ArticlePDF Available

NADEEM: Neighbor-node Approaching Distinct Energy Efficient Mates for reliable data delivery in IoT enabled underwater WSNs

Authors:

Abstract and Figures

In this research work we propose three schemes: neighbor node approaching distinct energy efficient mates (NADEEM), fallback approach NADEEM (FA-NADEEM) and transmission adjustment NADEEM (TA-NADEEM). In NADEEM, immutable forwarder node selection is avoided with the help of three distinct selection parameters. Void hole is avoided using fallback recovery mechanism to deliver data successfully at the destination. The transmission range is dynamically adjusted to resume greedy forwarding among the network nodes. The neighbor node is only eligible to become forwarder when it is not a void node. Additionally, linear programming based feasible regions are computed for an optimal energy dissipation and to improve network throughput. Extensive simulations are conducted for three parameters: energy, packet delivery ratio (PDR) and fraction of void nodes. Further, an analysis is performed by varying transmission range and data rate for energy consumption and fraction of void node. The results clearly depict that our proposed schemes outperform the baseline scheme (GEDAR) in terms of energy consumption and fraction of void nodes.
Content may be subject to copyright.
A preview of the PDF is not available
... Another article in which introduced the approach for reliable data delivery underwater. The neighbor node approaches distinct energy efficient mates (NADEEM) [17] with two invariants like fallback and transmission. Both these are following the greedy approach to forwarding the data among the nodes of the network. ...
... In order to calculate the achievable regions inside the network in an optimized manner, we used a linear programming approach in this section. To obtain the optimal result, the mathematical technique linear programming is used as same as [17]. The objective function that we analyzed through linear programming, minimum energy consumption, and maximum throughput is discussed in Figures 10 and 11. ...
... The proposed scheme of calculation of the maximum throughput is the bandwidth assigned for the next forwarder node in the case of empty regions and is in Equation (23) such that 'B_frwˆn' and for non-forwarding node is 'B_(N-frw)ˆn'. The overall bandwidth is calculated for the aforementioned equations are below where bandwidth is assigned for 150-300 KHz as from [17]. ...
Article
Full-text available
The Internet of Things (IoT) is an emerging technology in underwater communication because of its potential to monitor underwater activities. IoT devices enable a variety of applications such as submarine and navy defense systems, pre-disaster prevention, and gas/oil exploration in deep and shallow water. The IoT devices have limited power due to their size. Many routing protocols have been proposed in applications, as mentioned above, in different aspects, but timely action and energy make these a challenging task for marine research. Therefore, this research presents a routing technique with three sub-sections, Tri-Angular Nearest Vector-Based Energy Efficient Routing (TANVEER): Layer-Based Adjustment (LBA-TANVEER), Data Packet Delivery (DPD-TANVEER), and Binary Inter Nodes (BIN-TANVEER). In TANVEER, the path is selected between the source node and sonobuoys by computing the angle three times with horizontal, vertical, and diagonal directions by using the nearest vector-based approach to avoid the empty nodes/region. In order to deploy the nodes, the LBA-TANVEER is used. Furthermore, for successful data delivery, the DPD-TANVEER is responsible for bypassing any empty nodes/region occurrence. BIN-TANVEER works with new watchman nodes that play an essential role in the path/data shifting mechanism. Moreover, achievable empty regions are also calculated by linear programming to minimize energy consumption and throughput maximization. Different evaluation parameters perform extensive simulation, and the coverage area of the proposed scheme is also presented. The simulated results show that the proposed technique outperforms the compared baseline scheme layer-by-layer angle-based flooding (L2-ABF) in terms of energy, throughput, Packet Delivery Ratio (PDR) and a fraction of empty regions.
... The sensor nodes have limited energy resources, therefore, the SFNs robustness decreases due to the nodes' failure. Many researchers study the methods to increase the lifetime of nodes [15][16][17][18][19][20][21][22][23][24][25][26][27][28][29][30][31]. ...
... Variable attacks in this study are performed by randomly selecting the number of removed nodes in the range of 1 to 10. The number of nodes in the MCS 24 Thesis by: Muhammad Usman is calculated after each attack. Due to multiple nodes are randomly removed, therefore, the effect on network connectivity with multiple nodes removal in a single instant is analyzed. ...
Thesis
Full-text available
During the past few decades, the Internet of Things (IoT) has made remarkable progress in many real-world applications including healthcare, military, transportation, etc. Multiple sensor nodes are deployed in these _elds to get the required data. Different network topologies are used in IoT and scale-free is one of them. It is mostly preferred due to its robust behavior against random node removal, however, the network collapsed because of malicious attacks. Therefore, in this thesis, robustness of the scale-free networks is enhanced against malicious attacks through optimization. To achieve this, the edge's degree and nodes' distance based edge swap operations are used in the proposed Improved Scale-Free Networks (ISFNs) scheme. In the edge's degree based operation, nodes of similar degrees are linked. Moreover, the connections of the nearest nodes are made in distance based edge swap. These operations help to achieve a better onion-like structure without changing the degree distribution of the network. Therefore, the network becomes robust against malicious attacks. Moreover, no new links or nodes are added in the optimization process, therefore, no extra cost is incurred. Furthermore, to make the network more robust against realistic attacks, the variable attacks are considered. Simulation results of the proposed scheme are compared with ROSE and Simulated Annealing (SA) for different number of nodes. The proposed scheme outperforms the existing techniques for different numbers of nodes and against the low degree, high degree and random attacks. Moreover, ISFNs has 13% and 23% better network robustness as compared to ROSE and SA, respectively. Network Topology Evolution Scheme (NTES) is proposed to prevent the scale-free networks from random and malicious attacks. In this scheme, the network field is divided into two parts with uniformly distributed nodes. After the network's evolution, the nodes are linked with each other through one-to-many correspondence. The division of the network field is made by considering that a network is robust if its size is small. Moreover, to study the hierarchical changes in the degree of nodes, k-core decomposition is used. In addition, nodes' degrees and core based attacks are performed on the network to evaluate the performance of the proposed scheme. Furthermore, the network robustness is analyzed using three optimization techniques: Artificial Bee Colony (ABC), Bacterial Foraging Optimization (BFO) and Genetic Algorithm (GA). The techniques are compared with each other and a technique that efficiently optimizes the network to increase the robustness is selected. In the optimization process, we make use of three edge swap methods. Due to the edge swap, the network robustness is enhanced without changing the degree distribution, so the addition of nodes/links is not required to increase the robustness. Furthermore, NTES is compared with Barabasi Albert (BA) model and Hill Climbing (HC) algorithm against random and malicious attacks. The simulation results show that the proposed NTES optimized using GA outperforms BA and HC by 46.90% and 57.08%, respectively, in terms of robustness. In addition, the network robustness of Scale Free Networks (SFNs) is enhanced against the malicious attacks. For that purpose, initially, a parameterless optimization algorithm JAYA is used because it requires less computational efforts as compared to the heuristic techniques. Then, as the edge swap plays an important role to enhance the robustness of SFNs, therefore, the edge swaps are classified into three categories. For each category, effects on the network's topological parameters such as average shortest path length, assortativity and clustering coefficient are analyzed. Next, the robustness is enhanced with the addition of nodes in the maximum connected subgraphs and the protection of bridge edges maintain the network connectivity. Moreover, optimized network is analyzed for different attack strengths. In simulations, the comparison of JAYA is made with two existing algorithms: ROSE and Simulated Annealing (SA). The network optimized by JAYA has a better robustness against random and malicious attacks, as compared to the existing algorithms. Furthermore, among the edge swap categories, the degree dependent edge swap is better to increase the robustness of SFNs. Moreover, the addition of nodes into the maximum connected subgraphs enhances the robustness and the protection of bridge edges ensures the network connectivity in all the algorithms. Furthermore, the robustness against different attack strengths are analyzed and the results show that high attacks strength paralyzed the network more efficiently.
... Different types of protocols are proposed for optimal route finding including the geographic routing [3], fuzzy routing [4], transmission adjustment routing [5], etc. The geographic routing is also referred as position based routing that provides services, e.g., content-centric networking and location-aware services. ...
Article
Full-text available
In the above article [1], reference [2] is updated and the missing DOI is provided. In Section IV “Proposed System Model” of the article, a two-point distance formula is added which is taken from [3]. The text is updated as follows: “In order to send the sensed data, the OSN follows the shortest path. The OSN finds the shortest distance between itself and nearby SN using the x and y coordinates. As we have deployed a two-dimensional (2D) network. So, the above-mentioned distance is being calculated with the help of the two-point distance formula:
... Different types of protocols are proposed for optimal route finding including the geographic routing [3], fuzzy routing [4], transmission adjustment routing [5], etc. The geographic routing is also referred as position based routing that provides services, e.g., content-centric networking and locationaware services. ...
Article
Full-text available
Wireless Sensor Internet of Things (WSIoTs) face various challenges such as unreliable data communication, less cost efficiency, security issues and high energy consumption due to their deployment in hostile and unattended environments. Moreover, the node's rapid energy dissipation due to the void holes and imbalanced network deployment has a bad impact on the network performance. To overcome the aforementioned issues, a blockchain based trust model for WSIoTs is proposed in this paper. Moreover, the Dijkstra algorithm is used to propose a routing protocol for performing efficient communication between network nodes while simultaneously avoiding void holes between ordinary sensor nodes and a sink node. Furthermore, to provide transparency in the network, all the transactions performed by the nodes are recorded in the blockchain in an immutable manner. Moreover, the Proof of Authority (PoA) consensus algorithm is used to validate and add the transactions in the blocks. Besides, a distributed platform, known as interplanetary file system, is used in WSIoTs for reliable and cost-effective storage. The simulation results show that PoA performs 13% better than proof of work consensus algorithm. The proposed routing protocol and trust model are validated in terms of gas consumption, throughput, nodes' status and energy consumption.
... An important characteristic of the IoT-WSNs is that they are operational even in hostile environments [31]. The nodes in the WSNs are used for efficient data delivery towards the destination [32][33][34]. However, due to limited energy resources of the nodes [35][36][37][38][39], their communication capability, lifetime [40][41][42], etc., are greatly compromised. ...
Thesis
Full-text available
Nowadays, the Internet of Things (IoT) provides benefits to humans in numerous domains by empowering the projects of smart cities, healthcare, industrial enhancement and so forth. The IoT networks include nodes, which deliver the data towards their destination. However, the removal of nodes due to malicious attacks affects the connectivity of the nodes in the networks. The ideal plan is to construct a topology, which maintains the nodes' connectivity after the attacks and subsequently increases the network robustness. Therefore, in this thesis, werst adopt two different mechanisms for the construction of a robust scale-free network. Initially, a Multi-Population Genetic Algorithm (MPGA) is used to overcome the premature convergence in GA. Then, an entropy based mechanism is used, which replaces the first solution of high entropy population with the best solution of low entropy population to improve the network robustness. Second, two types of edge swap mechanisms are introduced. The Efficiency based Edge Swap Mechanism (EESM) selects the pair of edges with high efficiency to increase the network robustness. The second edge swap mechanism named EESM-Assortativity transforms the network topology into an onion-like structure to achieve maximum connectivity between similar degree nodes in the network. The optimization of the network robustness is performed using Hill Climbing (HC) and Simulated Annealing (SA) methods. The simulation results show that the proposed MPGA Entropy has 9% better network robustness as compared to MPGA. Moreover, the proposed ESMs effectively increase the network robustness with an average of 15% better robustness as compared to HC and SA. Furthermore, they also increase the graph density as well as network's connectivity with high computational cost. Furthermore, we design a robust network to support the nodes' functionality for the topology optimization in the scale-free IoT networks. It is because the computational complexity of an optimization process increases the cost of the network. Therefore, in this thesis, the main objective is to reduce the computational cost of the network with the aim of constructing a robust network topology. Thus, four solutions are presented to reduce the computational cost of the network. First, a Smart Edge Swap Mechanism (SESM) is proposed to overcome the excessive randomness of the standard Random Edge Swap Mechanism (RESM). Second, a threshold based node removal method is introduced to reduce the operation of the edge swap mechanism when an objective function converges at a point. Third, multiple attacks are performed in the network to find the correlation among the measures, which are degree, betweenness and closeness centralities. Fourth, based on the third solution, the Heat Map Centrality (HMC) is introduced that finds the set of most important nodes from the network. The HMC damages the network by utilizing the information of two positively correlated measures. It helps to provide a good attack strategy for robust optimization. The simulation results demonstrate the efficacy of the proposed SESM mechanism. It outperforms the existing RESM mechanism by almost 4% better network robustness and 10% less number of swaps. Moreover, 64% removal of nodes helps to reduce the computational cost of the network. In addition, we also perform topology optimization using a new heuristic algorithm, named as Great Deluge Algorithm (GDA). Afterwards, four rewiring strategies are designed. The first strategy is based on the degree dissortativity, which performs rewiring if maximum connectivity among similar degree nodes is achieved. In second strategy, we propose a degree difference operation using degree dissortativity to make sure that the connected edges possess low dissortativity and degree difference. Whereas the other two strategies consider nodes' load capacity as well as improved GDA to maximize the network robustness. The effectiveness of the proposed rewiring strategies is evaluated through simulations. The results prove that the proposed strategies increase the network robustness up to 25% as compared to HC and SA algorithms. Besides, the strategies are also very effective in increasing the graph density and network connectivity. However, their computational time is high as compared to HC and SA.
... The sensor nodes have limited energy resources, therefore, the Scale-Free Networks (SFNs) robustness decreases due to the nodes' failure. Many researchers study the methods to increase the lifetime of nodes [15][16][17][18][19][20][21][22][23][24][25][26][27][28][29][30][31]. ...
Research Proposal
Full-text available
In this synopsis, robustness of the Scale-Free Networks (SFNs) is enhanced against malicious attacks through optimization. To achieve this, the edge’s degree and nodes’ distance based edge swap operations are used in the proposed Improved Scale-Free Networks (ISFNs) scheme. In the edge’s degree based operation, nodes of similar degrees are linked. Moreover, connections of the nearest nodes are made in distance based edge swap. These operations help to achieve a better onion-like structure without changing the degree distribution of the network. Therefore, the network becomes robust against malicious attacks. Furthermore, to make the network robust against realistic attacks, the variable attacks are considered. Apart from that, a Network Topology Evolution Scheme (NTES) is proposed to prevent SFNs from random and malicious attacks. In this scheme, the network field is divided into two parts with uniformly distributed nodes. After the network’s evolution, the nodes are linked with each other through one-to-many correspondence. The division of the network field is made by considering that a network is robust if its size is small. Moreover, to study the hierarchical changes in the degree of nodes, k-core decomposition is used. In addition, nodes’ degrees and core based attacks are performed on the network to evaluate the performance of the proposed scheme. Furthermore, the network robustness is analyzed using three optimization techniques: Artificial Bee Colony (ABC), Bacterial Foraging Optimization (BFO) and Genetic Algorithm (GA). The techniques are compared with each other and a technique that efficiently optimizes the network to increase the robustness is selected. In the optimization process, we make use of three edge swap methods. Due to the edge swap, the network robustness is enhanced without changing the degree distribution, so the addition of nodes/links is not required to increase the robustness. In addition, the network robustness of SFNs is enhanced against the malicious attacks. For that purpose, initially, a parameterless optimization algorithm JAYA is used because it requires less computational efforts as compared to the heuristic techniques. Then, as the edge swap plays an important role to enhance the robustness of SFNs, therefore, the edge swaps are classified into three categories. For each category, effects on the network’s topological parameters such as average shortest path length, assortativity and clustering coefficient are analyzed. Next, the robustness is enhanced with the addition of nodes in the maximum connected subgraphs and the protection of bridge edges maintain the network connectivity. Moreover, optimized network is analyzed for different attack strengths.
... Therefore, the IoT network faces many issues, which capture the interest of researchers to improve its efficiency. The last few decades have been quite active in IoT research, which resulted in a huge amount of proposals for various routing protocols [5], [6], security models [7], [8] and clustering techniques [9] that provide secure and trustful communication in the IoT networks. However, IoT networks are always threatened to be compromised by the external nodes, which mislead the networks by sending false data for their benefit. ...
Article
Full-text available
Internet of Things (IoT) is an emerging domain in which different devices communicate with each other through minimum human intervention. IoT devices are usually operated in hostile and unattended environments. Moreover, routing in current IoT architecture becomes inefficient due to malicious and unauthenticated nodes' existence, minimum network lifetime, insecure routing, etc. This paper proposes a lightweight blockchain based authentication mechanism where ordinary sensors' credentials are stored. As IoT nodes have a short lifespan due to energy depletion, few credentials are stored in the blockchain to achieve lightweight authentication. Moreover, the route calculation is performed by a genetic algorithm enabled software defined network controller, which is also used for on-demand routing to optimize the energy consumption of the nodes in the IoT network. Furthermore, a route correctness mechanism is proposed to check the existence of malicious nodes in the calculated route. Moreover, a detection mechanism is proposed to restrict the malicious nodes' activities, while a malicious node's list is maintained in the blockchain, which is used in the route correctness mechanism. The proposed model is evaluated by performing intensive simulations. The effectiveness of the proposed model is depicted in terms of gas consumption, which shows the optimized utilization of resources. The residual energy of the network shows optimized route calculation, while the malicious node detection method shows the number of packets dropped.
... However, the greedy forwarding approach is not suitable for immutable forwarder node selection, which causes premature depletion of the node's battery and creates a void hole [4]. These void holes (usually created near the sink) in the network cause limited network lifetime, unnecessary delays, data packet losses, and throughput and network connection problems, as in NADEEM [5]. Another reason for a void hole in the network is the continuous and random movement of nodes in the I-UWSAN that cannot be neglected [6]. ...
Article
In the task of data routing in Internet of Things enabled volatile underwater environments, providing better transmission and maximizing network communication performance are always challenging. Many network issues such as void holes and network isolation occur because of long routing distances between nodes. Void holes usually occur around the sink because nodes die early due to the high energy consumed to forward packets sent and received from other nodes. These void holes are a major challenge for I‐UWSANs and cause high end‐to‐end delay, data packet loss, and energy consumption. They also affect the data delivery ratio. Hence, this paper presents an energy efficient watchman based flooding algorithm to address void holes. First, the proposed technique is formally verified by the Z‐Eves toolbox to ensure its validity and correctness. Second, simulation is used to evaluate the energy consumption, packet loss, packet delivery ratio, and throughput of the network. The results are compared with well‐known algorithms like energy‐aware scalable reliable and void‐hole mitigation routing and angle based flooding. The extensive results show that the proposed algorithm performs better than the benchmark techniques.
... Thus more effort are made to create and control WSNs in harsh environments where overcoming routing holes is typical. Several protocols have been proposed to solve the void hole problem in underwater WSNs, which is due to frequent topology changes (nodes moving around because of water flows) and signal attenuation and long delay [31][32][33][34]. Also, in [35] a virtual force based routing strategy is proposed to handle the energy hole problem, while in [36] a routing algorithm is created to overcome dynamic holes. ...
Article
Full-text available
A quest for geographic routing schemes of wireless sensor networks when sensor nodes are deployed in areas with obstacles has resulted in numerous ingenious proposals and techniques. However, there is a lack of solutions for complicated cases wherein the source or the sink nodes are located close to a specific hole, especially in cavern-like regions of large complex-shaped holes. In this paper, we propose a geographic routing scheme to deal with the existence of complicated-shape holes in an effective manner. Our proposed routing scheme achieves routes around holes with the (1+ϵ\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\epsilon$$\end{document})-stretch. Experimental results show that our routing scheme yields the highest load balancing and the most extended network lifetime compared to other well-known routing algorithms as well.
Article
nternet of Things (IoT) is an emerging domain in which different devices communicate with each other through minimum human intervention. IoT devices are usually operated in hostile and unattended environments. Moreover, routing in current IoT architecture becomes inefficient due to malicious and unauthenticated nodes' existence, minimum network lifetime, insecure routing, etc. This paper proposes a lightweight blockchain based authentication mechanism where ordinary sensors' credentials are stored. As IoT nodes have a short lifespan due to energy depletion, few credentials are stored in the blockchain to achieve lightweight authentication. Moreover, the route calculation is performed by a genetic algorithm enabled software defined network controller, which is also used for on-demand routing to optimize the energy consumption of the nodes in the IoT network. Furthermore, a route correctness mechanism is proposed to check the existence of malicious nodes in the calculated route. Moreover, a detection mechanism is proposed to restrict the malicious nodes' activities, while a malicious node's list is maintained in the blockchain, which is used in the route correctness mechanism. The proposed model is evaluated by performing intensive simulations. The effectiveness of the proposed model is depicted in terms of gas consumption, which shows the optimized utilization of resources. The residual energy of the network shows optimized route calculation, while the malicious node detection method shows the number of packets dropped.nternet of Things (IoT) is an emerging domain in which different devices communicate with each other through minimum human intervention. IoT devices are usually operated in hostile and unattended environments. Moreover, routing in current IoT architecture becomes inefficient due to malicious and unauthenticated nodes' existence, minimum network lifetime, insecure routing, etc. This paper proposes a lightweight blockchain based authentication mechanism where ordinary sensors' credentials are stored. As IoT nodes have a short lifespan due to energy depletion, few credentials are stored in the blockchain to achieve lightweight authentication. Moreover, the route calculation is performed by a genetic algorithm enabled software defined network controller, which is also used for on-demand routing to optimize the energy consumption of the nodes in the IoT network. Furthermore, a route correctness mechanism is proposed to check the existence of malicious nodes in the calculated route. Moreover, a detection mechanism is proposed to restrict the malicious nodes' activities, while a malicious node's list is maintained in the blockchain, which is used in the route correctness mechanism. The proposed model is evaluated by performing intensive simulations. The effectiveness of the proposed model is depicted in terms of gas consumption, which shows the optimized utilization of resources. The residual energy of the network shows optimized route calculation, while the malicious node detection method shows the number of packets dropped.I
Article
Full-text available
With a wide scope for exploration and research, underwater wireless sensor network (UWSN) is a fast growing research area in current scenario. UWSNs need energy efficient designing approach because underwater sensor nodes are battery driven. Also the deployed batteries can not be easily recharged by non-conventional energy resources like solar energies. Clustering is an effective technique to design an energy efficient UWSNs. Due to the sparse deployment of nodes and dynamic nature of the channel, the clustering characteristics of UWSNs are different from those of terrestrial wireless sensor networks (TWSNs). In this paper, we focused on optimal clustering for UWSNs which are compliant with any one of the acoustic, free space optical (FSO) and electromagnetic (EM) wave based communication techniques. Besides, we proposed an energy dissipation model of sensor node for FSO and EM wave based communication and compared with contemporary energy dissipation model for acoustic based communication. In particular, the suitability of the above three techniques for underwater communication is investigated and their performance is compared on the basis of energy consumption and optimal clustering.
Article
Full-text available
In Underwater Linear Sensor Networks (UW-LSN) routing process, nodes without proper address make it difficult to determine relative sensor details specially the position of the node. In addition, it effects to determine the exact leakage position with minimized delay for long range underwater pipeline monitoring. Several studies have been made to overcome the mentioned issues. However, little attention has been given to minimize communication delay using dynamic addressing schemes. This paper presents the novel solution called Hop-by-Hop Dynamic Addressing based Routing Protocol for Pipeline Monitoring (H2-DARP-PM) to deal with nodes addressing and communication delay. H2-DARP-PM assigns a dynamic hop address to every participating node in an efficient manner. Dynamic addressing mechanism employed by H2-DARP-PM differentiates the heterogeneous types of sensor nodes thereby helping to control the traffic flows between the nodes. The proposed dynamic addressing mechanism provides support in the selection of an appropriate next hop neighbour. Simulation results and analytical model illustrate that H2-DARP-PM addressing support distribution of topology into different ranges of heterogeneous sensors and sinks to mitigate the higher delay issue. One of the distinguishing characteristics of H2-DARP-PM has the capability to operate with a fewer number of sensor nodes deployed for long-range underwater pipeline monitoring.
Article
Full-text available
Due to limited energy resources, energy balancing becomes an appealing requirement/ challenge in Underwater Wireless Sensor Networks (UWSNs). In this paper, we present a Balanced Load Distribution (BLOAD) scheme to avoid energy holes created due to unbalanced energy consumption in UWSNs. Our proposed scheme prolongs the stability period and lifetime of the UWSNs. In BLOAD scheme, data (generated plus received) of underwater sensor nodes is divided into fractions. The transmission range of each sensor node is logically adjusted for evenly distributing the data fractions among the next hop neighbor nodes. Another distinct feature of BLOAD scheme is that each sensor node in the network sends a fraction of data directly to the sink by adjusting its transmission range and continuously reports data to the sink till its death even if an energy hole is created in its next hop region. We implement the BLOAD scheme, by varying the fractions of data using adjustable transmission ranges in homogeneous and heterogeneous simulation environments. Simulation results show that the BLOAD scheme outperforms the selected existing schemes in terms of stability period and network lifetime.
Article
Full-text available
Most existing deployment algorithms for event coverage in underwater wireless sensor networks (UWSNs) usually do not consider that network communication has non-uniform characteristics on three-dimensional underwater environments. Such deployment algorithms ignore that the nodes are distributed at different depths and have different probabilities for data acquisition, thereby leading to imbalances in the overall network energy consumption, decreasing the network performance, and resulting in poor and unreliable late network operation. Therefore, in this study, we proposed an uneven cluster deployment algorithm based network layered for event coverage. First, according to the energy consumption requirement of the communication load at different depths of the underwater network, we obtained the expected value of deployment nodes and the distribution density of each layer network after theoretical analysis and deduction. Afterward, the network is divided into multilayers based on uneven clusters, and the heterogeneous communication radius of nodes can improve the network connectivity rate. The recovery strategy is used to balance the energy consumption of nodes in the cluster and can efficiently reconstruct the network topology, which ensures that the network has a high network coverage and connectivity rate in a long period of data acquisition. Simulation results show that the proposed algorithm improves network reliability and prolongs network lifetime by significantly reducing the blind movement of overall network nodes while maintaining a high network coverage and connectivity rate.
Article
In this paper, to monitor the fields with square and circular geometries, three energy-efficient routing protocols are proposed for underwater wireless sensor networks (UWSNs). First one is, sparsity-aware energy efficient clustering (SEEC), second one is, circular SEEC (CSEEC), and the third one is, circular depth based SEEC (CDSEEC) routing protocol. All three protocols are proposed to minimize the energy consumption of sparse regions. Whereas, sparsity search algorithm (SSA) is proposed to find sparse regions and density search algorithm (DSA) is used to find dense regions of the network field. Moreover, clustering is performed in dense regions to minimize redundant transmissions of a data packet. While, sinks mobility is exploited to collect data from sensor nodes with an objective of minimum energy consumption. A depth threshold (d th) value is also used to minimize number of hops between source and destination for less energy consumption. Simulation results show that our schemes perform better than their counterpart schemes (DBR, EEDBR) in terms of energy efficiency.
Article
In duty-cycled wireless sensor networks running asynchronous MAC protocols, the time when a sender waits for its receiver to wake up and receive the packet is the major source of energy consumption. Opportunistic routing can reduce the sender wait time by allowing multiple candidate receivers, but by doing that it suffers from redundant packet forwarding due to multiple receivers waking up at the same time. Thus, number of forwarders should be controlled in a way that overall forwarding cost is minimized considering both sender wait time and cost of redundant packet forwarding. Also, in order to prolong network lifetime, candidate forwarders should be selected so that load is balanced among nodes. We propose ORR, an opportunistic routing protocol that addresses the two issues. First, optimal number of forwarders is calculated based on forwarding cost estimation, which is derived from duty cycle and network topology. Second, the metric used for selecting forwarders considers residual energy so that more traffic is guided through nodes with larger remaining energy. The resulting routing protocol is proven to avoid loops and shown to achieve longer network lifetime compared to other protocols regardless of duty cycle and network topology.
Article
The concentration of data traffic toward sink makes sensor nodes nearby have heavier communication burden and more quickly use up their energy, leading to energy hole problem. Sink mobility can realize load balancing data delivery by changing the hotspots around the sink as the sink moves. However, sink mobility also brings about the problem of localization of sink. Frequently broadcasting of mobile sinks' position will generate significant overhead. In this paper, we propose a novel heterogeneous adaptive relay chain routing protocol with a few mobile relay nodes, which is applied to large-scale 1-D long chain network. Mobile relay node is the sink of local subnetwork. The protocol achieves the following performances. First, through scheduled movement of the mobile relay nodes, load balancing is achieved not only among sensor nodes but also among high tier relay nodes in continuous data delivery model. Second, in the context of clock synchronization among nodes, every node decides its operating state by algorithm stored in its own processor. So, there is no need for advertisement of mobile relay nodes' location. Only a few messages for clock synchronization among nodes are needed. Third, by synthetically utilizing node deployment strategy and routing protocol, base station can real-time monitoring residual energy of sensor nodes for timely maintenance, which can extend the protocol to be suitable for event-driven and query-driven data delivery models. Finally, the performances are evaluated via extensive simulations.