Forwarding Node Selection Research Articles

Forward Node Selection by Evaluating Link Quality Using Fuzzy Logic in WBAN

WBAN technology plays a vital role in human life monitoring and maintaining health remotely without being hospitalized, particularly during pandemic situations. The miniature-sized and heterogeneous sensors involved in WBAN with limited resources face reliability as a key challenge that limits the growth of WBAN technology. Designing an efficient routing protocol helps to achieve reliable data transmission between sensor nodes in WBAN. The proposed Fuzzy logic-based Forward Node Selection chooses the best node to transmit the data by introducing fuzzy logic on routing parameters such as link quality, data rate, node’s residual energy and node-to-node distance. The key advantages of our proposed system are to extend the network lifetime and boost the packet delivery ratio. The efficiency of our proposed method is estimated by comparing the parameters of network lifetime and packet delivery ratio with DTS and EARP protocols.

MH‐ARO: Meta‐heuristic based adaptive routing for large scale opportunistic networks

SummaryIn wireless sensor networks, sensor nodes (SNs) are placed throughout a wide area and gather information from the surroundings. SN used to detect and send data consumes a lot of energy and dies instantly, which causes network overhead issues. Due to network overhead, network faults occur and do not cover a significant region for data transmission. A meta‐heuristic‐based adaptive routing for large‐scale opportunistic networks (MH‐ARO) is proposed in this work to overcome these problems. The network exploits the dragonfly approach (DA) with opportunistic routing in this protocol. The DA is based on local and global search (GS) optimization. In local search (LS), each node assigns/uses a rank for data transmission and selects the forwarder node after applying the decision level matrix in a single group. In GS, an opportunistic network has multiple groups. Each group sends optimal data to the next group. Each group assigns a relay ranking based on the forwarder node's highest rank. The BS receives critical data from the relay and increases the survival of the node. Based on LS and GS, MH‐ARO is categorized into two parts: (1) optimal forwarder opt (OFO) and (2) optimal route selection (ORS). In OFO, forwarder node selection is based on the following factors: relay ranking, node density, group ranking, residual energy, forwarder distance, and relay distance. ORS follows the adaptive routing and sends the data to BS using the best optimal route. The BS receives critical data without network failure and increases the survival of the node. The maximum active node participates in the network and consumes less energy so that a node covers a large region for communication. Comparing MH‐ARO's performance to competing routing protocols, key performance indicators such as PDR, MSR, alive node, survivability, AEC, AD, and throughput are examined. The results demonstrate that the MH‐ARO performs noticeably better than its rivals regarding energy efficiency.

Multi-granularity fusion resource allocation algorithm based on dual-attention deep reinforcement learning and lifelong learning architecture in heterogeneous IIoT

Deep reinforcement learning (DRL) is a promising technology to address the resource allocation problem for efficient data transmission in complex network environments. However, most DRL-based resource allocation algorithms suffer from limited feature extraction capabilities and lack scalability and generalization, especially in heterogeneous Industrial Internet of Things (IIoT) environments. In this paper, we develop a lifelong learning architecture that can integrate artificial intelligence (AI) algorithms into the heterogeneous IIoT network for efficient data transmission. Based on this, we propose an intelligent resource allocation algorithm based on dual-attention DRL (DADR) for forwarding node selection and channel access slot allocation in a specific network environment. The proposed DADR algorithm combines the advantages of multi-dimension convolutional attention and multi-head self-attention mechanisms. It can provide local- and global-feature fusion capabilities for distributed nodes while maximizing the performance of data transmission. Furthermore, we present a lifelong federated meta reinforcement learning (LFMRL) that can effectively utilize prior knowledge and enable the DRL agent quickly adapt to a new environment. Specifically, LFMRL adopts a federated meta learning-based knowledge fusion algorithm to fuse the knowledge of learned DADR algorithms and iteratively update the shared model, thereby improving the scalability and generalization of the shared model in heterogeneous IIoT environments. In addition, a simple and efficient knowledge transfer mechanism is enabled to accelerate the DRL model convergence by transferring the knowledge of the shared model to the new environment. Simulation results demonstrate the effectiveness of the proposed algorithms in terms of energy efficiency, data transmission reliability, and network stability. Compared to DADR and FedAvg algorithms, LFMRL algorithm can further reduce the energy consumption, training time, and average forwarding node switching times, while improving packet delivery rate to 99.2%.

FSE2R: An Improved Collision-Avoidance-based Energy Efficient Route Selection Protocol in USN

The 3D Underwater Sensor Network (USNs) has become the most optimistic medium for tracking and monitoring underwater environment. Energy and collision are two most critical factors in USNs for both sparse and dense regions. Due to harsh ocean environment, it is a challenge to design a reliable energy efficient with collision free protocol. Diversity in link qualities may cause collision and frequent communication lead to energy loss; that effects the network performance. To overcome these challenges a novel protocol Forwarder Selection Energy Efficient Routing (FSE2R) is proposed. Our proposal’s key idea is based on computation of node distance from the sink, Residual Energy (RE) of each node and Signal to Interference Noise Ratio (SINR). The node distance from sink and RE is computed for reliable forwarder node selection and SINR is used for analysis of collision. The novel proposal compares with existing protocols like H2AB, DEEP, and E2LR to achieve Quality of Service (QoS) in terms of throughput, packet delivery ratio and energy consumption. The comparative analysis shows that FSE2R gives on an average 30% less energy consumption, 24.62% better PDR and 48.31% less end-to-end delay compared to other protocols.

PERFORMANCE ANALYSIS ON GPSR PROTOCOL IN VANETS ENVIRONMENT OF OVERLAY NETWORK AND FORWARDING NODE SELECTION METHODS

VANETs are technology in Intelligent Transport Systems (ITS) in driving safety and convenient network services for vehicle users. However, the high mobility of VANETs makes the topology change frequently, resulting in the unavailability of routes and causing communication failures between nodes. Greedy Perimeter Stateless Routing (GPSR) is a routing protocol that solves communication problems in the VANETs environment. GPSR is a geographic routing protocol that uses information on the location of neighbouring nodes and the transmission range to the nearest destination node. But, GPSR does not always find the optimal route because not all nearby nodes can forward packets to their destination during heavy traffic and many intersections. In this research, the overlay network and forwarding node selection methods will be used to solve problems in the GPSR routing protocol related to communication instability because of changing node positions. Based on the results of testing and analysis that has been carried out on a grid scenario with 50 nodes, the Packet Delivery Ratio results are 32.60. In contrast, the results for the real scenario with the same nodes produce a value of 64. The analysis of End to End Delay in the 50-node grid scenario produces 5.64, while the real scenario results with 50 nodes yield the value of 24.11. The analysis Routing Overhead in the grid scenario with 50 nodes produces a value of 39,978, while the results of the real scenario with 50 nodes get a value of 10,239. With the result of these two analysis methods, it is expected to increase the average value of package delivery.

Honesty aware congestion concerned secured edge disjoint multi path routing with fuzzy rule descriptors

Congestion and security plays a most important key role in the wireless sensor network. In our previous work, energy balances routing is ensured by introducing the Energy Balancing and Optimal Routing Based Secured Data Transmission (EBORDT). But in this research work, congestion and security is not focused. This will lead to increased data loss rate along with entire network collision. These issues are focused and resolved in the proposed research work by introducing the method namely Honest aware Congestion concerned Secured Edge Disjoint Multipath Routing (HC-SEDMR) Scheme. In this work cluster head selection is done using hybridized simulated annealing with fuzzy rule descriptors. Base on these selected cluster head, clustering is done using Normalized optimal clustering algorithm. After clustering Energy and Edge disjoint aware optimal routing is done using Congestion and Collision aware Edge Disjoint multipath routing. Here secured routing is ensured by choosing honest nodes for the forwarding process. This is done by using honest forwarding node selection method. The performance analysis of the research work is done in the NS2 simulation environment from which it is proved that the proposed method attains better performance than the existing methodology.

Cross Layered Network Condition Aware Mobile-Wireless Multimedia Sensor Network Routing Protocol for Mission Critical Communication

The high pace emergence in wireless technologies have given rise to an immense demand towards Quality of Service (QoS) aware multimedia data transmission over mobile wireless multimedia sensor network (WMSN). Ensuring reliable communication over WMSN while fulfilling timely and optimal packet delivery over WMSN can be of great significance for emerging IoT ecosystem. With these motivations, in this paper a highly robust and efficient cross layered routing protocol named network condition aware mobile-WMSN routing protocol (NCAM-RP) has been developed. NCAM-RP introduces a proactive neighbour table management, congestion awareness, packet velocity estimation, dynamic link quality estimation (DLQE), and deadline sensitive service differentiation based multimedia traffic prioritization, and multi-constraints based best forwarding node selection mechanisms. These optimization measures have been applied on network layer, MAC layer and the physical layer of the protocol stack that eventually strengthen NCAM-RP to enable QoS-aware multimedia data transmission over WMSNs. The proposed NCAM-RP protocol intends to optimize real time mission critical (even driven) multimedia data (RTMD) transmission while ensuring best feasible resource allocation to the non-real time (NRT) data traffic over WMSNs. NCAM-RP has outperform RPAR based routing scheme in terms of higher data delivery, lower packet drops and deadline miss ratio. It signifies that NCAM-RP can ensure minimal retransmission that eventually can reduce energy consumption, delay and computational overheads. Being the mobility based WMSN protocol, NCAM-RP can play significant role in IoT ecosystem.

FIRST: Fuzzy based intelligent relay selection and transition technique for delay tolerant networks

SummaryDelay tolerant network (DTN) has attracted significant attention of the researchers due to its capability of delivering the message even in the situation where network connectivity is irregular. Irregular networks result in non‐delivery of data to user at right time, and the same is not possible with traditional algorithms due to requirement of end‐to‐end connectivity between nodes. DTN uses story–carry–forward technique to deliver a message in the environment of disconnection. Hence, for message transmission from source node to destination node, a relay node or forwarder node is required. The efficiency of the network is mainly dependent on the selection of forwarder node. Hence, forwarder node selection is very crucial in DTNs. The objective of this paper is to propose an efficient relay node selection technique integrated with fuzzy logic, based on four properties of node, namely, number of encounters, residual energy, buffer capacity, and speed so that performance metrics of the network can be improve. Proposed method uses fuzzy logic to decide which node should be selected as relay node in multi hop strategy. The study of simulation results indicate that proposed algorithm improves performance of the network with regards to delivery ratio, delay, hop count, and throughput.

ENHANCED LION SWARM OPTIMIZATION ALGORITHM WITH CENTRALIZED AUTHENTICATION APPROACH FOR SECURED DATA TRANSMISSION OVER WSN

Securing data accuracy in WSNs (Wireless Sensor Networks) is a major problem. Aggregation techniques for improving accuracy in data processing have been gaining attention of scholars, recently. Existing security systems using singular paths for transmission of data have delays in transmissions while being open to intrusions. Moreover, increased computational overheads and processing time increases the delay of data transmission in the given networks. To overcome these issues, this work proposes ELSOA-CA (Enhanced Lion Swarm Optimization Algorithm and Centralized Authentication) method. This method focuses on an optimal, faster and energy efficient data transmissions while ensuring accurate decisions on tomato crops. Multipath routing introduced in the proposed method ensures faster data transmissions by selecting optimal forwarder nodes which satisfy the constraints of delay and energy. Optimal forwarder node selection is done using ELOSA algorithm. Data transmissions are secured by centralized authentication involving third party nodes. Each and every node in a region gets registered with the authentication node where a node’s genuineness is checked the node is allowed into the forwarder node list, used for data routing. CA (Centralized Authentication) enhances the security level of data transmissions over WSN multi path routing. ELSOA-CA framework’s simulation results provide higher throughputs, reduced energy consumptions, improved network lifetimes PDRs (Packet Drop Ratios) and lesser delay times.

A Geographical Routing Approach Based on Probability Delegation Replication (GR-PDR) in VDTN

The routing in vehicular delay tolerant networks (VDTNs) does not presume an end-to-end connectivity from source to destination. One substitute is to use the real-time geographical information of vehicles to relay messages. However, if mobile destination is considered, then real-time information might not be generally available due to the sparse network density in VDTN. In this paper, a geographical routing approach based on the probability delegation replication (GR-PDR) is proposed. The functionality of GR-PDR is categorized into forwarder node selection phase and buffer management phase. The forwarder node selection utilizes the advantages of delegation replication approach to conquer the constraints of routing decisions and local maximum problem. Further, the buffer management is employed to prioritize packets to ensure delivery before the expiration of message lifetime. The proposed GR-PDR ensures that the message will be forwarded to higher quality node, resulting in a high delivery ratio. The approach utilizes the advantages of single-copy and multiple-copy forwarding approaches by avoiding redundant replication and enhancing delivery probability, respectively. The performance results show that the proposed GR-PDR outperforms in terms of packet delivery ratio, average delay and network overhead, when compared with the protocols of the same segment. Statistical analysis validates the effectiveness of the proposed protocol.

APSSR: Adaptive Packet Size Selection Based Routing Protocol for Underwater Acoustic Sensor Networks

Underwater Acoustic Sensor Networks offer very promising solutions to monitor the aqueous environments. Due to the distinctive characteristics of UASNs, it is very challenging to design a routing protocol that can achieve maximum data delivery ratio in the network. The main challenge is the communication medium (acoustic links) that is subject to temporary attenuation and high bit error rate (BER), which limits the throughput efficiency of the Network. Besides this, another major issue is the continuous movement of nodes due to water currents and the availability of limited resources. Due to nodes mobility distance among sensor nodes and consequently, BER varies, which have a direct impact on packet size, hence, leads to high packet loss and low data delivery ratio. To achieve a high data delivery ratio, the selection of optimal packet size is of utmost importance. Consequently, the selection of next-hop forwarding node based on optimal packet size is needed. Therefore, in this paper, we propose an adaptive routing protocol named Adaptive Packet Size Selection Based Routing (APSSR) Protocol for UASNs. APSSR determines the optimal packet size adaptively based on both varying distances between sensor nodes and BER and selects the next hop based on optimal packet size and BER. The simulation results show greater network performance in terms of Network Lifetime, Data Reception Ratio at Sink node, Average Network Delay, Packet Reception Ratio, and Packets Drop Ratio

An Enhanced Multi-Hop Intersection-Based Geographical Routing Protocol for the Internet of Connected Vehicles Network

Internet of connected vehicles (IoCV) is one of the popular subclasses of vehicle ad hoc networks and an up-rising form based on new Internet, 5G, cloud, and edge computing features. The vehicle nodes in such networks can exchange the information with other nodes with the help of infrastructure or without prior infrastructure. For efficient data communication among the vehicle nodes, the routing protocols play a significant role and able to handle the different network characteristics including high mobility, dynamic topologies, and disconnected links. To address the existing routing protocol issues including data delay, disconnection, interference, scalability, and overhead, this paper presents the Intersection Gateway and Connectivity based Routing (IGCR) protocol for IoCV networks. The proposed protocol uses important traffic-aware routing metrics, including traffic density and direction of nodes towards the destination for route and next forwarder node selection. The experimental results indicated that the proposed protocol well-behaved and showing better performance compared to the state of the art routing protocols in terms of data delivery, data delay, and data throughput.

Geographic routing enhancement for urban VANETs using link dynamic behavior: A cross layer approach

Geographic routing protocols are suitable for VANETs because of their scalability and low overhead. However, the optimal selection of next-hop forwarding nodes is challenged by the dynamic topology of VANETs, in addition to the variable quality of wireless links and the temporal changes in available bandwidth. In this paper, we introduce a scheme to select the next-hop forwarder based on its mobility relative to the destination and the dynamic behavior of its link with the current forwarder. We present a cross-layer model of link dynamic behavior (LDB), which takes into account the loss ratio, physical interference, and medium access control (MAC) overhead, including queuing and retransmission delays experienced on a wireless link. Based on LDB, we propose an enhancement of geographic routing, called Geo-CAP, for urban VANETs. By selecting more reliable links and timely reacting to varying nodes load and network conditions, the proposed protocol can offer considerable performance gains by reducing packet loss and delay. This performance is demonstrated using extensive simulation experiments in NS-3.

Underwater Acoustic Sensor Networks: An Energy Efficient and Void Avoidance Routing Based on Grey Wolf Optimization Algorithm

The purpose of underwater acoustic sensor networks (UWASNs) is to find varied applications for ocean monitoring and exploration of offshore. In majority of these applications, the network comprises of several sensor nodes deployed at different depths in water. The sensor nodes which are situated in depth, at the sea bed, are unable to communicate unswervingly with those nodes which are close to the surface level; these nodes necessitate multi-hop communication which is facilitated by suitable routing plan. The working of UWASNs is affected by some constraints like high transmission delay, energy consumption, deployment, long propagation delay and high attenuation. Apart from this, the existence of void region in the route can also affect the overall performance of UWASNs. So, the void region can be avoided by considering the best forwarder node. The selection of the best forwarder node depends on depth variance, depth difference, residual energy, and link quality. Apart from this, an angle is also considered to select the best forwarder node. This paper presents an energy efficient and void region avoidance routing. The concept of grey wolf optimization algorithm is used here to select the best forwarder node. The proposed work increases the network lifetime by avoiding the void region and also balancing the network energy. The proposed work is simulated in the MATLAB platform and compared with weighting depth and forwarding area division depth-based routing and energy and depth variance-based opportunistic void avoidance schemes. This work achieves the packet delivery ratio 96% with varying transmission range up to 1000 m at 180 node size. Along with this, it decreases the end-to-end delay and average number of dead nodes up to 53% and 145, respectively. This work also improves the overall network lifetime and reduces the transmission delay. This work also propagates 55% less copies of data packets. Similar to this, some other performance metrics are also explained in the results section.

Green Communication for Underwater Wireless Sensor Networks: Triangle Metric Based Multi-Layered Routing Protocol.

In this paper, we propose a non-localization routing protocol for underwater wireless sensor networks (UWSNs), namely, the triangle metric based multi-layered routing protocol (TM2RP). The main idea of the proposed TM2RP is to utilize supernodes along with depth information and residual energy to balance the energy consumption between sensors. Moreover, TM2RP is the first multi-layered and multi-metric pressure routing protocol that considers link quality with residual energy to improve the selection of next forwarding nodes with more reliable and energy-efficient links. The aqua-sim package based on the ns-2 simulator was used to evaluate the performance of the proposed TM2RP. The obtained results were compared to other similar methods such as depth based routing (DBR) and multi-layered routing protocol (MRP). Simulation results showed that the proposed protocol (TM2RP) obtained better outcomes in terms of energy consumption, network lifetime, packet delivery ratio, and end-to-end delay.

An Energy Efficient and Reliable Routing Scheme to enhance the stability period in Wireless Body Area Networks

Wireless Body Area Network (WBAN) is a wireless network of wearable sensing and computing devices connected through a wireless communication channel, thereby offering a plethora of enticing applications in the area of remote health monitoring, sports, and entertainment. However, WBANs nodes are highly resource-constrained; therefore, energy-efficient and reliable data transmission is very vital in the design and implementation of most of its applications. Furthermore, on time and accurate data delivery with minimum delay is also highly required. Over time, numerous energy-efficient routing solutions have been proposed for WBANs; however, the significant feature of reliability in these solutions has not been adequately addressed. Therefore, in this paper, we propose a new Energy-Efficient and Reliable Routing Scheme (ERRS) to enhance the stability period and reliability for resource-constrained WBAN. ERRS comprises two novel solutions, namely, the Forwarder Node Selection and Forwarder Node Rotation techniques. The proposed ERRS takes advantage of the adaptive static clustering routing technique and achieves enhanced stability period and longer network lifetime, ultimately maximizing reliability. Through extensive simulation-based evaluation using MATLAB, ERRS showed an improvement of 26% over the benchmark protocol in terms of network stability and throughput. Whereas the end-to-end delay of the proposed ERRS is improved by 17% and 40% than by SIMPLE and M-ATTEMPT protocols, respectively, which proves ERRS to be an efficient and reliable routing solution for WBANs.

An Efficient Data Collection Protocol for Underwater Wireless Sensor Networks

This paper presents the design and evaluation of a new data collection protocol for Underwater Wireless Sensor Networks called the Data Collection Tree Protocol (DCTP). It uses an efficient distributed algorithm to proactively construct and maintain a data collection tree rooted at the sink node. The preconstructed and maintained data collection tree allows the efficient selection of a single forwarding node at each hop when routing a data packet. We prove the correctness of the constructed data collection tree and we show that under some stability conditions, the constructed tree converges to an optimal shortestpath tree. Results of extensive simulations show a big improvement in terms of packet delivery ratio, endto-end delay and energy consumption compared to the well-known VBF protocol. The simulated cases show increases in the packet delivery ratio between 20% and 122%, reductions in the average end-to-enddelay between 15% and 55% and reductions in the energy consumption between 20% and 50%. These results clearly demonstrate the attractiveness of the proposed DCTP protocol.

Forward Node Selection Using Particle Swarm Optimization (PSO) for Broadcasting in MANET

Forward Node Selection Using Particle Swarm Optimization (PSO) for Broadcasting in MANET

Cross‐layer routing protocol for event‐driven M2M communication in IoT‐assisted Smart City Planning and Management: CWSN‐eSCPM

The robustness of wireless sensor networks (WSNs) has broadened the use of wireless communication systems for modern machine-to-machine (M2M) communication. Internet-of-Things (IoT) being one of the most explored technologies has gained wide attention due to low-cost WSN communication systems. IoT is one of the dominant technologies used in Smart City implementation demands better communication paradigm including mobility assisted transmission paradigms; however, native IEEE 802.15.4 standard does not have mobility provision that limits its use for real-time applications. On contrary, implementing mobility with classical WSN might impose significantly great topological changes and node or network condition variations which cannot be dealt with the traditional reactive routing approach. Incorporating node and/or network awareness with proactive network management can enable classical WSN to support mobility, which can be vital for IoT based Smart City Planning and Management (SCPM). With this motivation, in this study, a robust Cross-Layer Architecture based WSN Routing Protocol for Event-Driven M2M Communication in SCPM (CWSN-eSCPM) is developed. CWSN-eSCPM encompasses Proactive Node Management Strategy, Data-Centric Service Differentiation and Fair Resource Scheduling (DCSDFRS), Packet Velocity Estimation, Cumulative Congestion Estimation, Dynamic Link Assessment that enables optimal Best Forwarding Node selection for deadline sensitive and reliable data communication. CWSN-eSCPM applies dynamic link quality, cumulative congestion degree, and packet velocity of a node to enable optimal routing decision. DCSDFRS enables optimal resource provision to the real-time data while assuring maximum possible resource for non-real-time data that assures Quality of Service provision for event-driven critical communication in SCPM. Noticeably, CWSN-eSCPM protocol has been applied on top of IEEE 802.15.4 protocol standard, while preserving backward compatibility feature, it can be used for WSN assisted communication purposes. The authors' proposed protocol has performed better in terms of packet delivery ratio, packet loss ratio and deadline miss ratio for both real-time data as well as non-real-time data.

Optimal packet routing for wireless body area network using software defined network to handle medical emergency

<span lang="EN-US">The packet forwarding node selection is one of the main constraints in the Software Defined Network (SDN). To improve the network performance, the SDN controller has to choose the shortest and optimised path between source and destination in routine and emergency packet transmission. In e-health service, information of the emergency patient has to be transferred immediately to remote hospitals or doctors by using efficient packet routing approach in Wireless Body Area Network (WBAN). In WBAN, to improve the packet transmission, the optimal packet routing policy developed based on packets priority with the support of a greedy algorithm for SDN. The SDN Controller selects the forwarding node based on node propagation delay and available bandwidth between two forwarding nodes. The mesh network topology network created for implementation, implementation results are compared with existing research works. Finally, this algorithm implemented in our institution, Software defined communication testbed laboratory (SDCTestbed Lab) with the support of 13 Zodiac-Fx (Forwarding device), 2 Raspberry-Pi3 B+ Model (host) and Arduino kit (sensor node).</span>