design is workable for time sensitive, mission critical networks and expected to support multi-hop transmissions in similar manner.