Adaptive energy-efficient clustering path planning routing protocols for heterogeneous wireless sensor networks
Introduction
Present day innovations in Micro-Electro-Mechanical System (MEMS) based technology has enabled the sensor designers to develop tiny, low cost, and energy efficient sensors [11], [10], [35]. It is typical to deploy multiple sensors within a network area, where sensor's density depends upon the requirements of network supported applications in the installation [35], [29], [21], [3]. Environment monitoring, industrial sensing, infrastructure protection, battlefield, and temperature sensing are well-known applications which are supported by wireless sensor networks (WSNs) [9], [32], [7], [6]. Individual sensor node contains some compulsory components, such as, sensing unit, processing unit, communication unit, and power unit as shown in Fig. 1. Additional components, such as, Global Positioning System (GPS) equipment and mobility unit, can also be attached to these sensors [15], [4]. These multiple units are attached to the power units of individual sensors resulting in a much higher energy dissipation. Therefore, limited energy resources at a sensor nodes demand careful and intelligent energy efficient utilization of available limited battery capacity [23], [22].
Various energy efficient techniques have been applied to the protocol stacks of WSNs. As transmission energy dissipation is significantly more than sensing and processing energy consumptions, therefore, developing energy efficient routing protocols is critical for reducing the energy consumption in WSNs. A number of routing protocols have been proposed in the past for WSNs which are grouped into three classes namely, flat, hierarchical, and location-based routing protocols. Clustering routing protocols support much longer network lifetime as compared to the flat and location-based routing protocols [19], [8], [14], [17], [1], [27]. In clustering routing protocols, the whole network comprises of multiple clusters where one node in each cluster acts as a Cluster Head (CH), as shown in Fig. 2. Ordinary cluster nodes send their data to their respective CHs, which further aggregate the received data and forward it to the Base Station (BS) [17], [18], [24], [25], [13]. Furthermore, clustering routing protocols have been divided into different categories that are shown in Fig. 3.
Reputed categories of clustering routing protocols are reviewed as distributed and centralized protocols. The distributed network layer protocols executed by WSNs demand every sensor to participate in cluster formation independently despite their limited computational and battery capacity. Over the operational period of distributed protocols, sensor nodes have to maintain configurations and reconfigurations separately without any real external low-level and high-level vendor-specific network administration at BS. In order to ensure environmental reporting of critical applications of WSNs, routing policies have to be sufficient enough to deal with the dynamics of faults. Therefore, enforcing the distributed routing protocol in such a dynamic environment is highly challenging, where cluster formations are strongly coupled inside sensor devices that limits innovation in networking infrastructure WSNs. Recently proposed WSNs are highly heterogeneous resulting in uneven initial energy capacity of sensor nodes to maximize network lifetime [25], [5], [31], [26], [33], [35]. Consistent heterogeneity of WSNs introduces additional challenges for designing distributed routing protocols since designing a standard routing protocol for enterprise networks can take significantly long time to fully designed, evaluated and deployed.
Centralized networking techniques can provide energy efficient routing protocol that can deal with the limitations of current network infrastructures of WSNs. Centralized routing protocols handover the computational overhead of selection of potential forwarding nodes and potential routes (cluster heads) to BS. Sensor nodes have to participate in limited manner and try to save energy by avoiding unnecessary computation and communication by following the decisions of BS. Therefore, in this paper, we propose two energy efficient path planning routing protocols for three levels heterogeneous WSNs namely, Two-Hop heterogeneity-aware Centralized Energy Efficient Clustering (THCEEC) and Advanced heterogeneity-aware CEEC (ACEEC). The proposed models are advanced heterogeneity-aware routing models, derived from the Centralized Energy Efficient Clustering (CEEC) in order to extend the features of centralized routing to achieve more reliability, stability, and higher network lifetime for WSNs. In the proposed models, BS only assists nodes to find the potential CHs, while further membership phase and transmission phase is still sponsored by the nodes themselves. In this way, proposed models consider the practicality and divide the responsibilities according to the available local and remote resources for computations and communications. These protocols are designed for three-level heterogeneous network, moreover, these all path planning protocols are centralized, so that CHs are selected by the BS. While BS utilizes different network criteria for cluster formation in every clustering routing protocol, CEEC and ACEEC execution utilize the single-hop inter-cluster communication while THCEEC algorithm has the ability of two-hop inter-cluster communication which enabled THCEEC to perform better than CEEC and ACEEC.
The rest of the paper is organized as follows. We discuss related work and objectives of this research in Section 2. We design advanced heterogeneous network models for which the proposed models are designed in Section 3. In Section 4, we present the working mechanisms of the proposed models. We present the analytical discussion on the performance of the proposed protocols in Section 5. Finally, Section 6 concludes this paper.
Section snippets
Literature review
In earlier literature, several clustering routing protocols have been proposed which are capable of executing in homogeneous and heterogeneous WSNs with significant performance improvements with respect to network lifetime and stability [12]. For homogeneous network environment, LEACH [11] is a pioneer distributed clustering protocol, in which probability based cluster formation is carried out separately by network nodes. Although LEACH promises improvements as compared to direct transmission,
Heterogeneous network model
Conventional auto management of sensor's nodes introduces several key issues that demand careful planning on potential characteristics of sensor devices, distributions, data aggregation capabilities, and energy consumption by adopted radio model. We make the following assumptions, which are consistent with the assumptions made in the existing literature [11], [10], [35], for developing the proposed models:
- •
All nodes are stationary after first scattered period, and can achieve localization by GPS
Proposed model of THCEEC and ACEEC
In this section, we present the Two-Hop Centralized Energy Efficient Clustering (THCEEC) and Advanced Centralized Energy Efficient Clustering (ACEEC) clustering path planning routing protocols which are derived from Centralized Energy Efficient Clustering (CEEC). These protocols are executed in different type of sensor network model as discussed in the previous sections. Moreover, these protocols have different CHs selection criteria and inter-cluster communication. In the proposed models, BS
Performance evaluation of THCEEC and ACEEC
We have evaluated the proposed protocols using extensive simulations, and have compared their performance with LEACH, SEP, ESEP, and DEEC. In our evaluation two different networking scenarios are used that significantly generalize the performance overview. The values of α and E0 are kept the same in both scenarios. In the first scenario, 100 nodes are deployed in 100 m × 100 m network area, whereas, in the second scenario, 120 nodes are scattered in 210 m × 210 m network area. The simulation parameters
Conclusion
This paper proposes Two-Hop Centralized Energy Efficient Clustering (THCEEC) and Advanced heterogeneity-aware Centralized Energy Efficient Clustering (ACEEC) routing protocols which are derived from Centralized Energy Efficient Clustering (CEEC) routing protocol for three level heterogeneous WSNs to enhance the stability and network lifetime of WSN. Advanced heterogeneous network models are designed to support the proposed models to produce best energy efficient networking. These assistant
Acknowledgements
This research is supported in part by “National Natural Science Foundation of China” (No. 61272523), “the National Key Project of Science and Technology of China” (No. 2011ZX05039-003-4) and “the Fundamental Research Funds for the Central Universities”.
Muhammad Aslam received the B.S degree in Telecommunication System and the M.S degree in Electrical Engineering from BZU Multan and COMSATS Institute of Information Technology Islamabad in 2010, 2012, respectively. He was Lecturer at COMSATS Institute of Information Technology, Wah Cantt. His major research interests are Energy optimization in WSNs, WBANs, and UWSNs. Currently he is PhD scholar at School of Computer Science and Technology, Dalian University of Technology, Dalian, China.
References (35)
- et al.
Genetic algorithm based energy efficient clusters (GABEEC) in wireless sensor networks
- et al.
Energy efficient and QoS based routing protocol for wireless sensor networks
J. Parallel Distrib. Comput.
(2010) - et al.
Comparison of simulators for assessing the ability to sustain wireless sensor networks using dynamic network reconfiguration
Sustain. Comput. Inform. Syst.
(2016) - et al.
Design of a distributed energy-efficient clustering algorithm for heterogeneous wireless sensor networks
Comput. Commun.
(2006) - et al.
Performance evaluation of synchronous energy efficient MAC protocols for wireless sensor networks
Proc. ICCCS
Procedia Technol.
(2012) - et al.
Tree based energy efficient and high accuracy data aggregation for wireless sensor networks
Proc. ICMOC
Procedia Eng.
(2012) - et al.
A systematic review on clustering and routing techniques based upon LEACH protocol for wireless sensor networks
J. Netw. Comput. Appl.
(2013) - et al.
Minimum connected dominating sets and maximal independent sets in unit disk graphs
Theor. Comput. Sci.
(2006) - et al.
Mobile sink-based adaptive immune energy-efficient clustering protocol for improving the lifetime and stability period of wireless sensor networks
IEEE Sens. J.
(2015) - et al.
Routing techniques in wireless sensor networks: a survey
IEEE Wirel. Commun.
(2004)
A secure cluster-based multipath routing protocol for WMSNS
Sensors
CEEC: centralized energy efficient clustering a new routing protocol for WSNS
RMER: reliable and energy-efficient data collection for large-scale wireless sensor networks
IEEE Internet Things J.
Fundamental lifetime mechanisms in routing protocols for wireless sensor networks: a survey and open issues
Sensors
An energy balancing leach algorithm for wireless sensor networks
An application-specific protocol architecture for wireless microsensor networks
Trans. Wirel. Commun.
Energy-efficient communication protocol for wireless microsensor networks
Cited by (46)
An energy optimized and QoS concerned data gathering protocol for wireless sensor network using variable dimensional PSO
2021, Ad Hoc NetworksCitation Excerpt :Besides energy optimization, network Quality of Service (QoS) metrics have evolved as key requisites of any mission-critical, and real-time multimedia applications [7–10]. Cluster based communication protocols [11–16] have shown better competency in terms of energy-saving and reliability over the traditional routing protocols. However, in static sink scenario, cluster based multi-hop routing may encounter the energy hole issue [17,18].
AMERP: Adam moment estimation optimized mobility supported energy efficient routing protocol for wireless body area networks
2021, Sustainable Computing: Informatics and SystemsCitation Excerpt :The cost function has been optimized using genetic algorithm and the energy consumption during various modes like active, idle, sleep has been taken into consideration. Not only this, various energy efficient clustering routing protocols developed by researchers had proved to be more stable for the sensors network [21,22]. The authors in [23] proposed a power efficient MAC protocol that reduces the power consumption and enhances the network lifetime by the concept of low-cost wake-up radio.
HQCA-WSN: High-quality clustering algorithm and optimal cluster head selection using fuzzy logic in wireless sensor networks
2020, Fuzzy Sets and SystemsCitation Excerpt :Therefore, energy consumption and the network lifetime are the main challenges that affect these networks [3–5]. The data collected by the nodes are transmitted to a base station (BS) for processing [6]. Data transfer can be conducted in a single-hop or multi-hop manner [7,8].
MACR: A Novel Meta-Heuristic Approach to Optimize Clustering and Routing in IoT-based WSN
2024, International Journal of Intelligent Systems and Applications in EngineeringA hybrid C-GSA optimization routing algorithm for energy-efficient wireless sensor network
2023, Wireless NetworksA Reinforcement Learning Approach for Storing Data in Reactive IoT Network
2023, Proceedings of 8th IEEE International Conference on Science, Technology, Engineering and Mathematics, ICONSTEM 2023
Muhammad Aslam received the B.S degree in Telecommunication System and the M.S degree in Electrical Engineering from BZU Multan and COMSATS Institute of Information Technology Islamabad in 2010, 2012, respectively. He was Lecturer at COMSATS Institute of Information Technology, Wah Cantt. His major research interests are Energy optimization in WSNs, WBANs, and UWSNs. Currently he is PhD scholar at School of Computer Science and Technology, Dalian University of Technology, Dalian, China.
Ehsan Ullah Munir received his Masters in Computer Science from Barani Institute of Information Technology, Pakistan in 2001. He completed his PhD degree in Computer Software & Theory from Harbin Institute of technology Harbin, China in 2008. He is currently working as Associate Professor and Head in the Department of Computer Science at COMSATS Institute of Information Technology, Pakistan. His research interests include heterogeneous parallel and distributed computing, wired and wireless networks, and information retrieval.
M. Mustafa Rafique is a Research Scientist in the High Performance Systems Group at IBM Research Dublin. His research focuses on designing and developing accelerator- and coprocessor-based heterogeneous clusters for high-performance computing (HPC). His research interest includes resource management for cloud computing, resource management for asymmetric clusters, programming models for heterogeneous systems, and I/O techniques for asymmetric multiprocessors. Prior to joining IBM, Mustafa has worked at NEC Labs and Qatar Computing Research Institute (QCRI) on designing innovative solutions for adaptive and efficient resource management in massively parallel, distributed, and high-performance computing systems. Mustafa received his MS and PhD degrees in Computer Science from Virginia Tech in 2010 and 2011 respectively.
Xiaopeng Hu received the PhD degree in computer science from Imperial College London, U.K., in 2005. He is currently a Professor of Computer Science with the School of Computer Science and Technology, Dalian University of Technology. His research interests include computer vision, machine learning, and sensor fusion.