Minimum Hop Count Research Articles

An innovative NSGA-II-based Byzantine Fault Tolerant solution for software defined network environments

Byzantine fault tolerance (BFT) of the control plane in Software Defined Networking (SDN) is achieved by mapping each switch to 3f+1 number of controllers, where f represents the number of faulty controllers that can be tolerated at a time. A BFT approach protects the data plane from any potential malicious activity at the control plane by detecting the inconsistency among the response messages from multiple controllers. To compute the optimal mapping of switches to the controller, the existing literature does not consider some important parameters. This paper proposes a novel approach, named NBFT-SDN, that extends an artificial intelligence algorithm (i.e. NSGA-II) to solve a new formulated multi-objective optimization problem associated with this mapping. NBFT-SDN considers the very important parameters link reliability and link load along with switch-to-controller minimum delay, switch-to-controllers maximum reliability, controller-to-controller minimum delay, minimum link load, minimum hop count, and controller load balancing when mapping the switches to the controllers in optimum manner. The performance of our proposed approach is evaluated in comparison to a state-of-art approach using real network traces with network topologies of diverse sizes. Our proposed approach NBFT-SDN show improved network performance in terms of reliability, delay, hop count, load balancing and link load.

Routing algorithm for sparse unstructured P2P networks using honey bee behavior

SummaryUnstructured peer‐to‐peer (P2P) networks pose unique challenges for efficient and scalable routing. In this study, we introduce a novel routing algorithm inspired by the foraging behavior of honey bees named Honey Bee Optimization in P2P Networks (HBO_P2P) to address the inherent limitations of routing in unstructured P2P networks, focusing on improving packet delivery, minimizing hop count, reducing message overhead, and optimizing overall throughput. To evaluate the performance of our proposed algorithm, we conducted comprehensive experiments comparing it with existing algorithms commonly used in P2P networks, namely, particle swarm optimization (PSO), genetic algorithm (GA), and ant colony optimization (ACO). After the simulation, we got the results as follows: Our algorithm outperforms ACO, GA, and PSO by exhibiting the highest number of data hops indicating potential efficiency in route optimization. Routing overhead is also minimal as compared to ACO, GA, and PSO. The average data packet delay is also low in our algorithm as compared to ACO, GA, and PSO. HBO_P2P achieves the highest throughput, nearly reaching 100 Mbps. While ACO and GA exhibit similar throughput of around 80 Mbps, and PSO has the lowest throughput, approximately 60 Mbps.

A SDN improvement scheme for multi‐path QUIC transmission in satellite networks

AbstractIn recent years, with the development of low‐earth orbit broadband satellites, the combination of multi‐path transmission and software‐defined networking (SDN) for satellite networks has seen rapid advancement. The integration of SDN and multi‐path transmission contributes to improving the efficiency of transmission and reducing network congestion. However, the current SDN controllers do not support the multi‐path QUIC protocol (MPQUIC), and the routing algorithm used in current satellite networks based on minimum hop count struggles to meet the real‐time requirements for some applications. Therefore, this paper designs and implements an SDN controller that supports the MPQUIC protocol and proposes a multi‐objective optimization‐based routing algorithm. This algorithm selects paths with lower propagation delays and higher available bandwidth for subflow transmission to improve transmission throughput. Considering the high‐speed mobility of satellite nodes and frequent link switching, this paper also designs a flow table update algorithm based on the predictability of satellite network topology. It enables proactive rerouting upon link switching, ensuring stable transmission. The performance of the proposed solution is evaluated through satellite network simulation environments. The experimental results highlight that SDN‐MPQUIC significantly improves performance metrics: it reduces average completion time by 37.3% to 59.3% compared to QSMPS and by 52.8% to 72.4% compared to Disjoint for files with different sizes. Additionally, SDN‐MPQUIC achieves an average throughput improvement of 81.4% compared to QSMPS and 147.8% compared to Disjoint, while demonstrating a 26.3% lower retransmission rate than QSMPS.

On Maximizing the Probability of Achieving Deadlines in Communication Networks

We consider the problem of meeting deadline constraints in wireless communication networks. Fulfilling deadlines depends heavily on the routing algorithm used. We study this dependence generically for a broad class of routing algorithms. For analyzing the impact of routing decisions on deadline fulfillment, we adopt a stochastic model from operations research to capture the source-to-destination delay distribution and the corresponding probability of successfully delivering data before a given deadline. Based on this model, we propose a decentralized algorithm that operates locally at each node and exchanges information solely with direct neighbors in order to determine the probabilities of achieving deadlines. A modified version of the algorithm also improves routing tables iteratively to progressively increase the deadline achievement probabilities. This modified algorithm is shown to deliver routing tables that maximize the deadline achievement probabilities for all nodes in a given network. We tested the approach by simulation and compared it with routing strategies based on established metrics, specifically the average delay, minimum hop count, and expected transmission count. Our evaluations encompass different channel quality and small-scale fading conditions, as well as various traffic load scenarios. Notably, our solution consistently outperforms the other approaches in all tested scenarios.

Distributed Satellite-Terrestrial Cooperative Routing Strategy Based on Minimum Hop-Count Analysis in Mega LEO Satellite Constellation

Distributed Satellite-Terrestrial Cooperative Routing Strategy Based on Minimum Hop-Count Analysis in Mega LEO Satellite Constellation

A Novel Hybridized Cluster-Based Geographical Opportunistic Routing Protocol for Effective Data Routing in Underwater Wireless Sensor Networks

Underwater wireless sensor nodes comprise hundreds to thousands of battery-operated sensor nodes with limited bandwidth. These networks are employed to transmit the data with enhanced quality of service (QoS). However, efficient data routing is the most challenging obstacle in many underwater applications. To solve the issues in underwater sensor nodes, the hybridized cluster-based geographical opportunistic routing protocol with distance vector establishment has been proposed to transmit the data efficiently. Primarily, the proposed methodology finds out the shortest path with minimal hop count whereas the void node can be updated with infinite hop count. Thereafter, the sleep/wake scheduling and waiting mechanism and periodic beaconing algorithm are incorporated into the proposed model to attain a higher packet delivery ratio with minimal energy consumption. This proper scheduling and optimal cluster routing enhance the continuous data transmission in underwater applications. The simulation result reveals that the proposed method achieves better energy efficiency and higher network lifetime when compared with the existing clustering methods.

Adaptive Multi-Path Routing Protocol in Autonomous Vehicular Networks

Vehicular ad hoc networks consist of self-organizing nodes using multi-hop wireless links for communication without any infrastructure support. Traditionally, ad hoc routing protocols use the minimum hop count for their routing metric since a smaller number of transmissions is typically equivalent to a higher throughput, lower delay, and minimal power consumption. However, with the muti-rate capability of emerging radio interfaces, e.g., 802.11ax/be standards, the min-hop metric no longer results in high throughput. For instance, if the higher data rate links are selected for the route, it could result in a higher throughput even if the route takes more hop counts. In this paper, we propose a high throughput routing scheme, called MARV, which makes two key contributions. MARV searches for high throughput paths using an on-demand route searching algorithm so that the routing overhead is smaller compared to other multi-rate-aware routing schemes. MARV also searches for multiple paths to maintain both min-hop and high-throughput paths to select the adequate path depending on the data packet size. We conduct simulations to demonstrate that MARV outperforms not only min-hop path metrics but also previously proposed high-throughput metrics.

A DV-Hop optimization localization algorithm based on topological structure similarity in three-dimensional wireless sensor networks

Localization technology performs an essential part in wireless sensor networks (WSNs). The Distance vector hop (DV-Hop) localization algorithm has been frequently used in the WSNs with its simplicity, feasibility and minimal hardware requirements. However, the low localization accuracy of the DV-Hop algorithm has limited its further application in WSNs. To overcome the accuracy problem of the DV-Hop algorithm, we propose an improved DV-Hop algorithm based on topological structure similarity, called TDSDV-Hop. Different from the traditional DV-Hop algorithm, the topological structure similarity is applied to correct the hop count, reducing the inaccuracy caused by the minimum hop count. The hop counts will be converted from discrete to precise continuous values by the topological structure similarity. In this paper, firstly, the topological structure similarity is defined, followed by the proof of the theory that the distance between two nodes is inversely proportional to the topological structure similarity. Secondly, a hop-correction equation that can correct the hop count between neighbor nodes is set up. Then the TDSDV-Hop algorithm incorporates hop-correction formula and simulates the optimal hop-correction parameters in order to acquire more accurate values of the hop count. And the coordinates of unknown nodes are calculated by the least square method. Finally, the levy adaptive improved bird swarm algorithm (LSABSA) is utilized to optimize coordinates of unknown nodes by constructing a new objective function. The simulation results show that the localization performance of the TDSDV-Hop algorithm is better than that of DV-Hop, GWODV-Hop, CRWDV-Hop and CVLR algorithm in terms of localization accuracy, localization time and communication cost.

Innovative DMHS Algorithm Application in Wireless Sensor Networks for Efficient Routing in High-Risk Environments.

Efficient routing is essential for the proper functioning of wireless sensor networks (WSNs). Recent research has focused on optimizing energy and delay for these networks. Nevertheless, there is a dearth of studies that have examined the effects of volatile settings, such as chemical plants, coal mines, nuclear power plants, and battlefields, where connectivity is inconsistent. In such contexts, sensor networks may face security incidents, and environmental factors such as node movement and death can result in dynamic changes to the network topology. A novel design algorithm grounded on Dynamic Minimum Hop Selection (DMHS) was introduced in this paper. The key principle behind DMHS is to use a probabilistic forwarding decision-making process through a distributed route discovery strategy that utilizes dynamically adjusted minimum hop counts of nodes. Simulation results indicate that the life cycle of the DMHS algorithm increases by more than 12% over 700 nodes when compared to the traditional energy-saving algorithm. Furthermore, our algorithm performs better in the average delivery rate of node, and has a 10% to 21% improvement compared to the other algorithms. Overall, the DMHS algorithm represents an important contribution to the development of WSNs that can function robustly in high-risk and unstable environments.

Study on the wireless sensor networks routing for Low-Power FPGA hardware in field applications

Very intelligent compact sensors with low-power and inexpensive solutions have been created because of the industrial revolution and subsequent advancements in electrical technology and wireless communications. Modern innovative enhancements have been made for the utilization of small, low-price, and low-power wireless communication devices with fast processing capabilities. The sensor node communication and routing play a significant role in the configuration of a specific WSN environment. There are three types of WSN routing: proactive, reactive, and hybrid. DSDV and OLSR are two proactive routing technologies. AODV and DSR are reactive routing technologies. DSDV Routing requires a progress update of its routing tables even when the network is not in use, which uses battery power and generates negligible data. As a result, this protocol is inappropriate for networks that are both huge in scope and very dynamic. OLSR maintains track of all potential solutions in a routing table. The overhead from control messages rises as there are more mobile hosts. It requires more processing power than other protocols while looking for alternate routes. The DSR protocol relies on the minimal hop count parameter to pick the way without considering other parameters that impact routing algorithm performance, such as energy consumption, residual energy, and connection stabilities. The FPGA realization provides an ascendable computing environment for WSN planning in a specific region. The research articles emphasize the hardware chip simulation and analysis of these routing protocols which can be further applied for field applications and configuration The network performance is evaluated using several performance metrics such as throughput, control overhead, delay, packet delivery ratio, and power consumption. This study offers a key method for creating FPGA-based power estimation and verification models for a WSN planning environment.

A Time Synchronization Protocol for Barrage Relay Networks

Time-division multiple access (TDMA)-based medium access control (MAC) protocol has been widely used for avoiding access conflicts in wireless multi-hop ad hoc networks, where the time synchronization among wireless nodes is essential. In this paper, we propose a novel time synchronization protocol for TDMA-based cooperative multi-hop wireless ad hoc networks, which are also called barrage relay networks (BRNs). The proposed time synchronization protocol is based on cooperative relay transmissions to send time synchronization messages. We also propose a network time reference (NTR) selection technique for improving the convergence time and average time error. In the proposed NTR selection technique, each node overhears the user identifier (UID) of other nodes, hop count (HC) from them to itself, and network degree, which denotes the number of 1-hop neighbor nodes. Then, the node with the minimum HC from all other nodes is selected as the NTR node. If there are multiple nodes with the minimum HC, the node with the larger degree is selected as the NTR node. To the best of our knowledge, the proposed time synchronization protocol with the NTR selection is introduced for the first time for cooperative (barrage) relay networks in this paper. Through computer simulations, we validate the proposed time synchronization protocol in terms of the average time error under various practical network scenarios. Furthermore, we also compare the performance of the proposed protocol with the conventional time synchronization methods. It is shown that the proposed protocol significantly outperforms the conventional methods in terms of the average time error and convergence time. The proposed protocol is shown to be more robust against packet loss as well.

A genetic algorithm for shortest path with real constraints in computer networks

<span lang="EN-US">The shortest path problem has many different versions. In this manuscript, we proposed a muti-constrained optimization method to find the shortest path in a computer network. In general, a genetic algorithm is one of the common heuristic algorithms. In this paper, we employed the genetic algorithm to find the solution of the shortest path multi-constrained problem. The proposed algorithm finds the best route for network packets with minimum total cost, delay, and hop count constrained with limited bandwidth. The new algorithm was implemented on four different capacity networks with random network parameters, the results showed that the shortest path under constraints can be found in a reasonable time. The experimental results showed that the algorithm always found the shortest path with minimal constraints.</span>

Reinforcement Learning to Improve QoS and Minimizing Delay in IoT

Machine Learning concepts have raised executions in all knowledge domains, including the Internet of Thing (IoT) and several business domains. Quality of Service (QoS) has become an important problem in IoT surrounding since there is a vast explosion of connecting sensors, information and usage. Sensor data gathering is an efficient solution to collect information from spatially disseminated IoT nodes. Reinforcement Learning Mechanism to improve the QoS (RLMQ) and use a Mobile Sink (MS) to minimize the delay in the wireless IoT s proposed in this paper. Here, we use machine learning concepts like Reinforcement Learning (RL) to improve the QoS and energy efficiency in the Wireless Sensor Network (WSN). The MS collects the data from the Cluster Head (CH), and the RL incentive values select CH. The incentives value is computed by the QoS parameters such as minimum energy utilization, minimum bandwidth utilization, minimum hop count, and minimum time delay. The MS is used to collect the data from CH, thus minimizing the network delay. The sleep and awake scheduling is used for minimizing the CH dead in the WSN. This work is simulated, and the results show that the RLMQ scheme performs better than the baseline protocol. Results prove that RLMQ increased the residual energy, throughput and minimized the network delay in the WSN.

Connectivity-Based Localization Scheme for Social Internet of Things

Different from the social network which only focuses on the interaction between people, the integration of social networks and the internet of things (IoT) leads to multi-directional interactions of human to human, human to thing, and thing to thing. The social IoT is composed of a large number of heterogeneous devices, which can improve the scalability of resource and service. Meanwhile, the heterogeneous devices have uneven computing power and different location information measurement types (e.g., the distance, angle, and hop count). Therefore, a localization approach with easy-to-obtain measurement data and low requirements on the computing power is needed. In this article, we propose a localization approach for the social IoT by combining the fuzzy rough set theory and the ridge regression extreme learning machine (RRELM). First of all, a location fingerprint database is constructed. Different from the traditional location fingerprint database, the location fingerprint database here stores the minimum hop counts between the reference node (RN) and the anchor node (AN) instead of the received signal strength (RSS). Second, the fuzzy rough set theory is used to compute the significant degree of each AN, and the ANs that contribute little to the positioning result are removed. This approach not only relieves the storage pressure of the location fingerprint database but also reduces the computational complexity of user position estimation. Third, the RRELM is trained by using the samples in the location fingerprint database. Finally, by inputting the newly collected minimum hop counts from the user to each AN into the trained RRELM, the user’s position is estimated. From the extensive experimental results, the proposed approach has high positioning accuracy and low computational complexity, which is suitable for the social IoT.

Distributed formation control of multiple aerial vehicles based on guidance route

Formation control of fixed-wing aerial vehicles is an important yet rarely addressed problem because of their complex dynamics and various motion constraints, such as nonholonomic and velocity constraints. The guidance-route-based strategy has been demonstrated to be applicable to fixed-wing aircraft. However, it requires a global coordinator and there exists control lag, due to its own natures. For this reason, this paper presents a fully distributed guidance-route-based formation approach to address the aforementioned issues. First, a hop-count scheme is introduced to achieve distributed implementation, in which each aircraft chooses a neighbor with the minimum hop-count as a reference to generate its guidance route using only local information. Next, the model predictive control algorithm is employed to eliminate the control lag and achieve precise formation shape control. In addition, the stall protection and collision avoidance are also considered. Finally, three numerical simulations demonstrate that our proposed approach can implement precise formation shape control of fixed-wing aircraft in a fully distributed manner.

Energy-Efficient Guiding-Network-Based Routing for Underwater Wireless Sensor Networks

With the increasing underwater applications, underwater wireless sensor networks (UWSNs) have become a research hotspot. Routing protocols used to keep network connectivity and reliable transmission are essential in UWSNs. Due to the specific limitations in UWSNs, such as serious ocean interference, high propagation latency, and dynamic network topology, it is challenging to balance multiple performances, such as real timeness and energy efficiency in a routing protocol. To this end, this article proposes a localization-free routing scheme, termed energy-efficient guiding-network-based routing (EEGNBR) protocol, to provide a time saving and reliable routing for UWSNs, which is a good choice for applications characterized by intermittent connectivity. For reducing the network delay, EEGNBR cites the advantageous distance-vector mechanism and establishes a guiding network to provide underwater sensor nodes with the shortest route (minimum hop counts) toward the sinks. Moreover, EEGNBR innovatively replaces the waiting mechanism used in traditional opportunistic routing with a novel data forwarding mechanism named concurrent working mechanism, which could greatly reduce the forwarding delay while guaranteeing reliable routing. In order to ensure routing reliability as well as avoid duplicate transmission, the forwarding protection mechanism is adopted to save energy consumption and extend the service life of the network. Simulation results show that EEGNBR performs significantly better than some classical related protocols in terms of network delay while maintaining comparable or even better energy consumption and packet delivery ratio.

Hop Count Distribution for Minimum Hop-Count Routing in Finite Ad Hoc Networks

Hop count distribution (HCD), generally formulated as a discrete probability distribution of the hop count, constitutes an attractive tool for performance analysis and algorithm design. This paper devotes to deriving an analytical HCD expression for a finite ad hoc network under the minimum hop-count routing protocols. Formulating the node distribution with binomial point process, the network is provided as a bounded area with all nodes randomly and uniformly distributed. Considering an arbitrary pair of source node (SN) and destination node, an innovative and straightforward definition is presented for HCD. In order to derive HCD out, an original mathematical framework, named as the equivalent area replacement method (EARM), is proposed and verified. Under the EARM, HCD is derived by first considering the special case where SN locates at the network center and then extending to the general case where SN is randomly distributed. For each case, the accuracy of our HCD model is evaluated by simulation comparison. Results show that our model matches well with the simulation results over a wide range of parameters. Particularly, the derived HCD outperforms the existing formulations in terms of the Kullback Leibler divergence, especially when SN is randomly distributed.

Fuzzy Logic-based Trusted and Power-aware Routing Protocol in Mobile Ad-hoc Networks

Mobile ad-hoc networks (MANETs) have attracted much attention from researchers lately because MANETs are able to provide networks in areas with unavailable fixed network infrastructure. However, some mobile nodes may misbehave by dropping packets to conserve power usage because mobile ad-hoc networks nodes are usually battery operated. In this paper, a fuzzy logic-based routing protocol that considers the battery level of nodes, hop count, and trust among the nodes is proposed. The proposed routing protocol adaptively selects routes that use minimum hop count with the highest level of trust and a sufficient battery level to enhance the reliability of route selection while maintaining the percentage of successfully delivered packets. The result of the simulation shows that the proposed protocol can achieve a high ratio of successfully delivered packets, a lower average end-to-end delay, and a normalized routing load.

Ferry–Based Directional Forwarding Mechanism for Improved Network Life-Time in Cluster-Based Wireless Sensor Network

Considerable energy saving can be achieved with mobility-based wireless sensor networks (WSN's), where a mobile node (ferry) visits sensing nodes in a network to collect sensed data. However, the critical issues of such WSN's are limited networks lifetime and high data latency, these critical issues are due to the slow mobility and relatively long route distance for ferries to collect and forward data to the sink. Incorporating ferries in WSNs eliminates the need for multi-hop forwarding of data, and as a result, reduce energy consumption at sensing nodes. In this paper, we introduce the One Hop Cluster-Head Algorithm (OHCH), where a subset of ferries serve as cluster heads (CH), travel between nodes with short distance mobility, collect data originated from sources, and transfer it to the sink with minimum hop count possible, this approach can achieve more balance between network energy saving and data collection delay, also, it is an efficient design to combine between ferries and noise.

Reliable routing in Wireless Body Area Network using optimum number of relay nodes for enhancing network lifetime

Wireless Body Area Network (WBAN) is an emerging technology that has the potential to redefine healthcare sector around the world. It can perform proactively by ubiquitously monitoring human health. But its enormous scope is challenged by limited battery power of the sensors, energy and bandwidth. Moreover, the random motion of human beings makes sensor positioning difficult and restricts efficiently routing of critical health parameter values. State of the art protocols do not address the adverse effects of heating of the implanted sensors on human tissues along with energy constraints and interference issues simultaneously. This paper handles all these issues jointly by designing a topology which has an optimized number of relay nodes and then proposes an efficient routing algorithm. Relay nodes are incorporated to frame the backbone of the connected wireless network so that all sensor nodes are coupled with at least one relay node and none of the nodes in the network remain isolated. In the proposed method, the remaining energy of the in-vivo sensors are dissipated intelligently and homogeneously so that network lifetime is enhanced without compromising reliability. Moreover, in our method, multicasting has been used to reduce transmission of unnecessary packets. Our design also leads to minimum hop count from body sensors to the sink node. The effectiveness and feasibility of our proposed approach has been evaluated and analyzed through numerous simulations. The analysis illustrates the efficacy of the proposed solution in terms of delay, network lifetime, energy efficiency, SAR and throughput.