Energy Efficient Protocol Research Articles

Multipath Routing in Wireless Body Area Sensor Network for Healthcare Monitoring.

Mobility and low energy consumption are considered the main requirements for wireless body area sensor networks (WBASN) used in healthcare monitoring systems (HMS). In HMS, battery-powered sensor nodes with limited energy are used to obtain vital statistics about the body. Hence, energy-efficient schemes are desired to maintain long-term and steady connectivity of the sensor nodes. A sheer amount of energy is consumed in activities such as idle listening, excessive transmission and reception of control messages, packet collisions and retransmission of packets, and poor path selection, that may lead to more energy consumption. A combination of adaptive scheduling with an energy-efficient protocol can help select an appropriate path at a suitable time to minimize the control overhead, energy consumption, packet collision, and excessive idle listening. This paper proposes a region-based energy-efficient multipath routing (REMR) approach that divides the entire sensor network into clusters with preferably multiple candidates to represent each cluster. The cluster representatives (CRs) route packets through various clusters. For routing, the energy requirement of each route is considered, and the path with minimum energy requirements is selected. Similarly, end-to-end delay, higher throughput, and packet-delivery ratio are considered for packet routing.

FEEC: fuzzy based energy efficient clustering protocol for WSN

FEEC: fuzzy based energy efficient clustering protocol for WSN

Energy Efficient Routing and Dynamic Cluster Head Selection Using Enhanced Optimization Algorithms for Wireless Sensor Networks

A large number of spatially dispersed nodes on the wireless network create Wireless Sensor Networks (WSNs) to collect and analyze the physical data from the environment. The issues that affected the network and had an impact on network energy consumption were cluster head random selection, working node redundancy, and cluster head transmission path construction. Consequently, this energy constraint also has an impact on the network lifetime and energy-efficient routing. Therefore, the primary goals of this research are to decrease energy consumption and lengthen the network’s lifespan. So, using improved optimization algorithms, this paper presents a dynamic cluster head-based energy-efficient routing system. The Improved Coyote Optimization Algorithm (ICOA), in this case, consists of three phases setup, transmission, and measurement phase. The Improved Jaya Optimization Algorithm with Levy Flight (IJO-LF) then determines the route between the BS and the CH. It selects the most effective course based on the distance, node degree, and remaining energy. The proposed approach is compared with traditional methods and the routing protocols Power-Efficient Gathering in Sensor Information Systems (PEGASIS) and Threshold sensitive Energy Efficient Sensor Network protocol (TEEN) during implementation on the MATLAB platform. Performance indicators for the suggested methodology are evaluated based on data packets collected by the BS, energy usage, alive nodes, and dead nodes. The outputs of the suggested methodology performed better than the conventional plans.

An efficient quality of services based wireless sensor network for anomaly detection using soft computing approaches

Wireless sensor network (WSN) is widely acceptable communication network where human-intervention is less. Another prominent factors are cheap in cost and covers huge area of field for communication. WSN as name suggests sensor nodes are present which communicate to the neighboring node to form a network. These nodes are communicate via radio signals and equipped with battery which is one of most challenge in these networks. The battery consumption is depend on weather where sensors are deployed, routing protocols etc. To reduce the battery at routing level various quality of services (QoS) parameters are available to measure the performance of the network. To overcome this problem, many routing protocol has been proposed. In this paper, we considered two energy efficient protocols i.e. LEACH and Sub-cluster LEACH protocols. For provision of better performance of network Levenberg-Marquardt neural network (LMNN) and Moth-Flame optimisation both are implemented one by one. QoS parameters considered to measure the performance are energy efficiency, end-to-end delay, Throughput and Packet delivery ratio (PDR). After implementation, simulation results show that Sub-cluster LEACH with MFO is outperforms among other algorithms.Along with this, second part of paper considered to anomaly detection based on machine learning algorithms such as SVM, KNN and LR. NSLKDD dataset is considered and than proposed the anomaly detection method.Simulation results shows that proposed method with SVM provide better results among others.

An Energy-Efficient Protocol Based on Leach for Smart Home

In Smart Home (SH) the devices and appliances can be controlled automatically and remotely via the internet. Sensors in a smart home detect changes, which are processed and used to make intelligent decisions, such as automatically turning on the lights. To be effective, a smart home's sensors must be connected, establishing a wireless sensor network as the backbone for the smart home's functionalities. For many researchers, the performance of WSN faces several challenges. Power consumption is the most crucial factor since nodes require power to collect, process, and send data but have limited energy. As a result we propose an improved protocol for WSN in smart homes called EEP-LEACH (Energy Efficient Protocol - Low Energy Adaptive Clustering Hierarchy) based on the LEACH protocol. Matlab was used for the algorithm's performance analysis, and the simulation result showed that, compared to others protocols the death time of the nodes was longer, thus managing to balance the consumption of energy of the network nodes. Python and Arduino are used in this research to perform some simulations.

Cooperative self-scheduling routing protocol based IOT communication for improving life time duty cycled energy efficient protocol in SDN controlled embedded network

Internet of Things (IoT) is a developing interconnecting medium in a wireless network through internet of communication in network devices like sensors, smart devices and controllers. This interconnect the devices via the internet to make communication. Due to large sectors IoT devices and Software-Defined Networking (SDN) controllers contains energy constraints in improper routing strategies. Specifically in health care industries, the patient monitoring data's consumes higher energy to reduce the lifetime of network communication leads data losses during the IoT devices collecting the information become loss.The embedded communication are relatively controls through the Software defined network to maintain the energy consumption to improve the lifetime of energy efficient network. But leastpropagation energy losses arise communication losses because of traffic, packet losses, latency beyond with throughput limits. The main problem is Passive Infrared Sensor (PHR) sensor nodes and Relay nodes attain more energy because of non-uniform node displacement in routing in uneven energy drainage. So resolving these problems, in this system propose a cooperative self-scheduling routing protocol based IoT communication for improving energy efficient SDN controlled embedded network.Initially this construct the Neighbor Distance Discovery Protocol (NDDP) to identify the minimum depletion path by identifying Sensor closest route to the relay node. Then construct the Multipath Cooperative Self-Scheduling Protocol (MCSSP) to formalize the non-traffic route. By estimating the energy consumption on each sensor node on routing medium, this considers the prior routing communication rate by calculating average transmission delay, sensor absorption rate, power consumption, node response rate, and packet loss rate. UsingLife Time Duty Cycled Energy Efficient Protocol (LTDCEEP) to calculate the delimit of the feature limits along the network threshold latency energy limits. Based on the transition limit the weights of the nodes are estimated by energy consumption from each duty cycle by consuming more transmission energy, the route be scheduled to optimize the communication delay to reduce the power consumption in the sense of responsive nodes. This improves the power consumption rate, latency, power quality in transmission, throughput ratio in SDN network communication.

EEM-MAC: Enhanced energy efficient mobility aware MAC protocol for mobile internet of things

Mobile wireless sensor networks (MWSNs) have become a foremost solution in many emerging applications both in industry and academia. Moreover, considering the mobile node in WSN is a challenging task to designing efficient communication protocols, specifically at a medium access control (MAC) layer. Most of the existing protocols consider only for static and slow mobility. To meet with future MIoT applications, in this paper we propose Enhanced Energy Efficient Mobility aware MAC (EEM-MAC) protocol. Our EEM-MAC protocol consists of 3 contributions i) static synchronization and mobility handling phase to support both environments, ii) By using queue length-based channel access priority for static nodes, and iii) the combined highest signal strength and node status-based channel access priority for mobile nodes without any control packet overhead. The simulation results verify that EEM-MAC yields a notable improvement in the average power consumption, packet latency, and packet delivery ratio performances against the well-known mobility-aware MAC protocols under different mobility models and environments.

Optimized hybrid routing protocol for energy-aware cluster head selection in wireless sensor networks

The clustering mechanism in wireless sensor networks (WSNs) is the ideal strategy for constructing an energy efficient protocol for achieving extended network lifetime, energy efficiency, and scalability. The design of energy efficient protocols in WSNs is essential, as the sensor nodes are battery powered, and may be completely drained, resulting in deterioration in network lifetime. Energy efficient protocols aim to maximize network lifetime while minimizing overall energy consumption to avoid interruptions to the wireless sensor nodes deployed for monitoring and recording physical information from the environment. Moreover, hybrid metaheuristic-optimization based clustering and routing protocols are widely used for attaining energy stability and network lifetime. In this study, the golden eagle optimization algorithm (GEOA) and improved grasshopper optimization algorithm (IGHOA) based on the energy efficient cluster-based routing protocol (GEIGOA) are proposed for sustaining energy stability and augmenting network lifetime longevity by overcoming challenges in the cluster head (CH) selection process. In particular, by optimizing the node centrality, node degree, distance to the base station, distance to the neighbors, and residual node energy, GEOA selects an optimal CH from the deployed group of sensor nodes in the network. Furthermore, IGHOA is utilized to determine a reliable and optimal route between the CH and base station (BS) by assessing node degree, residual energy, and distance parameters. Moreover, the proposed GEIGOA was confirmed to be sufficiently capable in improving the probability of preventing the worst nodes from being selected as CHs with different number of sensor nodes, which was predominantly enhanced by 12.64%, 15.82%, 18.96%, and 20.98% compared with the competitive CH selection schemes. In addition, the computational cost incurred by the proposed GEIGOA with different number of sensor nodes was also confirmed to be minimized by 14.98%, 17.21%, 19.76%, and 21.62% compared with the competitive CH selection schemes.

Modified distributed energy efficient clustering protocol for lifetime maximization in wireless sensor networks

A wireless sensor network is a combination of tiny sensing nodes with minimal energy capabilities. The sensors are installed across field to monitor parameters such as noise, temperature etc for long time. WSN has wide range of applications such as military, health care industry etc. It has advantages such as easy deploying, lower cost and fault tolerance. Since the energy capabilities are minimal, we can take some measures to improve network capabilities. To overcome the issue, we need to concentrate on the performance of the routing protocol while designing the architecture. The aim of WSN is to transfer data by increasing the lifetime of the network, throughput, and number of Cluster Heads (CH). We take DEEC protocol in comparison with the proposed design of M-DEEC which helps in minimizing the energy consumption of the nodes in network and maximize the network lifetime. In M-DEEC is a modified energy distribution algorithm which uses energy aware adaptive clustering protocol in heterogeneous WSN. Each node will carry over a remaining energy over the network which can be further used as reference to increase the lifetime.

CSCRT Protocol with Energy Efficient Secured CH Clustering for Smart Dust Network Using Quantum Key Distribution

Energy efficient protocols for Mobile wireless smart dust networks are getting prominence in the present scenario. This paper describes a novel scheme for intrusion detection framework for secured clustered mobile smart dust networks which better suits the periodical data gathering. The essential objective of a battery equipped mobile wireless smart dust nodes is to upgrade the transmission energy. The proposed protocol has the favourable position that the communication and computational overheads get reduced and gives improved energy efficient routing protocol as far as energy efficient and intrusion detection system. The intrusion and interruption are fundamentally same as that it is difficult to recognize. The design becomes more complex, any security protection algorithms utilize more energy. This can be achieved by using IDS based clustering tactic, Specific Encryption algorithm with Quantum Key Distribution and Chance Succession Comparison Ratio Test protocol. Particular encryption for data based communication is carried out to low utilization of energy and also to discover attacks, when it occurs in mobile nodes. Data transmission rate is a factor for energy utilization. Simulation is done in NS2, results show that better energy efficient routing scheme for mobile wireless smart dust network.

ReLeC: A Reinforcement Learning-Based Clustering-Enhanced Protocol for Efficient Energy Optimization in Wireless Sensor Networks

Wireless sensor networks (WSNs) are a widely studied area in the field of networked embedded computing. They are made up of several sensor nodes, which keep track of a variety of physical and environmental parameters, like temperature and humidity. The nodes are autonomous, self-configuring, and wireless. A significant problem in WSNs is that sensors in these networks consume a lot of energy. Energy consumption is a big issue when it comes to the deployment of sensor networks. The reason for this is the cost of operating a sensor node and the cost incurred due to energy consumption. Energy optimization is based on intelligent energy management. This paper presents a reinforcement learning-based and clustering-enhanced method. Reinforcement learning is a set of algorithms inspired by operant conditioning in animal behavior, and clustering-based methods have been extensively used for devising energy-efficient protocols. The proposed method is able to plan and schedule the nodes to ensure an extended network lifetime. In this work, we aim to assess and increase the efficiency of power consumption and reduce sensor node energy loss. The simulation results prove that the presented protocol effectively reduces the energy consumption of sensor nodes and ensures a prolonged lifetime of the sensor network.

WSN Protocols and Security Challenges for Environmental Monitoring Applications: A Survey

In recent years, communication technology has improved exponentially, partly owing to the locations and nature of the deployment of sensor nodes. Wireless sensor networks (WSNs) comprise these sensor nodes and can provide real-time physical and environmental measurements. The sensor nodes have limited power, which reduces their lifespan, especially when placed in human-inaccessible locations. This paper reviews energy-efficient protocols for environmental monitoring applications and energy harvesting-wireless sensor networks. The dynamic deployment and communication challenges associated with environmental monitoring applications (EMAs) make this paper take into account the WSN protocol stack, focusing on the physical layer, network layer (routing), and medium access control (MAC). The paper will delve deeper into the security challenges of deploying sensor nodes for environmental monitoring applications (EMAs). The paper further describes scientific approaches that churn out innovative and engineering applications that must be followed to improve environmental monitoring applications.

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.

Energy efficient medium access control protocol for data collection in wireless sensor network: A Q-learning approach

In emerging business markets, the data is becoming new gold for the industries. There are several places such as marketing, manufacturing, and analysis of future trends becoming data-intensive to achieve growth. The tiny sensor placements in the field, cities, industry, buildings and sea are helping to collect data and process it either for information retrieval or decision making. The periodic scheduling of radio transceivers assists in accomplishing efficient energy utilization in sensors often uses Time-division multiple access (TDMA) protocols for node scheduling. Our objective is to reduce the amount of time; the receiver node is in the wake-up state. Besides, the slot which potentially not being used for an extended period can utilize by other nodes. The efficient utilization of slots can help to achieve low power duty cycles with low latency. To accomplish that, we propose the emulation of the classroom learning environment with the Q-learning grading for node scheduling. We proposed an analytical mapping of WSNs to classroom learning. The initial benchmark of the performance has compared to the IEEE.802.11 (TDMA-scheduling). Further, the TDMA driven protocols such as Z-MAC, learning-driven protocols (E-MAC or aloha-Q), i-Queue are compared to evaluate the parameters such as energy consumption, throughput, and latency.

Efficient energy utilization protocol for WSNS

On-time emerging technology of research is increasing requirement for a real-time application in Wireless Sensor Networks (WSNs) has made the quality based communication protocols an interesting and hot research topic. More precisely, the networking protocols need to cope up with energy constraints, while providing precise quality guarantee. In many of these applications, the network traffic is mixed of delay sensitive and delay tolerant traffic. Hence, Quality of Service (QoS) routing becomes an important issue. The main objective of this idea is to develop the path for quality of network and to further improve throughput, routing overhead and bandwidth and at the same time to create energy enhanced way with excellent QS. In this research paper, the propose model an Energy Efficient Quality Routing Protocol (EEQRP) technique based on energy efficient protocol that can be used to design fast, tiny, more energetic and efficient way then existing routing protocols, they evaluate and compare the performance of our routing protocol (EEQRP). Network Simulator (NS2) is used to carry out and test the proposed system achieves lower average delay, more energy savings, and higher packet delivery ratio than the existing protocol.

AI-Based Resource Allocation Techniques in Wireless Sensor Internet of Things Networks in Energy Efficiency with Data Optimization

For the past few years, the IoT (Internet of Things)-based restricted WSN (Wireless sensor network) has sparked a lot of attention and progress in order to attain improved resource utilisation as well as service delivery. For data transfer between heterogeneous devices, IoT requires a stronger communication network and an ideally placed energy-efficient WSN. This study uses deep learning architectures to provide a unique resource allocation method for wireless sensor IoT networks with energy efficiency as well as data optimization. EE (Energy efficiency) and SE (spectral efficiency) are two competing optimization goals in this case. The network’s energy efficiency has been improved because of a deep neural network based on whale optimization. The heuristic-based multi-objective firefly algorithm was used to optimise the data. This proposed method is applied to optimal power allocation and relay selection. The study is for a cooperative multi-hop network topology. The best resource allocation is achieved by reducing overall transmit power, and the best relay selection is accomplished by meeting Quality of Service (QoS) standards. As a result, an energy-efficient protocol has been created. The simulation results demonstrate the suggested model’s competitive performance when compared to traditional models in terms of throughput of 96%, energy efficiency of 95%, QoS of 75%, spectrum efficiency of 85%, and network lifetime of 91 percent.

Automation of the Protocol Selection Process for IoT Systems

The Internet of Things is designed to eliminate or minimize human participation in functioning intelligent devices connected to a network for improving human living conditions and their comfort in different spheres. The rapid expansion of the Internet of Things leads to a steady increase in the number of signaling protocols and data structure protocols being developed and used in the IoT, and thus, it complicates their selection when designing the IoT system. In addition, when designing a wireless IoT network, the problem of selecting an energy-efficient protocol arises, as the constant exchange of data depletes the power supply that IoT devices are equipped with. Thus, human intervention for regular battery maintenance is required. A set of rules and criteria for the selection of optimal combination of protocols when designing the IoT system is proposed. The assessment of distributed protocols according to selected criteria based on the Boolean functions has been conducted. The developed program that enables choosing the optimal combination of protocols has been presented. Automation of the protocol selection process at the initial stage will make it possible to reduce the time for designing the IoT system.

EMEECP-IOT: Enhanced Multitier Energy-Efficient Clustering Protocol Integrated with Internet of Things-Based Secure Heterogeneous Wireless Sensor Network (HWSN)

In recent years, Internet of Things (IoT)-based constrained wireless sensor networks (WSN) have been observed with radical developments. The aligned phenomenon such as maximizing resource utilization and the delivery of efficient services is the need of the hour to suffice for the purpose of seamless connectivity. Typically, IoT devices have limited battery life and are deployed in remote areas. As a result, limited battery life limits the use of networks in some situations. To develop energy-efficient techniques for the IoT requires innovative ideas where the current techniques of using WSNs cannot directly apply to the IoT due to protocol issues, SLAs (service level agreements), scalability issues, and complexity levels. To overcome these issues, this article proposes an Enhanced Multitier Energy-Efficient Clustering Protocol integrated with the Internet of Things (EMEECP-IOT) based on the heterogeneous wireless sensor networks (HWSN) technique. The proposed approach has been compared with the current and standard protocols with respect to the parameters such as network stability, packets received, average throughput, standard deviation (SD), and residual energy. The simulation results show significantly better performance of the proposed EMEECP-IoT-based HWSN technique than the existing technique. Extensive performance factors show that the proposed EMEECP-IOT extends the network lifetime by 35% and decreases the network’s energy consumption by 21%. This proposed approach can be applied to save energy and enhance network lifetime for WSN and IoT-oriented applications.

EESR: Energy efficient sector-based routing protocol for reliable data communication in UWSNs

There is a remarkable need of advancement in data communication for application of sensor and ad-hoc networks for reliable and secure delivery of data. Due to the dynamic behavior of the network, it is an emerging demand to achieve reliability in data communication. The existence of different network environment features and diverse dynamic topology leads to the need of protocol design for efficient and reliable delivery of data in underwater acoustic sensor networks. The paper proposes energy efficient and reliable protocol design for routing data packets in Underwater Wireless Sensor Networks environment using sector based forwarding mechanism. The sector based forwarding mechanism helps in routing the reliable data in an efficient and secure manner The proposal suggests to model the network in such a way that the entire network is divided into sectors to optimize the hop count that further leads towards the energy efficient delivery of data. The mechanism of data forwarding is done vertically by maintaining sector wise sequence through pivot node which is considered as sector head. The proposed sector-based network topology mechanism is useful in identifying the number of hops used in communication along with enhancement in energy for effective data communication. The experiment performed and its consecutive results suggests that the proposed protocol enriches the energy utilization of the network. The enhancement of data communication reliability in Underwater Wireless Sensor Networks environment is managed by the mechanism of reduced hop count.

Building Information Modeling-Embedded Building Energy Efficiency Protocol for a Sustainable Built Environment and Society

In order to accurately analyze the building energy consumption and identify the problem of building energy consumption in advance, this study carries out the energy consumption analysis based on BIM (Building Information Modeling). The research object is a four-story college student dormitory in Beijing, and this set of BIM-based energy consumption simulation data was obtained using standard operating procedures (SOP). This operating procedure can start energy consumption analysis in the conceptual design stage, and developers can participate in real-time through the use of a three-dimensional information model, without additional design required. Then, comparing this study with the traditional energy consumption analysis, we see that the SOP of this research result has the following advantages: SOP function analysis is more professional, and the visual display method is more popular and intuitive; due to the flexible file format of the SOP, when data exchange is required between different software, the SOP can realize more convenient operation, and users can identify problems in the early stage of design through the SOP, correcting the scheme according to the simulation results, which is conducive to the development of the construction process. Finally, this study puts forward the analysis and estimation of energy consumption in different stages of the building life cycle, so as to provide researchers with ideas for improvement.