Fuzzy chessboard clustering and artificial bee colony routing method for energy‐efficient heterogeneous wireless sensor networks

Energy is an extremely critical resource for battery‐powered wireless sensor networks (WSNs), thus making energy‐efficient protocol design a key challenging problem. However, uneven energy consumption is an inherent problem in WSNs caused by multi‐hop routing and many‐to‐one traffic pattern among sensors. In this paper, we therefore propose a new clustering method called fuzzy chessboard clustering (FFC), which is capable to overcome the bottleneck problem and addressing the uneven energy consumption problem in heterogeneous WSNs. We also propose an energy‐efficient routing method called artificial bee colony routing method (ABCRM) to find the optimal routing path for the heterogeneous WSNs. ABCRM seeks to investigate the problems of balancing energy consumption and maximization of network lifetime. To demonstrate the effectiveness of FCC‐ABCRM in terms of lessening end‐to‐end delay, balancing energy consumption, and maximization of heterogeneous network lifetime, we compare our method with three approaches namely, chessboard clustering approach, PEGASIS, and LEACH. Simulation results show that the network lifetime achieved by FCC‐ABCRM could be increased by nearly 25%, 45%, and 60% more than that obtained by chessboard clustering, PEGASIS, and LEACH, respectively. Copyright © 2013 John Wiley & Sons, Ltd.     

Actor-oriented directional anycast routing in wireless sensor and actor networks with smart antennas

Current routing protocols in wireless sensor and actor networks (WSANs) shows a lack of unification for different traffic patterns because the communication for sensor to actor and that for actor to actor are designed separately. Such a design poses a challenge for interoperability between sensors and actors. With the presence of rich-resource actor nodes, we argue that to improve network lifetime, the problem transforms from reducing overall network energy consumption to reducing energy consumption of constrained sensor nodes. To reduce energy consumption of sensor nodes, especially in challenging environments with coverage holes/obstacles, we propose that actor nodes should share forwarding tasks with sensor nodes. To enable such a feature, efficient interoperability between sensors and actors is required, and thus a unified routing protocol for both sensors and actors is needed. This paper explores capabilities of directional transmission with smart antennas and rich-resource actors to design a novel unified actor-oriented directional anycast routing protocol (ADA) which supports arbitrary traffic in WSANs. The proposed routing protocol exploits actors as main routing anchors as much as possible because they have better energy and computing power compared to constraint sensor nodes. In addition, a directional anycast routing approach is also proposed to further reduce total delay and energy consumption of overall network. Through extensive experiments, we show that ADA outperforms state-of-the-art protocols in terms of packet delivery latency, network lifetime, and packet reliability. In addition, by offer fault tolerant features, ADA also performs well in challenging environments where coverage holes and obstacles are of concerns.     

A novel residual energy‐based distributed clustering and routing approach for performance study of wireless sensor network

Non‐uniform energy consumption during operation of a cluster‐based routing protocol for large‐scale wireless sensor networks (WSN) is major area of concern. Unbalanced energy consumption in the wireless network results in early node death and reduces the network lifetime. This is because nodes near the sink are overloaded in terms of data traffic compared with the far away nodes resulting in node deaths. In this work, a novel residual energy–based distributed clustering and routing (REDCR) protocol has been proposed, which allows multi‐hop communication based on cuckoo‐search (CS) algorithm and low‐energy adaptive‐clustering–hierarchy (LEACH) protocol. LEACH protocol allows choice of possible cluster heads by rotation at every round of data transmission by a newly developed objective function based on residual energy of the nodes. The information about the location and energy of the nodes is forwarded to the sink node where CS algorithm is implemented to choose optimal number of cluster heads and their positions in the network. This approach helps in uniform distribution of the cluster heads throughout the network and enhances the network stability. Several case studies have been performed by varying the position of the base stations and by changing the number of nodes in the area of application. The proposed REDCR protocol shows significant improvement by an average of 15% for network throughput, 25% for network scalability, 30% for network stability, 33% for residual energy conservation, and 60% for network lifetime proving this approach to be more acceptable one in near future.     

A reliable and energy‐efficient routing protocol for underwater wireless sensor networks

Recently, underwater wireless sensor networks (UWSNs) have attracted much research attention to support various applications for pollution monitoring, tsunami warnings, offshore exploration, tactical surveillance, etc. However, because of the peculiar characteristics of UWSNs, designing communication protocols for UWSNs is a challenging task. Particularly, designing a routing protocol is of the most importance for successful data transmissions between sensors and the sink. In this paper, we propose a reliable and energy‐efficient routing protocol, named R‐ERP²R (Reliable Energy‐efficient Routing Protocol based on physical distance and residual energy). The main idea behind R‐ERP²R is to utilize physical distance as a routing metric and to balance energy consumption among sensors. Furthermore, during the selection of forwarding nodes, link quality towards the forwarding nodes is also considered to provide reliability and the residual energy of the forwarding nodes to prolong network lifetime. Using the NS‐2 simulator, R‐ERP²R is compared against a well‐known routing protocol (i.e. depth‐based routing) in terms of network lifetime, energy consumption, end‐to‐end delay and delivery ratio. The simulation results proved that R‐ERP²R performs better in UWSNs.Copyright © 2012 John Wiley & Sons, Ltd.     

A green cluster‐based routing scheme for large‐scale wireless sensor networks

In wireless sensor networks (WSNs), clustering has been shown to be an efficient technique to improve scalability and network lifetime. In clustered networks, clustering creates unequal load distribution among cluster heads (CHs) and cluster member (CM) nodes. As a result, the entire network is subject to premature death because of the deficient active nodes within the network. In this paper, we present clustering‐based routing algorithms that can balance out the trade‐off between load distribution and network lifetime “green cluster‐based routing scheme.” This paper proposes a new energy‐aware green cluster‐based routing algorithm to preventing premature death of large‐scale dense WSNs. To deal with the uncertainty present in network information, a fuzzy rule‐based node classification model is proposed for clustering. Its primary benefits are flexibility in selecting effective CHs, reliability in distributing CHs overload among the other nodes, and reducing communication overhead and cluster formation time in highly dense areas. In addition, we propose a routing scheme that balances the load among sensors. The proposed scheme is evaluated through simulations to compare our scheme with the existing algorithms available in the literature. The numerical results show the relevance and improved efficiency of our scheme.     

Optimal load balanced clustering in homogeneous wireless sensor networks

Balancing the load among sensor nodes is a major challenge for the long run operation of wireless sensor networks. When a sensor node becomes overloaded, the likelihood of higher latency, energy loss, and congestion becomes high. In this paper, we propose an optimal load balanced clustering for hierarchical cluster‐based wireless sensor networks. We formulate the network design problem as mixed‐integer linear programming. Our contribution is 3‐fold: First, we propose an energy aware cluster head selection model for optimal cluster head selection. Then we propose a delay and energy‐aware routing model for optimal inter‐cluster communication. Finally, we propose an equal traffic for energy efficient clustering for optimal load balanced clustering. We consider the worst case scenario, where all nodes have the same capability and where there are no ways to use mobile sinks or add some powerful nodes as gateways. Thus, our models perform load balancing and maximize network lifetime with no need for special node capabilities such as mobility or heterogeneity or pre‐deployment, which would greatly simplify the problem. We show that the proposed models not only increase network lifetime but also minimize latency between sensor nodes. Numerical results show that energy consumption can be effectively balanced among sensor nodes, and stability period can be greatly extended using our models.     

A new algorithm for cluster head selection in LEACH protocol for wireless sensor networks

In wireless sensor network, a large number of sensor nodes are distributed to cover a certain area. Sensor node is little in size with restricted processing power, memory, and limited battery life. Because of restricted battery power, wireless sensor network needs to broaden the system lifetime by reducing the energy consumption. A clustering‐based protocols adapt the use of energy by giving a balance to all nodes to become a cluster head. In this paper, we concentrate on a recent hierarchical routing protocols, which are depending on LEACH protocol to enhance its performance and increase the lifetime of wireless sensor network. So our enhanced protocol called Node Ranked–LEACH is proposed. Our proposed protocol improves the total network lifetime based on node rank algorithm. Node rank algorithm depends on both path cost and number of links between nodes to select the cluster head of each cluster. This enhancement reflects the real weight of specific node to success and can be represented as a cluster head. The proposed algorithm overcomes the random process selection, which leads to unexpected fail for some cluster heads in other LEACH versions, and it gives a good performance in the network lifetime and energy consumption comparing with previous version of LEACH protocols.     

Double Cluster Based Energy Efficient Routing Protocol for Wireless Sensor Network

Reducing the energy consumption of sensor nodes and prolonging the life of the network is the central topic in the research of wireless sensor network (WSN) protocol. The low-energy adaptive clustering hierarchy (LEACH) is one of the hierarchical routing protocols designed for communication in WSNs. LEACH is clustering based protocol that utilizes randomized rotation of local cluster-heads to evenly distribute the energy load among the sensors in the network. But LEACH is based on the assumption that each sensor nodes contain equal amount of energy which is not valid in real scenarios. A developed routing protocol named as DL-LEACH is proposed. The DL-LEACH protocol cluster head election considers residual energy of nodes, distance from node to the base station and neighbor nodes, which makes cluster head election reasonable and node energy consumption balance. The simulation results of proposed protocols are compared for its network life time in MATLAB with LEACH protocol. The DL-LEACH is prolong the network life cycle by 75 % than LEACH.     

EOMR: An Energy-Efficient Optimal Multi-path Routing Protocol to Improve QoS in Wireless Sensor Network for IoT Applications

The wireless sensor network based IoT applications mainly suffers from end to end delay, loss of packets during transmission, reduced lifetime of sensor nodes due to loss of energy. To address these challenges, we need to design an efficient routing protocol that not only improves the network performance but also enhances the Quality of Service. In this paper, we design an energy-efficient routing protocol for wireless sensor network based IoT application having unfairness in the network with high traffic load. The proposed protocol considers three-factor to select the optimal path, i.e., lifetime, reliability, and the traffic intensity at the next-hop node. Rigorous simulation has been performed using NS-2. Also, the performance of the proposed protocol is compared with other contemporary protocols. The results show that the proposed protocol performs better concerning energy saving, packet delivery ratio, end-to-end delay, and network lifetime compared to other protocols.

     

Implementation of depth‐based routing and its enhancement in AquaSim–Next Generation for underwater wireless sensor networks

In the last decade, underwater wireless sensor networks have been widely studied because of their peculiar aspects that distinguish them from common terrestrial wireless networks. Their applications range from environmental monitoring to military defense. The definition of efficient routing protocols in underwater sensor networks is a challenging topic of research because of the intrinsic characteristics of these networks, such as the need of handling the node mobility and the difficulty in balancing the energy consumed by the nodes. Depth‐based routing protocol is an opportunistic routing protocol for underwater sensor networks, which provides good performance both under high and low node mobility scenarios. The main contribution of our work is presenting a novel simulator for studying depth‐based routing protocol and its variants as well as novel routing protocols. Our simulator is based on AquaSim–Next Generation, which is a specialized tool for studying underwater networks. With our work, we improve the state of the art of underwater routing protocol simulators by implementing, among other features, a detailed cross‐layer communication and an accurate model of the operational modes of acoustic modem and their energy consumption. The simulator is open source and freely downloadable. Moreover, we propose a novel and completely distributed routing protocol, named residual energy–depth‐based routing. It takes into account the residual energy at the nodes' batteries to select the forwarder nodes and improve the network lifetime by providing a more uniform energy consumption among them. We compare its performance with that of depth‐based routing protocol and a receiver‐based routing protocol implementing a probabilistic opportunistic forwarding scheme.     

An Energy-Efficient Routing Protocol for Event-Driven Dense Wireless Sensor Networks

The routing energy efficiency of a wireless sensor network is a crucial issue for the network lifetime. In this article, we propose MICRO (MInimum Cost Routing with Optimized data fusion), an energy-efficient routing protocol for event-driven dense wireless sensor networks. The proposed routing protocol is an improvement over the formerly proposed LEACH and PEGASIS protocol, which is designed to be implemented mainly with node computations rather than mainly with node communications. Moreover, in the routing computation the proposed scheme exploits a new cost function for energy balancing among sensor nodes, and uses an iterative scheme with optimized data fusions to compute the minimum-cost route for each event-detecting sensor node. Compared to the PEGASIS routing protocol, MICRO substantially improves the energy-efficiency of each route, by optimizing the trade-off between minimization of the total energy consumption of each route and the balancing of the energy state of each sensor node. It is demonstrated that the proposed protocol is able to outperform the LEACH and the PEGASIS protocols with respect to network lifetime by 100–300% and 10–100%, respectively.     

A Novel Energy Efficient and Lifetime Maximization Routing Protocol in Wireless Sensor Networks

The energy consumption is a key design criterion for the routing protocols in wireless sensor networks (WSN). Some of the conventional single path routing schemes may not be optimal to maximize the network lifetime and connectivity. Thus, multipath routing schemes is an optimal alternative to extend the lifetime of WSN. Multipath routing schemes distribute the traffic across multiple paths instead of routing all the traffic along a single path. In this paper, we propose a multipath Energy-Efficient data Routing Protocol for wireless sensor networks (EERP). The latter keeps a set of good paths and chooses one based on the node state and the cost function of this path. In EERP, each node has a number of neighbours through which it can route packets to the base station. A node bases its routing decision on two metrics: state and cost function. It searches its Neighbours Information Table for all its neighbours concerned with minimum cost function. Simulation results show that our EERP protocol minimizes and balances the energy consumption well among all sensor nodes and achieves an obvious improvement on the network lifetime.     

An Improved Fuzzy Unequal Clustering Algorithm for Wireless Sensor Network

This paper introduces IFUC, which is an Improved Fuzzy Unequal Clustering scheme for large scale wireless sensor networks (WSNs).It aims to balance the energy consumption and prolong the network lifetime. Our approach focuses on energy efficient clustering scheme and inter-cluster routing protocol. On the one hand, considering each node’s local information such as energy level, distance to base station and local density, we use fuzzy logic system to determine each node’s chance of becoming cluster head and estimate the cluster head competence radius. On the other hand, we use Ant Colony Optimization (ACO) method to construct the energy-aware routing between cluster heads and base station. It reduces and balances the energy consumption of cluster heads and solves the hot spots problem that occurs in multi-hop WSN routing protocol to a large extent. The validation experiment results have indicated that the proposed clustering scheme performs much better than many other methods such as LEACH, CHEF and EEUC.     

An intelligent and knowledge‐based overlapping clustering protocol for wireless sensor networks

Overlapping is one of the topics in wireless sensor networks that is considered by researchers in the last decades. An appropriate overlapping management system can prolong network lifetime and decrease network recovery time. This paper proposes an intelligent and knowledge‐based overlapping clustering protocol for wireless sensor networks, called IKOCP. This protocol uses some of the intelligent and knowledge‐based systems to construct a robust overlapping strategy for sensor networks. The overall network is partitioned to several regions by a proposed multicriteria decision‐making controller to monitor both small‐scale and large‐scale areas. Each region is managed by a sink, where the whole network is managed by a base station. The sensor nodes are categorized by various clusters using the low‐energy adaptive clustering hierarchy (LEACH)‐improved protocol in a way that the value of p is defined by a proposed support vector machine–based mechanism. A proposed fuzzy system determines that noncluster heads associate with several clusters in order to manage overlapping conditions over the network. Cluster heads are changed into clusters in a period by a suggested utility function. Since network lifetime should be prolonged and network traffic should be alleviated, a data aggregation mechanism is proposed to transmit only crucial data packets from cluster heads to sinks. Cluster heads apply a weighted criteria matrix to perform an inner‐cluster routing for transmitting data packets to sinks. Simulation results demonstrate that the proposed protocol surpasses the existing methods in terms of the number of alive nodes, network lifetime, average time to recover, dead time of first node, and dead time of last node.     

基于最优簇头数的无线传感器网络安全LEACH路由协议

提出一种基于最优簇头数的无线传感器网络安全LEACH路由协议,该协议模拟真实传感器网络情况建立了三维空间模型,通过理论分析和仿真实验方法得到LEACH协议的最优簇头数,使网络能耗达到最优。在能量优化的同时把增强安全性作为设计目标,根据LEACH协议的特点,采用预置共享密钥对的方法,在簇头选举和数据传输阶段采用在数据包尾部捎带加密信息的方法,实现数据加密,在只增加少量能量开销的情况下数据机密性得到了实现。仿真验证了新协议的有效性,在能量优化的同时提高了路由安全性,延长了网络生命期。     

A Sink-Oriented Layered Clustering Protocol for Wireless Sensor Networks

Clustering is an effective technique to prolong network lifetime for energy-constrained wireless sensor networks. Due to the many-to-one traffic pattern in a multi-hop network, the nodes closer to the sink also help to relay data for those farther away from the sink, and hence they consume much more energy and tend to die faster. This paper proposes a sink-oriented layered clustering (SOLC) protocol to better balance energy consumption among nodes with different distances to the sink. In SOLC, the sensor field is divided into concentric rings, and the SOLC protocol consists of intra-ring clustering and inter-ring routing. We compute the optimal ring width and the numbers of cluster heads in different rings to balance energy consumption between intra-cluster data processing and inter-cluster data relaying. Cluster heads in a ring closer to the sink has smaller sizes than those in the rings farther away from the sink, and hence they can spend less energy for intra-cluster data processing and more energy for inter-cluster data relay. Simulation results show that the SOLC protocol can outperform several existing clustering protocols in terms of improved network lifetime.     

A Genetic‐Algorithm‐Based Optimized Clustering for Energy‐Efficient Routing in MWSN

With the increasing demands for mobile wireless sensor networks in recent years, designing an energy‐efficient clustering and routing protocol has become very important. This paper provides an analytical model to evaluate the power consumption of a mobile sensor node. Based on this, a clustering algorithm is designed to optimize the energy efficiency during cluster head formation. A genetic algorithm technique is employed to find the near‐optimal threshold for residual energy below which a node has to give up its role of being the cluster head. This clustering algorithm along with a hybrid routing concept is applied as the near‐optimal energy‐efficient routing technique to increase the overall efficiency of the network. Compared to the mobile low energy adaptive clustering hierarchy protocol, the simulation studies reveal that the energy‐efficient routing technique produces a longer network lifetime and achieves better energy efficiency.     

A Centralized Balance Clustering Routing Protocol for Wireless Sensor Network

Routing protocol plays a role of great importance in the performance of wireless sensor networks (WSNs). A centralized balance clustering routing protocol based on location is proposed for WSN with random distribution in this paper. In order to keep clustering balanced through the whole lifetime of the network and adapt to the non-uniform distribution of sensor nodes, we design a systemic algorithm for clustering. First, the algorithm determines the cluster number according to condition of the network, and adjusts the hexagonal clustering results to balance the number of nodes of each cluster. Second, it selects cluster heads in each cluster base on the energy and distribution of nodes, and optimizes the clustering results to minimize energy consumption. Finally, it allocates suitable time slots for transmission to avoid collision. Simulation results demonstrate that the proposed protocol can balance the energy consumption and improve the network throughput and lifetime significantly.     

Energy‐aware geographic routing in wireless sensor networks with anchor nodes

Energy efficiency has become an important design consideration in geographic routing protocols for wireless sensor networks because the sensor nodes are energy constrained and battery recharging is usually not feasible. However, numerous existing energy‐aware geographic routing protocols are energy‐inefficient when the detouring mode is involved in the routing. Furthermore, most of them rarely or at most implicitly take into account the energy efficiency in the advance. In this paper, we present a novel energy‐aware geographic routing (EAGR) protocol that attempts to minimize the energy consumption for end‐to‐end data delivery. EAGR adaptively uses an existing geographic routing protocol to find an anchor list based on the projection distance of nodes for guiding packet forwarding. Each node holding the message utilizes geographic information, the characteristics of energy consumption, and the metric of advanced energy cost to make forwarding decisions, and dynamically adjusts its transmission power to just reach the selected node. Simulation results demonstrate that our scheme exhibits higher energy efficiency, smaller end‐to‐end delay, and better packet delivery ratio compared to other geographic routing protocols. Copyright © 2011 John Wiley & Sons, Ltd.     

Secure coverage-preserving node scheduling scheme using energy prediction for wireless sensor networks

With the fast development of the micro-electro-mechanical systems(MEMS),wireless sensor networks(WSNs)have been extensively studied.Most of the studies focus on saving energy consumption because of restricted energy supply in WSNs.Cluster-based node scheduling scheme is commonly considered as one of the most energy-efficient approaches.However,it is not always so efficient especially when there exist hot spot and network attacks in WSNs.In this article,a secure coverage-preserved node scheduling scheme for WSNs based on energy prediction is proposed in an uneven deployment environment.The scheme is comprised of an uneven clustering algorithm based on arithmetic progression,a cover set partition algorithm based on trust and a node scheduling algorithm based on energy prediction.Simulation results show that network lifetime of the scheme is 350 rounds longer than that of other scheduling algorithms.Furthermore,the scheme can keep a high network coverage ratio during the network lifetime and achieve the designed objective which makes energy dissipation of most nodes in WSNs balanced.