ELDC: An Artificial Neural Network Based Energy-Efficient and Robust Routing Scheme for Pollution Monitoring in WSNs

[EN] The range of applications of Wireless Sensor Networks (WSNs) is increasing continuously despite of their serious constraints of the sensor nodes¿ resources such as storage, processing capacity, communication range and energy. The main issues in WSN are the energy consumption and the delay in relaying data to the Sink node. This becomes extremely important when deploying a big number of nodes, like the case of industry pollution monitoring. We propose an artificial neural network based energy-efficient and robust routing scheme for WSNs called ELDC. In this technique, the network is trained on huge data set containing almost all scenarios to make the network more reliable and adaptive to the environment. Additionally, it uses group based methodology to increase the life-span of the overall network, where groups may have different sizes. An artificial neural network provides an efficient threshold values for the selection of a group's CN and a cluster head based on back propagation technique and allows intelligent, efficient, and robust group organization. Thus, our proposed technique is highly energy-efficient capable to increase sensor nodes¿ lifetime. Simulation results show that it outperforms LEACH protocol by 42 percent, and other state-of-the-art protocols by more than 30 percent.Mehmood, A.; Lv, Z.; Lloret, J.; Umar, MM. (2020). ELDC: An Artificial Neural Network Based Energy-Efficient and Robust Routing Scheme for Pollution Monitoring in WSNs. IEEE Transactions on Emerging Topics in Computing. IEEE TETC. 8(1):106-114. https://doi.org/10.1109/TETC.2017.26718471061148

Unified clustering and communication protocol for wireless sensor networks

In this paper we present an energy-efficient cross layer protocol for providing application specific reservations in wireless senor networks called the “Unified Clustering and Communication Protocol ” (UCCP). Our modular cross layered framework satisfies three wireless sensor network requirements, namely, the QoS requirement of heterogeneous applications, energy aware clustering and data forwarding by relay sensor nodes. Our unified design approach is motivated by providing an integrated and viable solution for self organization and end-to-end communication is wireless sensor networks. Dynamic QoS based reservation guarantees are provided using a reservation-based TDMA approach. Our novel energy-efficient clustering approach employs a multi-objective optimization technique based on OR (operations research) practices. We adopt a simple hierarchy in which relay nodes forward data messages from cluster head to the sink, thus eliminating the overheads needed to maintain a routing protocol. Simulation results demonstrate that UCCP provides an energy-efficient and scalable solution to meet the application specific QoS demands in resource constrained sensor nodes. Index Terms — wireless sensor networks, unified communication, optimization, clustering and quality of service

On demand multicast routing in wireless sensor networks

The wireless networking environment presents imposing challenges to the study of broadcasting and multicasting problems. Developing an algorithm to optimize communication amongst a group of spatially distributed sensor nodes in a WSN (Wireless Sensor Network) has been met with a number challenges due to the characterization of the sensor node device. These challenges include, but are not limited to: energy, memory, and throughput constraints. The traditional approach to overcome these challenges have emphasised the development of low power electronics, efficient modulation, coding, antenna design etc., it has been recognised that networking techniques can also have a strong impact on the energy efficiency of such systems. A variety of networking based approaches to energy efficiency are possible. One of the well-known approaches is to apply clustering techniques to effectively establish an ordered connection of sensor nodes whilst improving the overall network lifetime. This paper proposes an improved clustering based multicast approach that allows any cluster head to be a multicast source with an unlimited number of subscribers, to optimize group communication in WSNs whilst ensuring sensor nodes do not deprecate rapidly in energy levels. We review several clustering approaches and examine multicast versus broadcast communication in WSNs

On Prolonging Network Lifetime through Load-Similar Node Deployment in Wireless Sensor Networks

This paper is focused on the study of the energy hole problem in the Progressive Multi-hop Rotational Clustered (PMRC)-structure, a highly scalable wireless sensor network (WSN) architecture. Based on an analysis on the traffic load distribution in PMRC-based WSNs, we propose a novel load-similar node distribution strategy combined with the Minimum Overlapping Layers (MOL) scheme to address the energy hole problem in PMRC-based WSNs. In this strategy, sensor nodes are deployed in the network area according to the load distribution. That is, more nodes shall be deployed in the range where the average load is higher, and then the loads among different areas in the sensor network tend to be balanced. Simulation results demonstrate that the load-similar node distribution strategy prolongs network lifetime and reduces the average packet latency in comparison with existing nonuniform node distribution and uniform node distribution strategies. Note that, besides the PMRC structure, the analysis model and the proposed load-similar node distribution strategy are also applicable to other multi-hop WSN structures

An Energy-Aware Routing Protocol in Wireless Sensor Networks

The most important issue that must be solved in designing a data gathering algorithm for wireless sensor networks (WSNS) is how to save sensor node energy while meeting the needs of applications/users. In this paper, we propose a novel energy-aware routing protocol (EAP) for a long-lived sensor network. EAP achieves a good performance in terms of lifetime by minimizing energy consumption for in-network communications and balancing the energy load among all the nodes. EAP introduces a new clustering parameter for cluster head election, which can better handle the heterogeneous energy capacities. Furthermore, it also introduces a simple but efficient approach, namely, intra-cluster coverage to cope with the area coverage problem. We use a simple temperature sensing application to evaluate the performance of EAP and results show that our protocol significantly outperforms LEACH and HEED in terms of network lifetime and the amount of data gathered

On demand multicast routing in wireless sensor networks

The wireless networking environment presents imposing challenges to the study of broadcasting and multicasting problems. Developing an algorithm to optimize communication amongst a group of spatially distributed sensor nodes in a WSN (Wireless Sensor Network) has been met with a number challenges due to the characterization of the sensor node device. These challenges include, but are not limited to: energy, memory, and throughput constraints. The traditional approach to overcome these challenges have emphasised the development of low power electronics, efficient modulation, coding, antenna design etc., it has been recognised that networking techniques can also have a strong impact on the energy efficiency of such systems. A variety of networking based approaches to energy efficiency are possible. One of the well-known approaches is to apply clustering techniques to effectively establish an ordered connection of sensor nodes whilst improving the overall network lifetime. This paper proposes an improved clustering based multicast approach that allows any cluster head to be a multicast source with an unlimited number of subscribers, to optimize group communication in WSNs whilst ensuring sensor nodes do not deprecate rapidly in energy levels. We review several clustering approaches and examine multicast versus broadcast communication in WSNs

Energy-efficient mobile sink routing scheme for clustered corona-based wireless sensor networks

Wireless Sensor Networks (WSNs) are generally composed of several tiny, inexpensive and self-configured sensor nodes, which are able to communicate with each other via wireless communication devices. The main duty of the nodes is to sense data and transmit to a sink via multi- or single-hop data transmission manners. Since the sensor nodes generally are limited in power resources, they deplete their energy rapidly. In addition, sensor nodes are usually distributed in places, where may be too harsh to be accessible for human. Consequently, exchanging or recharging the power supplies of the sensor nodes is difficult. Therefore, energy efficiency is the most critical issue in design of WSN, which affects the lifetime and performance of the network. Several cluster-based schemes are proposed to enhance the energy efficiency; however, most of them generate sub-optimal clusters without considering both coverage and energy issues simultaneously. Furthermore, several mobility-based schemes are proposed in order to achieve balanced energy consumption through optimizing the sojourn time and sojourn location of Mobile Sinks (MS). Nevertheless, most of them adjust the sojourn time of MS under predictable mobility pattern. Moreover, in most of existing mobility based schemes, time limitation is not considered for optimizing the sojourn location of MS. The aim behind this research is to develop an Energy-efficient Mobile Sink Routing (EMSR) Scheme, which improves the energy efficiency. The EMSR is the incorporation of three schemes: Energyefficient based Unequal-sized Clustering (EUC) mechanism aims to construct the optimal sized clusters, which ensures the energy conservation and coverage preservation. Collaborative Mobile Sink-based Inter-Cluster Routing (CMSICR) mechanism aims to optimize the sojourn time of MS to balance the energy consumption among Cluster Heads (CH). An Energy-efficient Intra-cluster Movement of Mobile Sink (EIM2S) mechanism, which identifies the optimal sojourn locations of the MS within clusters in order to balance the energy consumption among Member Nodes (MN). The EMSR partitions the network field into optimal clusters and employs MSs in order to balance the energy consumption among CHs and MNs. Simulation results show that EMSR achieved improved performance in terms of network lifetime by 51%, total energy consumption by 28% wasted energy by 36% compared to existing schemes. In conclusion, the proposed routing scheme proves to be a viable solution for multi hop cluster based WSN

Cluster-based Routing Protocols for Energy-Efficiency in Wireless Sensor Networks

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Optimization of routing-based clustering approaches in wireless sensor network: Review and open research issues

© 2020 by the authors. Licensee MDPI, Basel, Switzerland. In today’s sensor network research, numerous technologies are used for the enhancement of earlier studies that focused on cost-effectiveness in addition to time-saving and novel approaches. This survey presents complete details about those earlier models and their research gaps. In general, clustering is focused on managing the energy factors in wireless sensor networks (WSNs). In this study, we primarily concentrated on multihop routing in a clustering environment. Our study was classified according to cluster-related parameters and properties and is subdivided into three approach categories: (1) parameter-based, (2) optimization-based, and (3) methodology-based. In the entire category, several techniques were identified, and the concept, parameters, advantages, and disadvantages are elaborated. Based on this attempt, we provide useful information to the audience to be used while they investigate their research ideas and to develop a novel model in order to overcome the drawbacks that are present in the WSN-based clustering models

An Energy Aware Unequal Clustering Algorithm using Fuzzy Logic for Wireless Sensor Networks

In wireless sensor networks, clustering provides an effective way of organising the sensor nodes to achieve load balancing and increasing the lifetime of the network. Unequal clustering is an extension of common clustering that exhibits even better load balancing. Most existing approaches do not consider node density when clustering, which can pose significant problems. In this paper, a fuzzy-logic based cluster head selection approach is proposed, which considers the residual energy, centrality and density of the nodes. In addition, a fuzzy-logic based clustering range assignment approach is used, which considers the suitability and the position of the nodes in assigning the clustering range. Furthermore, a weight function is used to optimize the selection of the relay nodes. The proposed approach was compared with a number of well known approaches by simulation. The results showed that the proposed approach performs better than the other algorithms in terms of lifetime and other metrics