Energy-efficient Communication Protocols Research Articles

Optimizing Energy-Efficient Communication Protocols for IoT Devices in Smart Cities Using Narrowband IoT and LTE-M Technology

In the context of optimizing energy-efficient communication protocols for IoT devices in smart cities, this research addresses the pressing need for sustainable and reliable solutions. The research provides a comprehensive understanding of the strategies that contribute to minimizing energy consumption in smart city IoT deployments, with a specific focus on Narrowband IoT (NB-IoT) technology. Employing a structured framework and an integrated system architecture, incorporating LTE-M technology and an application server, the research leverages various optimization strategies. These include Adaptive Power Control, Duty Cycling, Data Aggregation, Protocol Optimization, and Network Topology Optimization. Methodologically, the study adopts a quantitative approach, utilizing metrics such as duty cycle percentages and energy consumption reductions. Data is collected through simulations and experiments, and the analysis involves assessing the impact of each optimization strategy on energy efficiency. Key findings demonstrate significant reductions in energy consumption, ranging from 15% to 25%, depending on the specific strategy employed. Adaptive Power Control and Network Topology Optimization emerge as particularly effective approaches. The implications of these findings underscore the importance of adopting tailored optimization strategies in smart city IoT deployments to achieve both energy efficiency and reliability. The study discusses the broader significance of these results and acknowledges potential limitations, paving the way for future research endeavors in the realm of sustainable and resource-conserving smart cities.

Energy-Efficient Dynamic MAC Protocol for M2M Communication

In the Internet of Things, which is vital for smart city applications, a vast network of battery-operated Machine Type Communication Devices (MTCDs) requires Machine Type Communication. These MTCDs connect directly to a network with a base station, facilitating a wide range of smart city functionalities. The development of energy-efficient communication protocols is essential to support the deployment of energy-constrained battery-operated devices. These protocols aim to minimize energy consumption, thereby enhancing network lifetime. Additionally, they must address scalability, reduce collisions and delays, and ensure a high Quality of Service (QoS) to effectively manage the vast number of devices involved. Clustering is a viable strategy to enhance scalability and energy efficiency in network communications. However, within this framework, particularly in the proposed Power Efficient Dynamic MAC protocol for M2M Communication (PMAC), there's still a need for energy-efficient communication between the Machine Type Communication Devices (MTCDs). This requirement is crucial to optimize the overall performance and sustainability of the network. In this paper, we analyses the Energy Efficient CSMA/CA (E-CSMA/CA) protocol, specifically developed for facilitating communication between Machine Type Communication Devices (MTCDs) in short-range communications. This analysis is set within the context of smart city applications, with a particular focus on smart metering. This approach underscores the importance of efficient, reliable communication protocols in modern urban infrastructure, especially for applications like smart metering that are integral to the smart city ecosystem.

Sustainability by Efficiency: Energy Considerations in IoT Device Development

The widespread use of Internet of Things (IoT) devices has brought about an unparalleled level of connectedness, revolutionizing several sectors and everyday existence. However, there are serious worries over the energy usage and environmental effect of these devices due to their increasing deployment. The urgent problem of improving energy efficiency in Internet of Things devices is explored in this study abstract. Acknowledging the complex issues, we examine the condition of IoT device architecture at the moment, focusing on elements that lead to excessive energy usage. We examine cutting-edge techniques via an extensive examination, such as advanced computing paradigms like edge and fog computing, low-power hardware design, and energy-efficient communication protocols. The study also looks at case studies and tests conducted in the real world, providing concrete proof of the efficacy of various energy-saving strategies. Even with significant progress, issues with security, privacy, and scalability still exist. We address the trade-offs between performance and energy efficiency, highlighting the necessity of standardizing solutions. Promising future prospects are outlined in our article, such as the incorporation of block chain applications, revolutionary developments in battery technology, and renewable energy sources. The purpose of this study abstract is to direct researchers, industry practitioners, and policymakers towards sustainable solutions for reducing the energy footprint of Internet of Things devices by offering a thorough view of the present scenario and forward-looking tactics.

A Review on Communication Protocols of Wireless Sensor Networks

Wireless Sensor Networks (WSNs) are networks of small, low-cost, low-power, and wirelessly connected sensor nodes. These sensor nodes can be distributed over a large area and can collect data about the environment, such as temperature, humidity, light, sound, vibration, and motion. WSNs are useful in a variety of applications, including environmental monitoring, smart agriculture, healthcare, industrial automation, and security. They can be used to gather data in remote or hard-to-reach locations, and they can also be used to monitor large areas continuously and in real-time. The nodes in a WSN are typically battery-powered and have limited processing and communication capabilities. Therefore, energy efficiency is a critical concern in WSNs, and the nodes are designed to conserve energy wherever possible. Proper choice of Communication protocols are essential for energy conservation in Wireless Sensor Networks (WSNs).This paper discuss about various communication protocols and its types. They help to reduce idle listening time, minimize data transmission, optimize routing, and control transmission power. By using energy-efficient communication protocols, WSNs can achieve longer network lifetime, better data accuracy, and improved network performance.

A comprehensive review of energy efficient wireless communication and routing protocols in smart agriculture

A comprehensive review of energy efficient wireless communication and routing protocols in smart agriculture

A Comprehensive review of energy efficient wireless communication and routing protocols in smart agriculture

A Comprehensive review of energy efficient wireless communication and routing protocols in smart agriculture

Optimization technique based on cluster head selection algorithm for 5G-enabled IoMT smart healthcare framework for industry

Abstract Internet of medical things (IoMT) communication has become an increasingly important component of 5G wireless communication networks in healthcare as a result of the rapid proliferation of IoMT devices. Under current network architecture, widespread access to IoMT devices causes system overload and low energy efficiency. 5G-based IoMT systems aim to protect healthcare infrastructure and medical device functionality for longer. Therefore, using energy-efficient communication protocols is essential for enhancing QoS in IoMT systems. Several methods have been developed recently to improve IoMT QoS; however, clustering is more popular because it provides energy efficiency for medical applications. The primary drawback of the existing clustering technique is that their communication model does not take into account the chance of packet loss, which results in unreliable communication and drains the energy of medical nodes. In this study, we concentrated on designing a clustering model named Whale optimized weighted fuzzy-based cluster head selection algorithm to facilitate successful communication for IoMT-based systems. The experimental study shows that the proposed strategy performs better in terms of QoS than compared approaches. Inferring from this, the proposed method not only reduces energy consumption levels of 5G-based IoMT systems but also uniformly distributes cluster-head over a network to improve QoS.

Statistical Channel Model and Systematic Random Linear Network Coding Based QoS Oriented and Energy Efficient UWSN Routing Protocol

Considering the significance of an energy efficient, delay tolerant and reliable communication protocol for underwater acoustic wireless sensor network (UWSN), this paper proposes a novel systematic random linear network coding (SRLNC) based transmission system examined over a robust statistical UWSN channel model. The derived statistical channel model deals with both the small-scale fading primarily caused by scattering and small wavelength changes and large-scale fading introduced due to node dislocation in the underwater acoustic medium. The proposed SRLNC transmission-based routing approach has been applied over the proposed underwater acoustic (statistical) channel model, and respective performance assessment has been conducted in terms of throughput, energy efficiency, delay and computational complexity by varying network condition parameters. The contributions such as low coefficient vector and Galois filed, low redundant message requirements, computationally efficient pre-coding scheme, iterative buffer flush and enhanced FEC based decoding make the SRLNC based routing protocol sufficiently robust to enable reliable, energy-efficient and delay resilient communication over UWSN. The proposed SRLNC based UWSN routing protocol and its efficacy over dynamic channel conditions affirm that it can be a potential solution for QoS-oriented mission critical underwater communication purposes.

Coverage and connectivity based lifetime maximization with topology update for WSN in smart grid applications

The self-sufficient Smart Grid (SG) with two-way data communication among its constituents is proposed as a remedy to the shortcomings of the traditional power grid. Due to their low cost and ease of deployment along with the advanced communication capabilities they offer, WSNs are seen as an important technology for SG applications. To this end, it is important to design energy-efficient communication protocols to achieve a long network lifetime while maintaining the desired coverage level. In this paper, we consider the case where the transmission paths are re-adapted to topology changes as long as the required coverage level and connectivity to the base station can be maintained with the current set of sensors with positive residual energy. We first propose a novel 0–1 mixed-integer programming (MIP) model, and then present two alternative 0–1 MIP models optimizing the network behavior in unit time decomposition with an emphasis on energy consumption. Our study is unique in terms of including topology adaptation due to energy depletion within a holistic solution framework based on optimization methods. We avoid the traditional time until the first sensor dies metric and allow the WSN to continue to function optimally as long as the predetermined coverage level and connectivity to the BS can be achieved with the remaining sensors. We observe that network lifetime can be increased significantly even after a one-time reorganization. Moreover, we analyze how the solutions of the three models differ in terms of lifetime and coverage level. As a side contribution, we show that maximizing the time until the first sensor dies is equivalent to minimizing the energy consumption of the most used sensor for the classical single-period problem, which is not necessarily true when there is an adaptation to a topology change. Hence, we provide a practical tool to determine the theoretical upper bound on the network lifetime with coverage and connectivity-based QoS requirements.

ETM-IoT: Energy-Aware Threshold Model for Heterogeneous Communication in the Internet of Things

The internet of things (IoT) has a wide variety of applications, which in turn raises many challenging issues. IoT technology enables devices to closely monitor their environment, providing context-aware intelligence based on the real-time data collected by their sensor nodes. The IoT not only controls these devices but also monitors their user's behaviour. One of the major issues related to IoT is the need for an energy-efficient communication protocol which uses the heterogeneity and diversity of the objects connected through the internet. Minimizing energy consumption is a requirement for energy-constrained nodes and outsourced nodes. The IoT nodes deployed in different geographical regions typically have different energy levels. This paper focuses on creating an energy-efficient protocol for IoT which can deal with the clustering of nodes and the cluster head selection process. An energy threshold model is developed to select the appropriate cluster heads and also to ensure uniform distribution of energy to those heads and member nodes. The proposed model envisages an IoT network with three different types of nodes, described here as advanced, intermediate and normal nodes. Normal nodes are first-level nodes, which have the lowest energy use; intermediate nodes are second-level nodes, which have a medium energy requirement; and the advanced class are third-level nodes with the highest energy use. The simulation results demonstrate that the proposed algorithm outperforms other existing algorithms. In tests, it shows a 26% improvement in network lifetime compared with existing algorithms.

Guest Editorial Special Issue on “Green Communication and Computing Technologies for 6G Networks” in IEEE Transactions on Green Communications and Networking

The next of wireless networks (i.e., 6G) is envisioned to support communication in the three-dimensional space by integrating space, aerial, terrestrial, and undersea networks. The overall goal is to provide ubiquitous and unlimited connectivity to a massive number of Internet of Things (IoT) and machine-type devices/users having diverse Quality of Service (QoS) requirements, supporting substantial and heterogeneous traffic demands, and reducing the energy consumption with the help of highly energy-efficient communication protocols, transceivers and computing technologies. Out of several innovations 6G is targeting, this special issue focuses on green communications and computing technologies, which are crucial to reduce the overall energy consumption and operational cost from both the environmental and business viewpoints. To this end, the ever-increasing demand for advanced and ubiquitous applications over the recent years has shifted the paradigm of self-organizing networks to self-sustainable networks (SSNs). One main goal of SSNs is to eliminate the need for separate charging of heterogeneous devices by combining energy-efficient communication, energy harvesting/power transfer techniques, and offloading of energy-intensive processing from the edge-devices to the edge- and cloud-servers. However, the coexistence of wireless information and power transfer systems/links should be as seamless as possible for the end-users. Furthermore, providing network sustainability, and energy-efficient, energy-aware, and environment-aware connections to the massive number of devices and users having different levels of processing capabilities is one of the key challenges.

Enriched cluster head selection using augmented bifold cuckoo search algorithm for edge‐based internet of medical things

SummaryHealthcare organizations are appending advanced scientific tools for processing digital data effectively due to enterprise demands. Among the recent tools, edge computing plays a vital role in aggregation and dissemination of data from the healthcare monitoring devices. A vital challenge in edge computing‐based Internet of Medical Things (IoMT) systems are energy‐efficient monitoring devices which in turn improves the overall lifetime of the network thus in turn improves the quality of monitoring system. In recent years, a significant number of approaches are developed for solving energy efficient communication protocols for IoMT. Clustering is one effective method to reduce the overall energy consumption by the medical wireless devices. The major drawback of the existing models is the sustainability of the network. In this paper, an evolutionary‐based cluster head selection technique is proposed, namely, augmented bifold cuckoo search algorithm (ABCSA). A novel binary model is also developed for handling the binary solution space. The experimental analysis of the proposed model has been evaluated and compared with the existing model to prove it significance. And as a result on comparing with the existing models, proposed ABCSA outperforms the existing models significantly.

EECPH: energy efficient cooperative communication protocol for heterogeneous wireless sensor networks

Typically, the energy consumption is the major issue in Wireless Sensor Network (WSN), and from past several years various clustering routing protocols are proposed to extend the lifetime of WSN. Sensor nodes can sense and sensed data will be forward to the Base Station (BS) in a cooperative manner. Hence, to transmit the data to BS a high amount of energy is required. To overcome this problem, the clustering approach is the key technique to reduce energy consumption. In this paper, we present an Energy Efficient Cooperative Communication Protocol for Heterogeneous (EECPH) Wireless Sensor Networks. Firstly, Cluster Head (CH) can be chosen according to the node initial energy, hop count, and remaining energy. Secondly, the introduction of cooperative node selection can reduce the uneven distribution of clusters. Finally, different levels of energy nodes are introduced namely normal, advanced, and super nodes to enhance the energy efficiency in heterogeneous WSN. Simulation results shows, the EECPH protocol outperforms with reference to network throughput, energy efficiency, and the network lifetime over EARPC, and LEACH protocol.

EECPH: energy efficient cooperative communication protocol for heterogeneous wireless sensor networks

Typically, the energy consumption is the major issue in Wireless Sensor Network (WSN), and from past several years various clustering routing protocols are proposed to extend the lifetime of WSN. Sensor nodes can sense and sensed data will be forward to the Base Station (BS) in a cooperative manner. Hence, to transmit the data to BS a high amount of energy is required. To overcome this problem, the clustering approach is the key technique to reduce energy consumption. In this paper, we present an Energy Efficient Cooperative Communication Protocol for Heterogeneous (EECPH) Wireless Sensor Networks. Firstly, Cluster Head (CH) can be chosen according to the node initial energy, hop count, and remaining energy. Secondly, the introduction of cooperative node selection can reduce the uneven distribution of clusters. Finally, different levels of energy nodes are introduced namely normal, advanced, and super nodes to enhance the energy efficiency in heterogeneous WSN. Simulation results shows, the EECPH protocol outperforms with reference to network throughput, energy efficiency, and the network lifetime over EARPC, and LEACH protocol.

SNR based Energy Efficient Communication Protocol for Emergency Applications in WBAN

Continuous remote monitoring of a patient’s health condition in dynamic environment imposes many challenges. Challenges further get multiplied based on the size of body area sensor network. One such challenge is energy efficiency of sensors. Maintaining longer life of all nodes, especially who participate in communicating vital signals from one network to another towards the base station is very important. In this work, an energy efficient communication protocol for the wireless body area network (WBAN) is proposed. The essential characteristics of the protocol are: random deployment of nodes, formation of clusters, node with high signal to noise ratio (SNR) as cluster head (CH), random rotation of CHs within each cluster, and so on. The developed algorithm is simulated in MATLAB by varying the number of nodes and networks. Obtained results are compared with some of the recent and most relevant existing works. It is found that there is an enhancement in the network lifetime by 19.5%, throughput by 12.61% and average remaining energy by 57.21%.

Performance Analysis of Energy Efficient and Reliable Protocols for Intra & Inter Cluster Communications in Wireless Sensor Networks

The discovery and the use of many wireless technologies are paving way for new remote monitoring applications. The sensing devices are becoming popular because of their flexibility, performance, low cost and portability. Wireless Sensor Networks (WSN) is a good alternative to wired systems because of easy deployment in remote areas. Wireless Sensor Networks are used in different domains for various applications because of their salient characteristics like reduced power consumption, scalability, ability to respond immediately within a short span of time, reliability, dynamic in nature, low cost and easy installation. The main objective of this paper work is to find a suitable energy efficient, scalable and reliable communication protocols for intra-cluster and intercluster communication. Therefore the proposed research work follows three different phases. To achieve the desired results, the proposed research work concentrates on three protocols namely Energy Efficient and Reliable Clustering Routing Protocol (EERCRP), Energy Efficient and Reliable MAC Protocol (EERMAC) and Energy Efficient and Reliable Hybrid Transport Protocol (EERHTP).EERCRP and EERMAC are intra-cluster communication protocols that help in cluster formation and effective data sensing. EERHTP is a transport layer protocol that is used for inter-cluster communication. All the above protocols are evaluated using network simulator NS2 for their performance analysis. EERCRP is compared with PASCC and PCDCC which from the root level header node are existing congestion and queue based hybrid clustering protocols. The proposed EERCRP follows hierarchical cluster formation where the leader node is selected based on queue length, residual energy of the node and distance. It is efficient than the existing methods in terms of energy and reliability metrics.EERMAC is compared with existing MAC protocols namely SMAC, IEEE 802.11 EDCA and EA-MAC. SMAC follows traditional TDMA or CSMA method of data access. They are suitable only for periodic data sensing. The proposed EERMAC allows hybrid data sensing consisting of both periodic and event based data which are classified using priority levels. Event based data is assigned higher priority than periodic data. Queues are used for storing both types of data using various levels of threshold values. EERMAC uses CSMA/CA method for event based data. Variable TDMA method is used for event based and periodic data. EERHTP is a transport layer protocol that uses two types of reliability models namely ACK and NACK depending on the type of data. All the three protocols are evaluated both for energy and reliability metrics such as total energy consumption, residual energy comparison, energy consumption per packet, packet delivery ratio, delay, packet drop, jitter, throughput and network routing overhead. Thus it is concluded that all the three protocols are more optimal than the existing protocols and prove to be the best protocols for intracluster and inter-cluster communications.

Selective-path clustered-based routing protocol for large scale wireless sensor networks

Wireless sensor networks (WSNs) consist of large number of small low-powered electronic sensor devices. Therefore, reliable power saving schemes must be developed in order to manage the energy dissipated and extend the network life and functionality for a meaningful time. Arranging sensor nodes (SNs) into clusters has been viewed as an efficient approach of balancing the energy dissipated in WSNs. Regardless, a clustered WSN needs a robust energy efficient (EE) and energy balanced (EB) routing communication protocol. This paper proposes a selective-path priority table (SPT) EE and EB routing protocol (RP) ideal for most conventional clustering algorithms. The SPT RP forms the priority table by prioritising the k nearest multi-hop paths to the cluster heads (CHs) and/or base station (BS) based on some robust rules. These rules are compiled using a combination of some routing metrics which include the residual energy (RE) and transmission range/power. Firstly, the simulation results indicate that the SPT RP can be combined with most of the conventional clustering algorithm irrespective of the number of deployed SNs. Secondly, the performance of the SPT RP improves as the value of the selected number of routing paths (k) increase. More so, the simulation results show that the SPT RP reduces the energy dissipated and can prolong the network life and throughput as compared to related routing schemes.

Selective-path clustered based routing protocol for large scale wireless sensor networks

Wireless sensor networks (WSNs) consist of large number of small low-powered electronic sensor devices. Therefore, reliable power saving schemes must be developed in order to manage the energy dissipated and extend the network life and functionality for a meaningful time. Arranging sensor nodes (SNs) into clusters has been viewed as an efficient approach of balancing the energy dissipated in WSNs. Regardless, a clustered WSN needs a robust energy efficient (EE) and energy balanced (EB) routing communication protocol. This paper proposes a selective-path priority table (SPT) EE and EB routing protocol (RP) ideal for most conventional clustering algorithms. The SPT RP forms the priority table by prioritising the k nearest multi-hop paths to the cluster heads (CHs) and/or base station (BS) based on some robust rules. These rules are compiled using a combination of some routing metrics which include the residual energy (RE) and transmission range/power. Firstly, the simulation results indicate that the SPT RP can be combined with most of the conventional clustering algorithm irrespective of the number of deployed SNs. Secondly, the performance of the SPT RP improves as the value of the selected number of routing paths (k) increase. More so, the simulation results show that the SPT RP reduces the energy dissipated and can prolong the network life and throughput as compared to related routing schemes.

Energy-Efficient Time-Triggered Communication Policies for Wireless Networked Control Systems

Energy-efficient communication protocols have become an important topic over the past two decades due to environmental issues, increased monetary costs of energy consumption, and limited battery capacities of sensors and mobile devices. In this context, we present a novel approach to design energy-efficient time-triggered communication policies for wireless networked control systems, while ensuring a given control performance. We consider a plant, modeled as a deterministic discrete-time linear system, which is controlled through a wireless network by an output-feedback law. We proceed by emulation, i.e., we construct the controller to stabilize the origin of the plant while ignoring communication constraints. Next, the wireless network is taken into account and we assume that the probability of packet drops depends on the transmission signal power. We introduce the notion of stochastic allowable transmission interval (SATI) to characterize stabilizing time-triggered transmission policies. We then explain how to minimize the average energy expenditure of the transmitting devices while satisfying the SATI constraints, thus ensuring the control requirements. Simulations results are provided to illustrate the tradeoff between the communication and the control costs.

Energy‐balanced and energy‐efficient clustering routing protocol for wireless sensor networks

Prolonging the network lifetime for a reasonable period while meeting users' needs is key in developing a data gathering algorithm for WSNs. Clustered sensor networks are considered as an efficient approach for extending the network lifetime of WSNs. In clustering, sensor devices are arranged in clusters. Inside the cluster, non-cluster head nodes transmit data to the cluster head ( C H ) nodes while the C H forward the message to the sink. Irrespective of how the clusters are formed, a clustered WSN requires sturdy energy-balanced (EB) and energy-efficient (EE) communication protocol. Different from the previous clustered based routing protocol, this paper develops and analyses a selective-path priority table EB and EE clustering based routing protocol, which employs a mobile sink. The priority table is formed by prioritising the two shortest paths to the C H or sink according to some simple but efficient rules. The rules are derived using some routing metrics such as transmission range/power and residual energy. The simulation results show that the proposed routing protocol can be integrated with most clustering formation algorithms, even in large scale WSNs. Besides, results show that this routing protocol improve the network lifetime and throughput as compared to similar schemes.