Assimilation of fuzzy clustering approach and EHO‐Greedy algorithm for efficient routing in WSN

The problems related to energy consumption and improvement of the network lifetime of WSN (wireless sensor network) have been considered. The base station (BS) location is the main concern in WSN. BSs are fixed, yet, they have the ability to move in some situations to collect the information from sensor nodes (SNs). Recently, introducing mobile sinks to WSNs has been proved to be an efficient way to extend the lifespan of the network. This paper proposes the assimilation of the fuzzy clustering approach and the Elephant Herding Optimization (EHO)‐Greedy algorithm for efficient routing in WSN. This work considers the separate sink nodes of a fixed sink and movable sink to decrease the utilization of energy. A fixed node is deployed randomly across the network, and the movable sink node moves to different locations across the network for collecting the data. Initially, the number of nodes is formed into the multiple clusters using the enhanced expectation maximization algorithm. After that, the cluster head (CH) selection done through a fuzzy approach by taking the account of three factors of residual energy, node centrality, and neighborhood overlap. A suitable collection of CH can extremely reduce the utilization of energy and also enhancing the lifespan. Finally, the routing protocol of the hybrid EHO‐Greedy algorithm is used for efficient data transmission. Simulation results display that the proposed technique is better to other existing approaches in regard to energy utilization and the system lifetime.     

Fish bone structure based data aggregation and routing in wireless sensor network: multi-agent based approach

Wireless sensor networks (WSNs) are constrained by limited node (device) energy, low network bandwidth, high communication overhead and latency. Data aggregation alleviates the constraints of WSN. In this paper, we propose a multi-agent based homogeneous temporal data aggregation and routing scheme based on fish bone structure of WSN nodes by employing a set of static and mobile agents. The primary components of fishbone structure are backbone and ribs connected to both sides of a backbone. A backbone connects a sink node and one of the sensor nodes on the boundary of WSN through intermediate sensor nodes. Our aggregation scheme operates in the following steps. (1) Backbone creation and identifying master centers (or nodes) on it by using a mobile agent based on parameters such as Euclidean distance, residual energy, backbone angle and connectivity. (2) Selection of local centers (or nodes) along the rib of a backbone connecting a master center by using a mobile agent. (3) Local aggregation process at local centers by considering nodes along and besides the rib, and delivering to a connected master center. (4) Master aggregation process along the backbone from boundary sensor node to the sink node by using a mobile agent generated by a boundary sensor node. The mobile agent aggregates data at visited master centers and delivers to the sink node. (5) Maintenance of fish bone structure of WSN nodes. The performance of the scheme is simulated in various WSN scenarios to evaluate the effectiveness of the approach by analyzing the performance parameters such as master center selection time, local center selection time, aggregation time, aggregation ratio, number of local and master centers involved in the aggregation process, number of isolated nodes, network lifetime and aggregation energy. We observed that our scheme outperforms zonal based aggregation scheme.     

Fair data collection in wireless sensor networks: analysis and protocol

In general, wireless sensor networks (WSNs) consist of many sensors which transmit data to a central node, called the sink, possibly over multiple hops. This many-to-one data routing paradigm leads to nonuniform traffic distribution for the different sensors (e.g., nodes closer to the sink transfer more traffic than those farther away). In this paper, we perform an analysis of the fairness issue by presenting a tree-based WSN and derive the throughput, delay, and energy distribution for each sensor under the fairness constraint. Based on the analysis, we design our fair data collection protocol in which each node decides its media access and packet forwarding strategies in a distributed manner. Finally, we demonstrate the effectiveness of our solution through simulations. The results for the proposed protocol show the accuracy of the analysis and show that the protocol ensures the fair delivery of packets and reduces end-to-end delay. Based on the analysis, we also quantitatively determine the energy required for each of the nodes and show that a nonuniform energy distribution can maximize the network lifetime for the WSN scenario under study.     

Cluster-Head Restricted Energy Efficient Protocol (CREEP) for Routing in Heterogeneous Wireless Sensor Networks

A magnanimous number of collaborative sensor nodes make up a Wireless Sensor Network (WSN). These sensor nodes are outfitted with low-cost and low-power sensors. The routing protocols are responsible for ensuring communications while considering the energy constraints of the system. Achieving a higher network lifetime is the need of the hour in WSNs. Currently, many network layer protocols are considering a heterogeneous WSN, wherein a certain number of the sensors are rendered higher energy as compared to the rest of the nodes. In this paper, we have critically analysed the various stationary heterogeneous clustering algorithms and assessed their lifetime and throughput performance in mobile node settings also. Although many newer variants of Distributed Energy-Efficiency Clustering (DEEC) scheme execute proficiently in terms of energy efficiency, they suffer from high system complexity due to computation and selection of large number of Cluster Heads (CHs). A protocol in form of Cluster-head Restricted Energy Efficient Protocol (CREEP) has been proposed to overcome this limitation and to further improve the network lifetime by modifying the CH selection thresholds in a two-level heterogeneous WSN. Simulation results establish that proposed solution ameliorates in terms of network lifetime as compared to others in stationary as well as mobile WSN scenarios.     

Energy Efficient Energy Hole Repelling (EEEHR) Algorithm for Delay Tolerant Wireless Sensor Network

Reducing energy consumption and increasing network lifetime are the major concerns in Wireless Sensor Network (WSN). Increase in network lifetime reduces the frequency of recharging and replacing batteries of the sensor node. The key factors influencing energy consumption are distance and number of bits transmitted inside the network. The problem of energy hole and hotspot inside the network make neighbouring nodes unusable even if the node is efficient for data transmission. Energy Efficient Energy Hole Repelling (EEEHR) routing algorithm is developed to solve the problem. Smaller clusters are formed near the sink and clusters of larger size are made with nodes far from the sink. This methodology promotes equal sharing of load repelling energy hole and hotspot issues. The opportunity of being a Cluster Head (CH) is given to a node with high residual energy, very low intra cluster distance in case of nodes far away from the sink and very low CH to sink distance for the nodes one hop from the sink. The proposed algorithm is compared with LEACH, LEACH-C and SEP routing protocol to prove its novel working. The proposed EEEHR routing algorithm provides improved lifetime, throughput and less packet drop. The proposed algorithm also reduces energy hole and hotspot problem in the network.     

Flower pollination algorithm‐based energy‐efficient stable clustering approach for WSNs

The advances in the size, cost of deployment, and user‐friendly interface of wireless sensor devices have given rise to many wireless sensor network (WSN) applications. WSNs need to use protocols for transmitting data samples from event regions to sink through minimum cost links. Clustering is a commonly used method of data aggregation in which nodes are organized into groups to reduce energy consumption. Nonetheless, cluster head (CH) has to bear an additional load in clustering protocols to organize different activities within the cluster. Proper CH selection and load balancing using efficient routing protocol is therefore a critical aspect for WSN's long‐term operation. In this paper, a threshold‐sensitive energy‐efficient cluster‐based routing protocol based on flower pollination algorithm (FPA) is proposed to extend the network's stability period. Using FPA, multihop communication between CHs and base station is used to achieve optimal link costs for load balancing distant CHs and energy minimization. Analysis and simulation results show that the proposed algorithm significantly outperforms competitive clustering algorithms in terms of energy consumption, stability period, and system lifetime.     

Wheel Based Event Triggered Data Aggregation and Routing in Wireless Sensor Networks: Agent Based Approach

Event triggered data aggregation and routing minimizes the amount of energy and bandwidth required to transmit the data from the event affected area. This paper proposes a Wheel based Event Triggered data aggregation and routing (WETdar) scheme in Wireless Sensor Networks (WSNs) by employing a set of static and mobile agents. A wheel with spokes is constructed by WSN nodes around an event node (a sensor node where an event occurs). Gathering and aggregation of the information is performed along the spokes of a wheel in Spoke Aggregator (SA) nodes and sent to an event node, which routes to a sink node. Spoke generation and identification of SA nodes along the spokes is performed by using a mobile agent, based on parameters such as Euclidean distance, residual energy, spoke angle and connectivity. Mobile agent and its clones discover multiple paths to a sink node from an event node. The scheme is simulated in various WSN scenarios to evaluate the effectiveness of the approach. The performance parameters analyzed are number of SAs, SA selection time, aggregation time, aggregation energy, energy consumption, number of isolated nodes and network life time. We observed that proposed scheme outperforms as compared to the existing aggregation scheme.     

Relocation routing for energy balancing in mobile sensor networks

Wireless sensor networks (WSNs) have been widely investigated in the past decades because of its applicability in various extreme environments. As sensors use battery, most works on WSNs focus on energy efficiency issues (e.g., local energy balancing problems) in statically deployed WSNs. Few works have paid attention to the global energy balancing problem for the scenario that mobile sensor nodes can move freely. In this paper, we propose a new routing protocol called global energy balancing routing protocol (GEBRP) based on an active network framework and node relocation in mobile sensor networks. This protocol achieves global energy efficiency by repairing coverage holes and replacing invalid nodes dynamically. Simulation and experiment results demonstrate that the proposed GEBRP achieves superior performance over the existing scheme. In addition, we analyze the delay performance of GEBRP and study how the delay performance is affected by various system parameters.Copyright © 2013 John Wiley & Sons, Ltd.     

Improved low energy adaptive clustering hierarchy and its optimum cluster head selection

ABSTRACT

Wireless sensor networks (WSNs) play a vital role in present-day world, which are being used in different types of applications and occupy an important part in networking domain. The main objective of WSNs is to sense and collect the information from a given area of interest and provide the gathered data to the sink. WSN comprises of number of sensor nodes with batteries of limited energy for communication and computational activities, which are not possible to recharge the batteries after their deployment in the region of interest. Therefore, saving battery energy and utilising the limited power to the optimum level for extending network lifetime became the main factor of WSN. Hence, optimum cluster head (CH) selection will make the network to support longer lifetime and balanced energy consumption during its lifetime. Our proposed protocol selects the optimum CH and found out to be more efficient than the existing low energy adaptive clustering hierarchy. The simulated output shows better network lifetime and in some other performance metric.     

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.     

A cluster‐based fault‐tolerant routing protocol for wireless sensor networks

Energy conservation and fault tolerance are two critical issues in the deployment of wireless sensor networks (WSNs). Many cluster‐based fault‐tolerant routing protocols have been proposed for energy conservation and network lifetime maximization in WSNs. However, these protocols suffer from high frequency of re‐clustering as well as extra energy consumption to tolerate failures and consider only some very normal parameters to form clusters without any verification of the energy sufficiency for data routing. Therefore, this paper proposes a cluster‐based fault‐tolerant routing protocol referred as CFTR. This protocol allows higher energy nodes to become Cluster Heads (CHs) and operate multiple rounds to diminish the frequency of re‐clustering. Additionally, for the sake to get better energy efficiency and balancing, we introduce a cost function that considers during cluster formation energy cost from sensor node to CH, energy cost from CH to sink, and another significant parameter, namely, number of cluster members in previous round. Further, the proposed CFTR takes care of nodes, which have no CH in their communication range. Also, it introduces a routing algorithm in which the decision of next hop CH selection is based on a cost function conceived to select routes with sufficient energy for data transfer and distribute uniformly the overall data‐relaying load among the CHs. As well, a low‐overhead algorithm to tolerate the sudden failure of CHs is proposed. We perform extensive simulations on CFTR and compare their results with those of two recent existing protocols to demonstrate its superiority in terms of different metrics.     

A boolean spider monkey optimization based energy efficient clustering approach for WSNs

Wireless sensor network (WSN) consists of densely distributed nodes that are deployed to observe and react to events within the sensor field. In WSNs, energy management and network lifetime optimization are major issues in the designing of cluster-based routing protocols. Clustering is an efficient data gathering technique that effectively reduces the energy consumption by organizing nodes into groups. However, in clustering protocols, cluster heads (CHs) bear additional load for coordinating various activities within the cluster. Improper selection of CHs causes increased energy consumption and also degrades the performance of WSN. Therefore, proper CH selection and their load balancing using efficient routing protocol is a critical aspect for long run operation of WSN. Clustering a network with proper load balancing is an NP-hard problem. To solve such problems having vast search area, optimization algorithm is the preeminent possible solution. Spider monkey optimization (SMO) is a relatively new nature inspired evolutionary algorithm based on the foraging behaviour of spider monkeys. It has proved its worth for benchmark functions optimization and antenna design problems. In this paper, SMO based threshold-sensitive energy-efficient clustering protocol is proposed to prolong network lifetime with an intend to extend the stability period of the network. Dual-hop communication between CHs and BS is utilized to achieve load balancing of distant CHs and energy minimization. The results demonstrate that the proposed protocol significantly outperforms existing protocols in terms of energy consumption, system lifetime and stability period.     

DR-NAP: Data reduction strategy using neural adaptation phenomenon in wireless sensor networks

Internet of Things (IoT) has got significant popularity among the researchers' community as they have been applied in numerous application domains. Most of the IoT applications are implemented with the help of wireless sensor networks (WSNs). These WSNs use different sensor nodes with a limited battery power supply. Hence, the energy of the sensor node is considered as one of the primary constraints of WSN. Besides, data communication in WSN dissipates more energy than processing the data. In most WSNs applications, the sensed data generated from the same location sensor nodes are identical or time-series/periodical data. This redundant data transmission leads to more energy consumption. To reduce the energy consumption, a data reduction strategy using neural adaptation phenomenon (DR-NAP) has been proposed to decrease the communication energy in routing data to the BS in WSN. The neural adaptation phenomenon has been utilized for designing a simple data reduction scheme to decrease the amount of data transmitted. In this way, the sensor node energy is saved and the lifetime of the network is enhanced. The proposed approach has been implanted in the existing gravitational search algorithm (GSA)-based clustered routing for WSN. The sensed data are transmitted to CH and BS using DR-NAP. Real sensor data from the Intel Berkeley Research lab have been used for conducting the experiments. The experiment results show 47.82% and 51.96% of improvement in network lifetime when compared with GSA-based clustered routing and clustering scheme using Canada Geese Migration Principle (CS-CGMP) for routing, respectively.     

MiniTE: data acquisition routing for wireless sensor networks

Routing is one of the most important supporting parts in wireless sensor networks (WSNs) application that directly affects the application efficiency. Routing time and energy consumption are two major factors used to evaluate WSNs routing. This article proposes a minimum routing time and energy consumption (MiniTE) routing, which can ensure feasibility of the routing protocol both in routing time and energy consumption. Based on the MiniTE, WSNs can be partitioned into different regions according to the received signal strength indication (RSSI). Messages are sent by nodes in the region to their parent node and again up to their parent node until finally to the sink node. Theoretic evaluation and simulation results are given to verify the features of the protocol.     

A grid based clustering and routing algorithm for solving hot spot problem in wireless sensor networks

Energy conservation of the sensor nodes is the most important issue that has been studied extensively in the design of wireless sensor networks (WSNs). In many applications, the nodes closer to the sink are overburdened with huge traffic load as the data from the entire region are forwarded through them to reach the sink. As a result, their energy gets exhausted quickly and the network is partitioned. This is commonly known as hot spot problem. Moreover, sensor nodes are prone to failure due to several factors such as environmental hazards, battery exhaustion, hardware damage and so on. However, failure of cluster heads (CHs) in a two tire WSN is more perilous. Therefore, apart from energy efficiency, any clustering or routing algorithm has to cope with fault tolerance of CHs. In this paper, we address the hot spot problem and propose grid based clustering and routing algorithms, combinedly called GFTCRA (grid based fault tolerant clustering and routing algorithms) which takes care the failure of the CHs. The algorithms follow distributed approach. We also present a distributed run time management for all member sensor nodes of any cluster in case of failure of their CHs. The routing algorithm is also shown to tolerate the sudden failure of the CHs. The algorithms are tested through simulation with various scenarios of WSN and the simulation results show that the proposed method performs better than two other grid based algorithms in terms of network lifetime, energy consumption and number of dead sensor nodes.     

Stable-Aware Evolutionary Routing Protocol for Wireless Sensor Networks

In real life scenario for wireless sensor networks (WSNs), energy heterogeneity among the sensor nodes due to uneven terrain, connectivity failure, and packet dropping is a crucial factor that triggered the race for developing robust and reliable routing protocols. Prolonging the time interval before the death of the first sensor node, viz. the stability period, is critical for many applications where the feedback from the WSN must be reliable. Although Low Energy Adaptive Clustering Hierarchy (LEACH) and LEACH-like protocols are fundamental and popular clustering protocols to manage the system’s energy and thus to prolong the lifespan of the network, they assume a near to a perfect energy homogeneous system where a node failure, drainage and re-energizing are typically not considered. More recent protocols like Stable Election Protocol (SEP) considers the reverse, i.e., energy heterogeneity, and properly utilizes the extra energy to guarantee a stable and reliable performance of the network system. While paradigms of computational intelligence such as evolutionary algorithms (EAs) have attracted significant attention in recent years to address various WSN’s challenges such as nodes deployment and localization, data fusion and aggregation, security and routing, they did not (to the best of our knowledge) explore the possibility of maintaining heterogeneous-aware energy consumption to guarantee a reliable and robust routing protocol design. By this, a new protocol named stable-aware evolutionary routing protocol (SAERP), is proposed in this paper to ensure maximum stability and minimum instability periods for both homogeneous/heterogeneous WSNs. SAERP introduces an evolutionary modeling, where the cluster head election probability becomes more efficient, to well maintain balanced energy consumption in both energy homogeneous and heterogeneous settings. The performance of SAERP over simulation for 90 WSNs is evaluated and compared to well known LEACH and SEP protocols. We found that SAERP is more robust and always ensures longer stability period and shorter instability period.     

Tree‐based channel assignment schemes for multi‐channel wireless sensor networks

Many sensor node platforms used for establishing wireless sensor networks (WSNs) can support multiple radio channels for wireless communication. Therefore, rather than using a single radio channel for whole network, multiple channels can be utilized in a sensor network simultaneously to decrease overall network interference, which may help increase the aggregate network throughput and decrease packet collisions and delays. This method, however, requires appropriate schemes to be used for assigning channels to nodes for multi‐channel communication in the network. Because data generated by sensor nodes are usually delivered to the sink node using routing trees, a tree‐based channel assignment scheme is a natural approach for assigning channels in a WSN. We present two fast tree‐based channel assignment schemes (called bottom up channel assignment and neighbor count‐based channel assignment) for multi‐channel WSNs. We also propose a new interference metric that is used by our algorithms in making decisions. We validated and evaluated our proposed schemes via extensive simulation experiments. Our simulation results show that our algorithms can decrease interference in a network, thereby increasing performance, and that our algorithms are good alternatives for static channel assignment in WSNs. Copyright © 2015 John Wiley & Sons, Ltd.     

Adaptive energy aware cluster-based routing protocol for wireless sensor networks

Wireless sensor networks (WSNs) have grown excessively due to their various applications and low installation cost. In WSN, the main concern is to reduce energy consumption among nodes while maintaining timely and reliable data forwarding. However, most of the existing energy aware routing protocols incur unbalanced energy consumption, which results in inefficient load balancing and compromised network lifetime. Therefore, the main target of this research paper is to present adaptive energy aware cluster-based routing (AECR) protocol for improving energy conservation and data delivery performance. Our proposed AECR protocol differs from other energy efficient routing schemes in some aspects. Firstly, it generates balance sized clusters based on nodes distribution and avoids random clusters formation. Secondly, it optimizes both intra-cluster and inter-cluster routing paths for improving data delivery performance while balancing data traffic on constructed forwarding routes and at the end, in order to reduce the excessive energy consumption and improving load distribution, the role of Cluster Head (CH) is shifted dynamically among nodes by exploit of network conditions. Simulation results demonstrate that AECR protocol outperforms state of the art in terms of various performance metrics.

     

Extending the Lifetime of Wireless Sensor Networks Through Mobile Relays

We investigate the benefits of a heterogeneous architecture for wireless sensor networks (WSNs) composed of a few resource rich mobile relay nodes and a large number of simple static nodes. The mobile relays have more energy than the static sensors. They can dynamically move around the network and help relieve sensors that are heavily burdened by high network traffic, thus extending the latter's lifetime. We first study the performance of a large dense network with one mobile relay and show that network lifetime improves over that of a purely static network by up to a factor of four. Also, the mobile relay needs to stay only within a two-hop radius of the sink. We then construct a joint mobility and routing algorithm which can yield a network lifetime close to the upper bound. The advantage of this algorithm is that it only requires a limited number of nodes in the network to be aware of the location of the mobile relay. Our simulation results show that one mobile relay can at least double the network lifetime in a randomly deployed WSN. By comparing the mobile relay approach with various static energy-provisioning methods, we demonstrate the importance of node mobility for resource provisioning in a WSN.      

Energy Efficient Cluster Based Routing Protocol Using Charged System Harmony Search Algorithm in WSN

In general, Wireless Sensor Networks (WSNs) is developed with a group of distributed and locative sensor nodes for sensing different environmental conditions. The primary challenges faced by WSN are: low network time and transmission data delay. In crucial applications like monitoring the ecosystem, military and disaster management, and data routing, the incorporation of WSN is very critical. Henceforth, a Low-Energy Adaptive Clustering Hierarchy (LEACH) protocol was proposed but it was found to be uneconomical for energy management. Also, the optimization of Cluster Head (CH) is considered as NP hard problem. This research work deals the issues in optimal path selection in routing of wireless sensor networks to increase the network lifetime. Various techniques are available in metaheuristics, such as the Charged System Search (CSS), that effectively used to resolve the routing problem. Despite of this, most of the meta-heuristics suffer from local optima issues. A charged system search and harmony search algorithm based routing protocol is presented in this research work. Experimental results present the efficient performance of proposed HS model with increased cluster structures, improved network lifetime and reduced end-to-end delay and average packet loss rate.