An adaptive‐aware energy and queue improvement of AOMDV

Because the node energy and network resources in the wireless sensor network (WSN) are very finite, it is necessary to distribute data traffic reasonably and achieve network load balancing. Ad hoc on‐demand multipath distance vector (AOMDV) is a widely used routing protocol in WSN, but it has some deficiencies: establishes the route by only using hop counts as the routing criterion without considering other factors such as energy consumption and network load; forwards route request in fixed delay resulting in building the nonoptimal path; and cannot update the path status after built paths. For the deficiency of AOMDV, this paper proposes a multipath routing protocol adaptive energy and queue AOMDV (AEQAOMDV) based on adaptively sensing node residual energy and buffer queue length. When sending a routing request, the forwarding delay of the routing request is adaptively adjusted by both the residual energy and the queue length of the intermediate node; when establishing routes, a fitness is defined as a routing criterion according to the link energy and the queue load, predicting the available duration of the node based on the energy consumption rate and adjusting the weight of the routing criterion by the available duration of the node; after the routes are established, the path information status are updated via periodically broadcasting Hello that carries the path information with the minimum fitness, making the source node update the path information periodically. By using NS‐2, simulations demonstrate that compared with AOMDV, AEQAOMDV has obvious improvements in increasing packet delivery ratio, reducing network routing overhead, reducing route discovery frequency, and decreasing the network delay. And AEQAOMDV is more suitable for WSN.     

e‐LiteSense: Self‐adaptive energy‐aware data sensing in WSN environments

Currently deployed in a wide variety of applicational scenarios, wireless sensor networks (WSNs) are typically a resource‐constrained infrastructure. Consequently, characteristics such as WSN adaptability, low‐overhead, and low‐energy consumption are particularly relevant in dynamic and autonomous sensing environments where the measuring requirements change and human intervention is not viable. To tackle this issue, this article proposes e‐LiteSense as an adaptive, energy‐aware sensing solution for WSNs, capable of auto‐regulate how data are sensed, adjusting it to each applicational scenario. The proposed adaptive scheme is able to maintain the sensing accuracy of the physical phenomena, while reducing the overall process overhead. In this way, the adaptive algorithm relies on low‐complexity rules to establish the sensing frequency weighting the recent drifts of the physical parameter and the levels of remaining energy in the sensor. Using datasets from WSN operational scenarios, we prove e‐LiteSense effectiveness in self‐regulating data sensing accurately through a low‐overhead process where the WSN energy levels are preserved. This constitutes a step‐forward for implementing self‐adaptive energy‐aware data sensing in dynamic WSN environments.     

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 placement and routing strategies for resilient two‐tiered sensor networks

In hierarchical sensor networks using relay nodes, sensor nodes are arranged in clusters and higher powered relay nodes can be used as cluster heads. The lifetime of such a network is determined primarily by the lifetime of the relay nodes. In this paper, we propose two new integer linear programs (ILPs) formulations for optimal data gathering, which maximize the lifetime of the upper tier relay node network. Unlike most previous approaches considered in the literature, our formulations can generate optimal solutions under the non‐flow‐splitting model. Experimental results demonstrate that our approach can significantly extend network lifetime, compared to traditional routing schemes, for the non‐flow‐splitting model. The lifetime can be further enhanced by periodic updates of the routing strategy based on the residual energy at each relay node. The proposed rescheduling scheme can be used to handle single or multiple relay node failures. We have also presented a very simple and straightforward algorithm for the placement of relay nodes. The placement algorithm guarantees that all the sensor nodes can communicate with at least one relay node and that the relay node network is at least 2‐connected. This means that failure of a single relay node will not disconnect the network, and data may be routed around the failed node. The worst case performance of the placement algorithm is bounded by a constant with respect to any optimum placement algorithm. Copyright © 2008 John Wiley & Sons, Ltd.     

Low end‐to‐end delay fuzzy networking protocol for mobile wireless sensing

Because of the practical limitations of the energy and processing capabilities, the deployment of many Wireless Sensor Networks (WSN) is facing two main challenges of increasing network lifetime and reducing End to End Delay (EED) which become critical when the nodes are mobile and use non‐rechargeable energy sources. One way to help to extend network lifetime is using fuzzy logic in a form of artificial intelligence. To this end we propose a new routing protocol for using mobile WSNs, which holds the nodes in an equal level of energy and decreases energy dissipation of the network. An optimum path is selected based on the cost of each node to increase network lifetime. In order to lessen EED, we also attempt to design a novel zoning‐scheme for the network area. In this scheme, zonation is dynamic and works based on the Data Link (DL) position. The simulation result shows a significant improvement in lifetime and EED by proposed protocol compared with existing protocols. Copyright © 2016 John Wiley & Sons, Ltd.     

Capsule network‐based data pruning in wireless sensor networks

The development of the wireless sensor networks (WSN) being deployed among numerous application for its sensing capabilities is increasing at a very fast tread. Its distributed nature and ability to extend communication even to the inaccessible areas beyond communication range that lacks human intervention has made it even more attractive in a wide space of applications. Confined with numerous sensing nodes distributed over a wide area, the WSN incurs certain limitations as it is battery powered. Many developed routing enhancements with power and energy efficiency lacked in achieving the significant improvement in the performance. So, the paper proposes a machine learning system (capsule network) and technique (data pruning) for WSN involved in the real world observations to have knowledge‐based learning from the experience for an intelligent way of handling the dynamic and real environment without the intervention of the humans. The WSN cluster‐based routing aided with capsule network and data pruning proffered in paper enables the WSN to have a prolonged network lifetime, energy efficiency, minimized delay, and enhanced throughput by reducing the energy usage and extending communication within the limited battery availability. The proposed system is validated in the network simulator and compared with the WSN without ML to check for the performance enhancements of the WSN with ML inclusions in terms of quality of service enhancements, network lifetime, packet delivery ratio, and energy to evince the efficacy of the WSN with capsule network‐based data pruning.     

Performance analysis of spectrally efficient amplify‐and‐forward opportunistic relaying scheme for adaptive cooperative wireless systems

In this paper, we propose an adaptive amplify‐and‐forward (AF) relaying scheme that selects the best relay among the available relay nodes opportunistically to cooperate with a source node for improvement of the spectral efficiency. This improvement can be achieved by introducing a policy that gives the useful cooperative regions and defines a switching threshold signal‐to‐noise ratio that guarantees the bit error rate (BER) of cooperative transmission is below the target. We model all links as independent non‐identically distributed Rayleigh fading channels. We then derive closed‐form expressions for the average spectral efficiency, average BER, and outage probability when an upper bound for the signal‐to‐noise ratio of the end‐to‐end relay path is applied and adaptive discrete rate is considered. Numerical and simulation results show that the proposed scheme, compared with the outage‐based AF incremental relaying, AF fixed relaying, and the conventional direct transmission, can achieve the maximum average spectral efficiency while maintaining the average BER and outage probability. Copyright © 2013 John Wiley & Sons, Ltd.     

Energy‐efficient management using a traffic‐oriented routing scheme for cognitive radio networks

This paper elaborates on a traffic manipulation routing scheme that associates the moments of the traffic, targeting the maximization of the energy conservation, as well as the effective resource management of the network nodes. The energy conservation is achieved through the data flow coordination, in association with the data traffic volume and the resource exchange, between the nodes that exploit radio spectrum access in cognitive radio networking architectures. The routing scheme that is proposed in this paper interrelates the backward difference of traffic moments for each node based on a series model, together with the sleep‐time period, towards reflecting this measurement to the minimization of the nodes activity durations to achieve energy conservation. The effective operation of the routing scheme is achieved by exploiting a signalling mechanism that was adopted for the proper communication of the nodes over the available radio spectrum parts, such as the television white spaces. Simulation tests were conducted towards examining the validity of the proposed routing scheme via multiple performance evaluation experiments. Simulation results have shown the offered reliability and the efficiency of the proposed traffic‐aware scheme, in reference to the efficient energy consumption of the networking nodes and the minimization of the delays. Copyright © 2015 John Wiley & Sons, Ltd.     

A simple void node and loop‐free three‐dimensional routing protocol for multi‐hop wireless networks

Wireless networks are now very essential part for modern ubiquitous communication systems. The design of efficient routing and scheduling techniques for such networks have gained importance to ensure reliable communication. Most of the currently proposed geographic routing protocols are designed for 2D spatial distribution of user nodes, although in many practical scenarios user nodes may be deployed in 3D space also. In this paper, we propose 3D routing protocols for multihop wireless networks that may be implemented in two different ways depending on how the routing paths are computed. When the routing paths to different user nodes from the base station in the wireless network are computed by the base station, we call it centralized protocol (3DMA‐CS). A distributed routing (3DMA‐DS) protocol is implemented when respective routing path of each user node to the base station is computed by the user node. In both of these protocols, the user (base station) selects the relay node to forward packets in the direction of destination, from the set of its neighbours, which makes minimum angle with the reference line drawn from user (base station) to the base station (user), within its transmission range. The proposed protocols are free from looping problem and can solve the void node problem (VNP) of multihop wireless networks. Performance analysis of the proposed protocol is shown by calculating end‐to‐end throughput, average path length, end‐to‐end delay, and energy consumption of each routing path through extensive simulation under different network densities and transmission ranges.     

Importance‐based data transmission optimization in multi‐source single‐sink wireless sensor networks

Energy‐efficient routing becomes one of the most critical technologies for sustaining the overall network lifetime of wireless sensor networks. In this paper, we propose a novel data transmission scheme between a number of specified source nodes and the single sink, which can efficiently restrict the usage frequency of each relay node, measured by the number of source nodes using it for data transmission. On the basis of the importance of source nodes that is closely related to deployed location, they form a descending sequence such that each node finds the minimum energy path earlier than the succeeding one. Then, the energy‐efficient multiple path algorithm with the computational complexity of O(n³) is developed for deriving the minimum energy paths, where n is the number of nodes in the network. Also, a polynomial algorithm is presented for deriving the range of the feasible values of N₀ serving as the threshold of the usage frequency of relay nodes, in which each can guarantee the existence of the solution. Further, we theoretically investigate the existence of the solution and the tree‐structured solution using m‐ary tree. Extensive simulation results show that our proposed scheme can achieve significant performance enhancement. Copyright © 2012 John Wiley & Sons, Ltd.     

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.     

Improving physical layer security via cooperative diversity in energy‐constrained cognitive radio networks with multiple eavesdroppers

In this paper, a scheme that exploits cooperative diversity of multiple relays to provide physical layer security against an eavesdropping attack is concerned. Relay‐based cognitive radio network (CRN) faces issues multiple issues other than the same as faced by conventional wireless communications. If the nodes in a CRN are able to harvest energy and then spend less energy than the total energy available, we can ensure a perpetual lifetime for the network. In this paper, an energy‐constrained CRN is considered where relay nodes are able to harvest energy. A cooperative diversity‐based relay and subchannel‐selection algorithm is proposed, which selects a relay and a subchannel to achieve the maximum secrecy rate while keeping the energy consumed under a certain limit. A transmission power factor is also selected by the algorithm, which ensures long‐term operation of the network. The power allocation problem at the selected relay and at the source also satisfies the maximum‐interference constraint with the primary user (PU). The proposed scheme is compared with a variant of the proposed scheme where the relays are assumed to have an infinite battery capacity (so maximum transmission power is available in every time slot) and is compared with a scheme that uses jamming for physical layer security. The simulation results show that the infinite battery‐capacity scheme outperforms the jamming‐based physical layer security scheme, thus validating that cooperative diversity‐based schemes are suitable to use when channel conditions are better employed, instead of jamming for physical layer security.     

Secured routing in wireless sensor networks using fault‐free and trusted nodes

Wireless sensor network (WSN) should be designed such that it is able to identify the faulty nodes, rectify the faults, identify compromised nodes from various security threats, and transmit the sensed data securely to the sink node under faulty conditions. In this paper, we propose an idea of integrating fault tolerance and secured routing mechanism in WSN named as fault tolerant secured routing: an integrated approach (FASRI) that establishes secured routes from source to sink node even under faulty node conditions. Faulty nodes are identified using battery power and interference models. Trustworthy nodes (non‐compromised) among fault‐free nodes are identified by using agent‐based trust model. Finally, the data are securely routed through fault‐free non‐compromised nodes to sink. Performance evaluation through simulation is carried out for packet delivery ratio, hit rate, computation overhead, communication overhead, compromised node detection ratio, end‐to‐end delay, memory overhead, and agent overhead. We compared simulation results of FASRI with three schemes, namely multi‐version multi‐path (MVMP), intrusion/fault tolerant routing protocol (IFRP) in WSN, and active node‐based fault tolerance using battery power and interference model (AFTBI) for various measures and found that there is a performance improvement in FASRI compared with MVMP, IFRP, and AFTBI. Copyright © 2014 John Wiley & Sons, Ltd.     

An efficient weighted trust‐based malicious node detection scheme for wireless sensor networks

The aim of wireless sensor networks (WSNs) is to gather sensor data from a monitored environment. However, the collected or reported information might be falsified by faults or malicious nodes. Hence, identifying malicious nodes in an effective and timely manner is essential for the network to function properly and reliably. Maliciously behaving nodes are usually detected and isolated by reputation and trust‐based schemes before they can damage the network. In this paper, we propose an efficient weighted trust‐based malicious node detection (WT‐MND) scheme that can detect malicious nodes in a clustered WSN. The node behaviors are realistically treated by accounting for false‐positive and false‐negative instances. The simulation results confirm the timely identification and isolation of maliciously behaving nodes by the WT‐MND scheme. The effectiveness of the proposed scheme is afforded by the adaptive trust‐update process, which implicitly performs trust recovery of temporarily malfunctioning nodes and computes a different trust‐update factor for each node depending on its behavior. The proposed scheme is more effective and scalable than the related schemes in the literature, as evidenced by its higher detection ratio (DR) and lower misdetection ratio (MDR), which only slightly vary with the network's size. Moreover, the scheme sustains its efficient characteristics without significant power consumption overheads.     

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.     

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.     

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.     

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.     

LSAPSP: Load distribution‐based slot allocation and path establishment using optimized substance particle selection in sensor networks

Sensor node energy conservation is the primary design parameters in wireless sensor networks (WSNs). Energy efficiency in sensor networks directly prolongs the network lifetime. In the process of route discovery, each node cooperates to forward the data to the base station using multi‐hop routing. But, the nodes nearer to the base station are loaded more than the other nodes that lead to network portioning, packet loss and delay as a result nodes may completely loss its energy during the routing process. To rectify these issues, path establishment considers optimized substance particle selection, load distribution, and an efficient slot allocation scheme for data transmission between the sensor nodes in this paper. The selection of forwarders and conscious multi‐hop path is selected based on the route cost value that is derived directly by taking energy, node degree and distance as crucial metrics. Load distribution based slot allocation method ensures the balance of data traffic and residual energy of the node in areal‐time environment. The proposed LSAPSP simulation results show that our algorithm not only can balance the real‐time environment load and increase the network lifetime but also meet the needs of packet loss and delay.     

ABC algorithm‐based trustworthy energy‐efficient MIMO routing protocol

This paper introduces artificial bee algorithm (ABC)‐based energy‐efficient protocol with security for the enhancement of lifetime of wireless sensor network. A trustworthy energy‐efficient routing MIMO (TEEM) technique is used by implementing MIMO technique in TEER protocol to isolate malicious nodes and to reduce the fading effects and interference in the network. The performance of ABC‐based trustworthy energy‐efficient MIMO routing (ABC‐TEEM) protocol is analysed. Alive node performance, residual energy, throughput analysis, and pocket loss rate of ABC‐TEEM protocol for WSN are computed and compared with the performance of existing TEEM protocol for various diversity orders.