Multi-hop Routing Scheme Research Articles

DRAMS: Double-RIS assisted multihop routing scheme for device-to-device communication

Reconfigurable intelligent surfaces (RISs) is a promising solution for enhancing the performance of multihop wireless communication networks. In this paper, we propose a double-RIS assisted multihop routing scheme for a device-to-device (D2D) communication network. Specifically, the scheme is dependent on the already deployed RISs and users in the surroundings. Besides the RISs, the emphasis of this work is to make more use of the existing intermediate users (IUs), which can act as relays. Hence, the density of RIS deployment in the surroundings can be reduced, which leads to the avoidance of resource wastage. However, we cannot solely depend on the IUs because this implies complete dependence on their availability for relaying and as a result, the aspect of reliability in terms of delay-constrained information transfer cannot be guaranteed. Moreover, the IUs are considered capable of energy harvesting and as a result, they do not waste their own energy in the process of volunteering to act as a relay for other users. Numerical results demonstrate the advantage of the proposed scheme over some existing approaches and lastly, useful insights related to the scheme design are also drawn, where we characterize the maximum acceptable delay at each hop under different set-ups.

Energy Efficient Cluster based Routing Scheme for WSN based IoT to Extend Network Lifetime

With the development and advancement of wireless sensor networks (WSN), the emergence of the Internet of Things (IoT) has achieved prominence in the modern era. With the increasing number of connected devices, WSN has become a key factor in the communication component of the IoT. In IoT-based WSN infrastructure, devices are equipped with intelligent sensors that sense the environment to collect data, process data, and deliver information to the sink or base station (BS). WSN-assisted IoT has become a key technology for various data-centric applications such as health care, smart cities, and the military. Sensor nodes in IoT devices are equipped with bound and irreplaceable batteries. An increased number of connected devices face serious issues of energy depletion, maintenance, and load balancing, which might result in device failure. Energy efficiency is considered a vital parameter in the design of an IoT based WSN, and this can be accomplished through clustering and multihop routing techniques. In this paper, we propose an energy-aware multihop routing scheme (EAMRS) for hierarchical cluster-based WSN-assisted IoT. EAMRS considers the improved low-energy adaptive clustering algorithm (I-LEACH) to select optimal cluster heads (CH). During data transmission, multihop routing is involved by considering routing metrics such as residual energy, distance to BS and optimal route choice to balance the energy load. However, conventional routing schemes fail to achieve the flexibility and adaptability prerequisites of load balancing mechanisms. EAMRS decreases computation overhead and restricts energy usage, resulting in a prolonged network lifetime.

Energy Efficient Multi-hop routing scheme using Taylor based Gravitational Search Algorithm in Wireless Sensor Networks

A group of small sensors can participate in the wireless network infrastructure and make appropriate transmission and communication sensor networks. There are numerous uses for drones, including military, medical, agricultural, and atmospheric monitoring. The power sources available to nodes in WSNs are restricted. Furthermore, because of this, a diverse method of energy availability is required, primarily for communication over a vast distance, for which Multi-Hop (MH) systems are used. Obtaining the optimum routing path between nodes is still a significant problem, even when multi-hop systems reduce the cost of energy needed by every node along the way. As a result, the number of transmissions must be kept to a minimum to provide effective routing and extend the system's lifetime. To solve the energy problem in WSN, Taylor based Gravitational Search Algorithm (TBGSA) is proposed, which combines the Taylor series with a Gravitational search algorithm to discover the best hops for multi-hop routing. Initially, the sensor nodes are categorised as groups or clusters and the maximum capable node can access the cluster head the next action is switching between multiple nodes via a multi-hop manner. Initially, the best (CH) Cluster Head is chosen using the Artificial Bee Colony (ABC) algorithm, and then the data is transmitted utilizing multi-hop routing. The comparison result shows out the extension of networks longevity of the proposed method with the existing EBMRS, MOGA, and DMEERP methods. The network lifetime of the proposed method increased by 13.2%, 21.9% and 29.2% better than DMEERP, MOGA, and EBMRS respectively.

Metaheuristic Optimization Based Node Localization and Multihop Routing Scheme with Mobile Sink for Wireless Sensor Networks

Metaheuristic Optimization Based Node Localization and Multihop Routing Scheme with Mobile Sink for Wireless Sensor Networks

Dynamic Multihop Routing in Terahertz Flow-Guided Nanosensor Networks: A Reinforcement Learning Approach

The Internet of Nano-Things (IoNT) is an emerging paradigm in which devices sized to the nanoscale (nanonodes) and transmitting in the terahertz (THz) band can become decisive actors in future medical applications. Flow-guided nanonetworks are well-known THz networks aimed at deploying the IoNT inside the human body, among other issues. In these networks, nanonodes flowing through the bloodstream monitor-sensitive biological/physical parameters and dispatch these data via electromagnetic (EM) waves to a nanorouter implanted in human tissue, which operates as a gateway to external Internet connectivity devices. Under these premises, two shortcomings arise. First, the use of the THz band greatly limits the nanonode’s communication range. Second, the nanonodes lack resources for processing, memory, and batteries. To minimize the impact of these concerns in EM nanocommunications, a novel dynamic multihop routing scheme is proposed to model in-body, flow-guided nanonetwork architecture. To this end, a reinforcement learning-based framework is conceived, combining the features of EM nanocommunications and hemodynamics or fluid dynamics applied to the bloodstream. A generic Markov decision process (MDP) approach is derived to maximize the throughput metric, analytically modeling: 1) the movement of the nanonodes in the bloodstream as laminar flow; 2) energy consumption (including energy-harvesting issues); and 3) prioritized events. A thoroughly THz flow-guided nanonetwork case of study is also defined. Under the umbrella of this case, diverse testbeds are planned to create a procedure of evaluation, validation, and discussion. Results reveal that multihop scenarios obtain better performance than direct nanonode-nanorouter communication, specifically, the two-hop scenario, which, for instance, quadrupled the throughput in a hand vein without sharply penalizing other aspects such as energy consumption.

Dwarf Mongoose Optimization-Based Secure Clustering with Routing Technique in Internet of Drones

Over the last few years, unmanned aerial vehicles (UAV), also called drones, have attracted considerable interest in the academic field and exploration in the research field of wireless sensor networks (WSN). Furthermore, the application of drones aided operations related to the agriculture industry, smart Internet of things (IoT), and military support. Now, the usage of drone-based IoT, also called Internet of drones (IoD), and their techniques and design challenges are being investigated by researchers globally. Clustering and routing aid to maximize the throughput, reducing routing, and overhead, and making the network more scalable. Since the cluster network used in a UAV adopts an open transmission method, it exposes a large surface to adversaries that pose considerable network security problems to drone technology. This study develops a new dwarf mongoose optimization-based secure clustering with a multi-hop routing scheme (DMOSC-MHRS) in the IoD environment. The goal of the DMOSC-MHRS technique involves the selection of cluster heads (CH) and optimal routes to a destination. In the presented DMOSC-MHRS technique, a new DMOSC technique is utilized to choose CHs and create clusters. A fitness function involving trust as a major factor is included to accomplish security. Besides, the DMOSC-MHRS technique designs a wild horse optimization-based multi-hop routing (WHOMHR) scheme for the optimal route selection process. To demonstrate the enhanced performance of the DMOSC-MHRS model, a comprehensive experimental assessment is made. An extensive comparison study demonstrates the better performance of the DMOSC-MHRS model over other approaches.

LEMH: Low-Energy-First Electoral Multipath Alternating Multihop Routing Algorithm for Wireless Sensor Networks

Lifetime is a vital performance metric for wireless sensor networks (WSNs), with current hierarchical routing protocols suffering from the premature death of overloaded nodes, affecting the network’s lifetime. Spurred by this problem, we propose a low-energy first electoral multipath alternating multihop (LEMH) routing scheme. To avoid overloading the nodes, these are given a contention radius that adaptively changes with the topology and affords the nodes to combine the remaining energy to vote for those participating in the cluster heads election process. Then, the running nodes decide the final cluster head based on two-dimensional competition parameters. Finally, the traditional multihop communication shortcomings are addressed by formulating an energy balance lifetime maximization routing problem based on sequential quadratic programming (SQP) under alternating multihop. This problem is optimally solved using particle swarm optimization (PSO), providing an improved multihop transmission scheme for WSNs. The simulation results demonstrate that LEMH effectively extends the network’s survival time and improves performance.

A dual-hop topology-aware routing protocol for underwater optical wireless sensor networks

Underwater optical wireless communication (UOWC) is an emerging technology for underwater wireless sensor networks (UWSNs). Compared with acoustic waves and radio frequency waves, optical waves can provide higher data rates and lower latency. However, given the limited transmission range and energy supply, as well as the existence of communication void regions in UOWC which may further deteriorate its transmission performances (e.g. packet deliver rate), effective multi-hop routing schemes are highly desirable for UOWC to expand its transmission range with satisfactory performance. In this paper, we propose a dual-hop topology-aware (DHTA) routing algorithm for UOWC. By adopting dual-hop routing strategy, the proposed algorithm reduces the packet entry possibility into void regions, and thus improves the packet deliver rate. And by selecting the next relay node considering both the available distance of transmission and the deviation of transmission direction, the proposed algorithm can effectively reduce the average energy consumption of the network. Besides, a threshold is employed by the proposed algorithm for energy balance to prevent excessive energy consumption of some nodes. The simulation results verify that the proposed DHTA routing algorithm effectively alleviates the effluence of void regions on forwarding packet and increases the packet delivery rate (PDR), with reduced average energy consumption and energy standard deviation.

A Study on Multi-Hop Routing Scheme for Wireless Sensor Networks

Wireless sensor networks (WSN) play an important role in IoT (Internet of Things) as an interconnecting infrastructure. Working with a limited energy source, the vital challenge for WSN is to prolong the network lifetime as an important performance metric. Furthermore, the limitations of regular transmission technologies create localized network areas of a multi-hop fashion form that adds more constraints to enhance the network performance. Hence, the clustering strategies initially have solved these problems and received the attention of many studies, an approach using unequal clustering strategy has yielded some positive results since consumed energy gaps are avoided in regions near base stations. However, the routing strategy among cluster heads in multi-hop wireless networks is still a big challenge because of its inefficiency in energy consumption aspects. Therefore, in this paper, we propose a novel method that combining an unequal clustering problem and a simple multi-hop routing to prolong network life. The numerical results show that the proposed solution is more effective than other models in recent studies

Spatial Correlation Based Clustering with Node Energy Based Multi-Hop Routing Scheme for Wireless Sensor Networks

Major points of concern in implementing a wireless sensor network (WSN) are the network lifetime and energy utility within any delay tolerant network. Both these parameters define the success of the sensor network. The higher the expectancy of network Lifetime, the higher is the probability of acceptance of the network. Similarly, better the energy utilization in the network, better are the chances of success and implementation of the sensor network. Clustering is one such scheme adopted in WSN towards harnessing the best of above specified parameters for the network implemented. Most popular clustering techniques are the variants of LEACH protocol that facilitate cluster formation based on the proximity of an individual node to other nodes in the sensor network. These protocols are based on a single hop structure from the selected cluster heads in the network. This paper embarks on a multi-hop clustering algorithm that takes into consideration the spatial correlation between the nodes to form clusters and implements a highly energy efficient routing scheme which selects the multi-hop path in the network in a dynamic fashion.

A novel energy-efficient balanced multi-hop routing scheme (EBMRS) for wireless sensor networks

Wireless Sensor Network has been recognized as an attractive candidate among the telecommunication, meteorology, and sensor industries for the last few years owing to its wide range of applications, including environmental- and industrial-monitoring. In this paper, the authors propose an Energy Balanced Multi-hop Routing Scheme (EBMRS) at both the inter- and intra-clustering level to discover the optimal route to the Base Station (BS) for maximizing energy efficiency. It selects the required number of sensor nodes as Cluster-Heads (CHs) based on their Probability of Selection (PS) metrics like the residual energy, the number of hop-counts, and the distance to the BS. Inside inter-cluster communication, each sensor node decreases their energy consumption by using nearest intermediate sensor node to communicate with the CH. During intra-cluster communication, CHs adopt multi-hop approach to transmit the aggregated data to the BS by finding a suitable CH that locates on the way to the BS. Moreover, to avoid unbalance cluster-formation, EBMRS ensure that the CHs locate at a minimum distance from each other. The outcomes report an improvement of a minimum of 40% in the network’s lifetime of the demonstrated WSN network employed with the proposed EBMRS strategy in distinction with the existing energy-efficient routing approaches.

Scaling Performance Analysis and Optimization Based on the Node Spatial Distribution in Mobile Content‐Centric Networks

Content‐centric networks (CCNs) have become a promising technology for relieving the increasing wireless traffic demands. In this paper, we explore the scaling performance of mobile content‐centric networks based on the nonuniform spatial distribution of nodes, where each node moves around its own home point and requests the desired content according to a Zipf distribution. We assume each mobile node is equipped with a finite local cache, which is applied to cache contents following a static cache allocation scheme. According to the nonuniform spatial distribution of cache‐enabled nodes, we introduce two kinds of clustered models, i.e., the clustered grid model and the clustered random model. In each clustered model, we analyze throughput and delay performance when the number of nodes goes infinity by means of the proposed cell‐partition scheduling scheme and the distributed multihop routing scheme. We show that the node mobility degree and the clustering behavior play the fundamental roles in the aforementioned asymptotic performance. Finally, we study the optimal cache allocation problem in the two kinds of clustered models. Our findings provide a guidance for developing the optimal caching scheme. We further perform the numerical simulations to validate the theoretical scaling laws.

PageRank-Based Multi-Hop Computation Offloading in D2D Networks

In a D2D network, the tasks of a user device (UD) can be offloaded to other UDs to improve the UD’s performance. We propose a novel computation offloading scheme to efficiently alleviate the delay of task processing and the energy consumption of UDs. Inspired by PageRank algorithm, the strategies of computation offloading for UDs are determined by their steady ranking values, which reflect the overall influence of UDs’ performance in the network. Firstly, we model the network as a directed weighted graph, where the weight of each vertex is obtained by integrating the computing ability, battery energy, and available storage capacity of the corresponding UD, and the weight of each directed edge is obtained by integrating the data rates and potential interference of the D2D connection between the corresponding two UDs. Secondly, a power iteration algorithm, which satisfies Markov convergence, is designed to compute the steady ranking values of UDs. Finally, we design an algorithm to obtain one-hop strategies and multi-hop routing strategies for computation offloading among UDs. The superiority of our scheme is demonstrated in simulations and by comparisons.

Trust-aware energy-efficient stable clustering approach using fuzzy type-2 Cuckoo search optimization algorithm for wireless sensor networks

With the advancement of communication and sensor technologies, it has become possible to develop low-cost circuitry to sense and transmit the state of surroundings. Wireless networks of such circuitry, namely wireless sensor networks (WSNs), can be used in a multitude of applications like healthcare, intelligent sectors, environmental sensing, and military defense. The crucial problem of WSN is the reliable exchange of data between different sensors and efficient communication with the data collection center. Clustering is the most appropriate approach to prolong the performance parameters of WSN. To overcome the limitations in clustering algorithms such as reduced cluster head (CH) lifetime; an effective CH selection algorithm, optimized routing protocol, and trust management are required to design an effective WSN solution. In this paper, a Cuckoo search optimization algorithm using a fuzzy type-2 logic-based clustering strategy is suggested to extend the level of confidence and hence network lifespan. In intra-cluster communication, a threshold-based data transmission algorithm is used and a multi-hop routing scheme for inter-cluster communication is employed to decrease dissipated energy from CHs far away from BS. Simulation outcomes indicate that the proposed strategy outperforms other communication techniques in the context of the successful elimination of malicious nodes along with energy consumption, stability period, and network lifetime.

Two-Level Clustering and Routing Algorithms to Prolong the Lifetime of Wind Farm-Based WSN

In recent years, wind power is emerging as one of the most promising renewable energy sources. Yet, reliability is less due to the unplanned downtimes caused by faults in the wind turbines. Monitoring of turbine elements with existing wired technology is not economical and hence replacement with smart wireless sensor devices are rapidly emerging as the next evolution. In such a wireless scenario, maximizing network lifetime and reliability is essential. The recently proposed hybrid multihop routing protocol aims to improve the lifetime of a WSN deployed in a widely distributed network. Though its performance is revealed to be better, the chain based CH selection and routing of data through MST increases the energy consumption thereby reducing the network lifetime. With an objective to circumvent this, three novel multihop routing strategies namely, Shortest Grid Routing, Partitioned Super Grid Direct Routing, and Shortest Super Grid Routing are proposed. For different network scenarios, the proposals are analyzed through simulation and validated via real time experimentation. The performance of the proposals is evaluated using metrics such as first node death, energy consumption, stability, and network reliability and are compared with the recently proposed protocol. The results reveal enhanced network lifetime and reliability which proves the applicability of the proposed routing protocols for CPS based infrastructure network.

A Novel Energy-Efficient Routing Scheme for LoRa Networks

Although being simple and currently adopted for LoRaWAN, single-hop routing (i.e., direct transmission from end devices to the gateway) is not necessarily optimal in terms of minimizing the total energy consumption of the network. This paper extends Distance Ring Exponential Generator (DRESG) framework and presents a multi-hop routing scheme in the context of low-power wide-area networks (LPWANs) based on LoRa transmission technology. An evaluation framework is developed to analyze and compare different routing mechanisms that takes into account important factors such as the type of nodes in the network and node distribution. Considered are direct-hop (DH) routing, next-ring-hop (NRH) routing and variable-hop (VH) routing. Analysis and simulations results confirm that better performance in terms of energy efficiency is achieved with multi-hop routing model over single-hop routing. In particular, while maintaining a high level of network connectivity, VH routing outperforms DH routing by minimizing energy consumption of critical nodes. The gain in terms of energy saving or enhancing network lifetime becomes more significant with payload aggregation.

Physiological Monitoring by Fail Proof Lifetime Enhancement Algorithm for Smart Digital Environments

Physiological signals monitoring in smart digital environment became ease with miniaturized embedded systems. The node loses its energy due to continuous monitoring and becomes unavailable during critical conditions. The implanted node dissipated heat and causes tissue damage when overloaded. The problem is addressed through Fail Proof Lifetime Enhancement (FPLE) Algorithm by optimally scheduling the nodes in digital environment based on the energy level and through Threshold T* policy model proposed. The objective is achieved by classifying packets based on their status and packets are transmitted towards sink once it meets a threshold value T*. A part of the energy in the sensor node is utilized during emergencies to ensure the availability of monitoring the subject during critical conditions. The subject status is realized as a Finite State Machine and evaluated through the Markov model and threshold T* based framework is adopted to enhance the lifetime of the network. The FPLE algorithm performs better than the SingleHop, MultiHop and ATTEMPT routing scheme in terms of network lifetime and throughput. The proposed FPLE algorithm provides 1.91 times lifetime and 1.1 times throughput when compared with the ATTEMPT communication protocol. The false data generation is identified and alarmed through this approach, and the FPLE algorithm also ensures monitoring during critical conditions. The implanted node is loaded least to avoid thermal dissipation and tissue damage of the subject. The FPLE algorithm is tested in real-time digital environment for its novel working, provides better results when compared to ATTEMPT, SingleHop, and MultiHop protocol.

A Modular IoT Hardware Platform for Distributed and Secured Extreme Edge Computing

The hardware of networked embedded sensor nodes is in continuous evolution, from those 8-bit MCUs-based platforms such as Mica, up to powerful Edge nodes that even include custom hardware devices, such as FPGAs in the Cookies platform. This evolution process comes up with issues related to the deployment of the Internet of Things, particularly in terms of performance and communication bottlenecks. Moreover, the associated integration process from the Edge up to the Cloud layer opens new security concerns that are key to assure the end-to-end trustability and interoperability. This work tackles these questions by proposing a novel embedded Edge platform based on an EFR32 SoC from Silicon Labs with Contiki-NG OS that includes an ARM Cortex M4 MCU and an IEEE 802.15.4 transceiver, used for resource-constrained low-power communication capabilities. This IoT Edge node integrates security by hardware, adding support for confidentiality, integrity and availability, making this Edge node ultra-secure for most of the common attacks in wireless sensor networks. Part of this security relies on an energy-efficient hardware accelerator that handles identity authentication, session key creation and management. Furthermore, the modular hardware platform aims at providing reliability and robustness in low-power distributed sensing application contexts on what is called the Extreme Edge, and for that purpose a lightweight multi-hop routing strategy for supporting dynamic discovery and interaction among participant devices is fully presented. This embedded algorithm has served as the baseline end-to-end communication capability to validate the IoT hardware platform through intensive experimental tests in a real deployment scenario.

Novel Reliable and Energy-Efficient Routing Protocols for Wireless Sensor Networks

In this paper, novel energy-aware and reliable routing protocols are proposed. The aim is to maximize the lifespan of wireless sensor networks (WSNs) subject to predefined reliability constraints by using multi-hop routing schemes, in which the source node forwards the packet to the base station (BS) via other nodes as relays. In the first proposed protocol, energy efficiency is achieved by maximizing the minimum residual energy of the path subject to fulfilling a predefined reliability constraints. The second protocol is an optimized version of the first one with respect to lifespan and complexity. The optimal path is the one in which the residual energy distribution of the nodes along the path is as close to uniform as possible and the packet arrives at the base station with a given success probability. To measure the uniformity of the residual energy distribution, we use an entropy like measure. The information about the current energy state of the network is maintained by using a look-up-table from which the optimal routes are computed on the BS. The BS broadcasts the updated optimal paths to each node after each round of packet transmission.

Probabilistic bundle relaying scheme in a multi-copy vehicular delay tolerant network

Delay Tolerant Networks (DTNs) enable communications where connectivity issues like intermittent and sparse connection, variable and long delay, high latency and even no end-to-end connectivity exist. Vehicular Delay Tolerant Networks (VDTNs) used the concept of DTNs where vehicles are used for data transmission. A specific class of VDTN considers two types of node: stationary nodes and mobile nodes. Stationary nodes are deployed along roadsides and mobile nodes restricted to move over the road. In this paper, we have proposed a new routing scheme which is an extension of probabilistic bundle relaying scheme with multi-hop. In this routing we have used multi-copy, which allows multiple copies of message to be transmitted, and therefore the delivery ratio can be increased. We compared both the schemes to measure the benefits of multi-copy over the multi-hop routing scheme.