Showing papers on "Sensor node published in 2017"

Optimal Linear Cyber-Attack on Remote State Estimation

Abstract: Recent years have witnessed the surge of interest of security issues in cyber-physical systems. In this paper, we consider malicious cyber attacks in a remote state estimation application where a smart sensor node transmits data to a remote estimator equipped with a false data detector. It is assumed that all the sensor data can be observed and modified by the malicious attacker and a residue-based detection algorithm is used at the remote side to detect data anomalies. We propose a linear deception attack strategy and present the corresponding feasibility constraint which guarantees that the attacker is able to successfully inject false data without being detected. The evolution of the estimation error covariance at the remote estimator is derived and the degradation of system performance under the proposed linear attack policy is analyzed. Furthermore, we obtain a closed-form expression of the optimal attack strategy among all linear attacks. Comparison of attack strategies through simulated examples are provided to illustrate the theoretical results.

An Autonomous Wireless Body Area Network Implementation Towards IoT Connected Healthcare Applications

Abstract: Internet of Things (IoT) is a new technological paradigm that can connect things from various fields through the Internet. For the IoT connected healthcare applications, the wireless body area network (WBAN) is gaining popularity as wearable devices spring into the market. This paper proposes a wearable sensor node with solar energy harvesting and Bluetooth low energy transmission that enables the implementation of an autonomous WBAN. Multiple sensor nodes can be deployed on different positions of the body to measure the subject’s body temperature distribution, heartbeat, and detect falls. A web-based smartphone application is also developed for displaying the sensor data and fall notification. To extend the lifetime of the wearable sensor node, a flexible solar energy harvester with an output-based maximum power point tracking technique is used to power the sensor node. Experimental results show that the wearable sensor node works well when powered by the solar energy harvester. The autonomous 24 h operation is achieved with the experimental results. The proposed system with solar energy harvesting demonstrates that long-term continuous medical monitoring based on WBAN is possible provided that the subject stays outside for a short period of time in a day.

An overview of Wireless Sensor Networks towards internet of things

Abstract: With the advancements in wireless technology and digital electronics, some tiny devices have started to be used in numerous areas in daily life. These devices are capable of sensing, computation and communicating. They are generally composed of low power radios, several smart sensors and embedded CPUs (Central Processing Units). These devices are used to form wireless sensor network (WSN) which is necessary to provide sensing services and to monitor environmental conditions. In parallel to WSNs, the idea of internet of things (IoT) is developed where IoT can be defined as an interconnection between identifiable devices within the internet connection in sensing and monitoring processes. This paper presents detailed overview of WSNs. It also assesses the technology and characteristics of WSNs. Moreover, it provides a review of WSN applications and IoT applications.

On Theoretical Modeling of Sensor Cloud: A Paradigm Shift From Wireless Sensor Network

Abstract: This paper focuses on the theoretical modeling of sensor cloud, which is one of the first attempts in this direction. We endeavor to theoretically characterize virtualization, which is a fundamental mechanism for operations within the sensor-cloud architecture. Existing related research works on sensor cloud have primarily focused on the ideology and the challenges that wireless sensor network (WSN)-based applications typically encounter. However, none of the works has addressed theoretical characterization and analysis, which can be used for building models for solving different problems to be encountered in using sensor cloud. We present a mathematical formulation of sensor cloud, which is very important for studying the behavior of WSN-based applications in the sensor-cloud platform. We also suggested a paradigm shift of technology from traditional WSNs to sensor-cloud architecture. A detailed analysis is made based on the performance metrics, i.e., energy consumption, fault tolerance, and lifetime of a sensor node. A thorough evaluation of the cost effectiveness of sensor cloud is also done by examining the cash inflow and outflow characteristics from the perspective of every actor of the sensor cloud. Analytical results show that the sensor-cloud architecture outperforms a traditional WSN, by increasing the sensor lifetime by 3.25% and decreasing the energy consumption by 36.68%. We also observe that the technology shift to sensor cloud reduces the expenditure of an end user by 14.72%, on average.

Ultimate Boundedness Control for Networked Systems With Try-Once-Discard Protocol and Uniform Quantization Effects

Abstract: This paper is concerned with the ultimate boundedness control problem for a class of networked nonlinear systems subject to the try-once-discard (TOD) protocol scheduling and uniform quantization effects. To prevent the transmission data from collisions, the communication between sensor nodes and the controller is implemented via a constrained communication channel, where only one sensor node is permitted to transmit data at each time instant. The TOD protocol is utilized to regulate the signal transmission over the communication network under which the scheduling behavior is described by a special switching function. On the other hand, the uniform quantization effects of the network are characterized by a round function (i.e., the nearest integer function). The purpose of the addressed problem is to design an observer-based controller for the networked nonlinear systems such that, in the presence of TOD protocol and uniform quantization effects, the closed-loop system is ultimately bounded and the controlled output is locally minimized. Sufficient conditions are established to guarantee the ultimate boundedness of the dynamics of the closed-loop system in mean square by applying the stochastic analysis approach. Furthermore, the desired controller gains are derived by solving a convex optimization problem. Finally, a numerical example is given to illustrate the effectiveness of the proposed controller design scheme.

Energy Efficient Hierarchical Clustering Approaches in Wireless Sensor Networks: A Survey

Abstract: Wireless sensor networks (WSN) are one of the significant technologies due to their diverse applications such as health care monitoring, smart phones, military, disaster management, and other surveillance systems. Sensor nodes are usually deployed in large number that work independently in unattended harsh environments. Due to constraint resources, typically the scarce battery power, these wireless nodes are grouped into clusters for energy efficient communication. In clustering hierarchical schemes have achieved great interest for minimizing energy consumption. Hierarchical schemes are generally categorized as cluster-based and grid-based approaches. In cluster-based approaches, nodes are grouped into clusters, where a resourceful sensor node is nominated as a cluster head (CH) while in grid-based approach the network is divided into confined virtual grids usually performed by the base station. This paper highlights and discusses the design challenges for cluster-based schemes, the important cluster formation parameters, and classification of hierarchical clustering protocols. Moreover, existing cluster-based and grid-based techniques are evaluated by considering certain parameters to help users in selecting appropriate technique. Furthermore, a detailed summary of these protocols is presented with their advantages, disadvantages, and applicability in particular cases.

An improved and anonymous two-factor authentication protocol for health-care applications with wireless medical sensor networks

Abstract: Wireless sensor networks (WSNs) are fast developed and widely used in many applications. One of the most important applications is wireless medical sensor network (WMSN) which makes modern health-care more popular. The doctor can get the patient's physiological data collected by special sensors deployed on or in the patient's body in real time with the mobile devices via the wireless communication channel. The collected data are important and should be confidential. So security measures are considered in the process of communication. Recently, He et al. (Multimed Syst, 21(1), 49---60, 2015) proposed a new two-factor authentication scheme for health-care with WMSNs and claimed it to be secure. But we find that it is vulnerable to the off-line guessing attack, the user impersonation attack, and the sensor node capture attack. Moreover, we present an improved scheme to overcome the disadvantages. Through the formal verification with Proverif and the analysis presented by us, our scheme is secure. It is more practical for applications through the comparison between some recent schemes for WMSNs.

Smart Random Neural Network Controller for HVAC Using Cloud Computing Technology

Abstract: Smart homes reduce human intervention in controlling the heating ventilation and air conditioning (HVAC) systems for maintaining a comfortable indoor environment. The embedded intelligence in the sensor nodes is limited due to the limited processing power and memory in the sensor node. Cloud computing has become increasingly popular due to its capability of providing computer utilities as internet services. In this study, a model for the intelligent controller by integrating internet of things (IoT) with cloud computing and web services is proposed. The wireless sensor nodes for monitoring the indoor environment and HVAC inlet air, and wireless base station for controlling the actuators of HVAC have been developed. The sensor nodes and base station communicate through RF transceivers at 915 MHz. Random neural network (RNN) models are used for estimating the number of occupants, and for estimating the predicted-mean-vote-based setpoints for controlling the heating, ventilation, and cooling of the building. Three test cases are studied (Case 1—Data storage and implementation of RNN models on the cloud, Case 2—RNN models implementation on base station, Case 3—Distributed implementation of RNN models on sensor nodes and base stations) for determining the best architecture in terms of power consumption. The results have shown that by embedding the intelligence in the base station and sensor nodes (i.e., Case 3), the power consumption of the intelligent controller was 4.4% less than Case 1 and 19.23% less than Case 2.

Cooperative Control of Mobile Sensor Networks for Environmental Monitoring: An Event-Triggered Finite-Time Control Scheme

Abstract: This paper deals with the problem of environmental monitoring by developing an event-triggered finite-time control scheme for mobile sensor networks. The proposed control scheme can be executed by each sensor node independently and consists of two parts: one part is a finite-time consensus algorithm while the other part is an event-triggered rule. The consensus algorithm is employed to enable the positions and velocities of sensor nodes to quickly track the position and velocity of a virtual leader in finite time. The event-triggered rule is used to reduce the updating frequency of controllers in order to save the computational resources of sensor nodes. Some stability conditions are derived for mobile sensor networks with the proposed control scheme under both a fixed communication topology and a switching communication topology. Finally, simulation results illustrate the effectiveness of the proposed control scheme for the problem of environmental monitoring.

Real-Time Performance of a Self-Powered Environmental IoT Sensor Network System.

Abstract: Wireless sensor networks (WSNs) play an increasingly important role in monitoring applications in many areas. With the emergence of the Internet-of-Things (IoT), many more lowpower sensors will need to be deployed in various environments to collect and monitor data about environmental factors in real time. Providing power supply to these sensor nodes becomes a critical challenge for realizations of IoT applications as sensor nodes are normally battery-powered and have a limited lifetime. This paper proposes a wireless sensor network that is powered by solar energy harvesting. The sensor network monitors the environmental data with low-power sensor electronics and forms a network using multiple XBee wireless modules. A detailed performance analysis of the network system under solar energy harvesting has been presented. The sensor network system and the proposed energy-harvesting techniques are configured to achieve a continuous energy source for the sensor network. The proposed energy-harvesting system has been successfully designed to enable an energy solution in order to keep sensor nodes active and reliable for a whole day. The paper also outlines some of our experiences in real-time implementation of a sensor network system with energy harvesting.

The Optimal Deployment, Coverage, and Connectivity Problems in Wireless Sensor Networks: Revisited

Abstract: Finding an optimal node deployment strategy in wireless sensor networks (WSNs) that would reduce cost, be robust to node failures, reduce computation, and communication overhead, and guarantee a high level of coverage along with network connectivity is a difficult problem. In fact, sensing coverage and network connectivity are two of the most fundamental problems in WSNs as they can directly impact the network lifetime and operation. In this paper, we consider deriving optimal conditions for connectivity with coverage in WSNs. Most versions of this problem are (NP-complete), while approximation algorithms cannot be developed for some versions of polynomial time, unless P = NP. Hence, we also develop a heuristic for some versions of the problem and the efficacy of the heuristic will be evaluated through extensive simulations. We are also interested in determining the probability of finding a path between a given pair of nodes over a given topology of WSNs. This will serve as a measure of connectivity with coverage of the network. Hence, we derive necessary and sufficient conditions for connectivity with coverage over a clustered structure in WSNs. Then, employing queuing networks modeling techniques, we present a dynamic programming study of the connectivity with coverage of clustered structure and its effect on routing in generalized WSNs. The performance evaluation of the proposed schemes shows that availability of nodes, sensor node coverage, and the connectivity were sufficiently enhanced to maximize network lifetime.

A survey on energy efficient coverage protocols in wireless sensor networks

Abstract: A Wireless Sensor Network (WSN) is used to monitor an area for events. Each node in the WSN has a sensing range and a communication range. The sensing coverage of a sensor node is the area determined by the sensing range of the sensor node. Sensing coverage of the network is the collective coverage of the sensor nodes in a WSN. Sufficient number of sensor nodes need to be deployed to ensure adequate coverage of a region. Further, since sensor nodes have limited battery life, it is also essential to reduce the energy consumption. This would help improve the network lifetime and thus the coverage lifetime. To reduce energy consumption in the WSN, some of the nodes with overlapping sensing areas could be turned off using a coverage optimization protocol. In this paper, we discuss various coverage optimization protocols. These protocols are broadly classified as clustering and distributed protocols. Further, these protocols are classified based on the type of sensing model used, node location information, and mechanism used to determine neighboring node information (based on probe or computational geometry). In this paper, we review the key coverage optimization protocols and present open research issues related to energy efficient coverage.

Wireless-Powered Sensor Networks: How to Realize

Abstract: In this paper, we study a multi-antenna wireless-powered sensor network (WPSN), in which a power beacon wirelessly transfers electric energy to a sensor node via an electromagnetic wave We have implemented a real-life multi-antenna WPSN testbed and conducted extensive experiments on the testbed The key technology for the high-efficiency WPSN is an adaptive energy beamforming scheme that dynamically steers a microwave beam towards a sensor node We propose a receive power-based channel estimation and energy beamforming algorithm In addition, an adaptive duty cycle control algorithm is proposed to prevent energy storage of a sensor node from being depleted The proposed duty cycle control algorithm is designed based on a proportional–integral–derivative controller These algorithms are all implemented in the multi-antenna WPSN testbed By experiments, we validate the feasibility of the multi-antenna WPSN, and show the performance of the proposed algorithms

RF Energy Harvesting Wireless Powered Sensor Networks for Smart Cities

Abstract: This paper investigates the optimal energy beamforming and time assignment in radio frequency (RF) energy harvesting (EH) wireless powered sensor networks for smart cities, where sensor nodes (SNs) first harvest energy from a sink node, and then transmit their collected data to the sink node via time-division-multiple-access (TDMA) manner by using the harvested energy In order to achieve green system design, we formulate a problem to minimize the energy requirement of the sink node to support transmission between the sink node and the SNs under data amount constraint and EH constraint For practical design, the energy consumed by circuit and information processing is also considered Since the problem is non-convex, we use semidefinite relaxation (SDR) method to relax it into a convex optimization problem and then solve it efficiently We theoretically prove that when the number of SNs are not greater than two, the relaxed problem guarantees rank-one constraint and when the number of SNs exceeds two, our obtained results are very close to the optimal ones Simulation results show that when the data amount is relatively small, the energy consumed by circuit and information processing affects the system performance greatly, but for a relatively large data amount, the energy requirement of the sink node on its own signal processing is affected very limited and the system energy requirement is dominated by the transmit power consumption at the SNs Furthermore, we also discuss the effects of the other parameters on the system performance, which provide some useful insights in future smart city planning

Development of an Indoor Photovoltaic Energy Harvesting Module for Autonomous Sensors in Building Air Quality Applications

Abstract: A 50 mm ${\times } \,\, 20$ mm ${\times } \,\, 15$ mm indoor photovoltaic (PV) energy harvesting power module (IPEHPM) has been developed for powering an Internet of Things (IoT) sensor node containing a low-power CO2 sensor for automatic building ventilation It is composed of a high efficiency PV energy harvesting module and a supercapacitor to produce 36–42 V output voltage with 100 mA pulse current for up to 600 ms Storage efficiency analysis and storage efficiency tests of the IPEHPM have demonstrated that with the adopted simple power management scheme, which exempts the commonly used power management blocks of the voltage regulator and the maximum power point tracking to save power, 887% average storage efficiency has been achieved at 200 lux With the newly established PV powering model, the power consumption requirements of an IoT node can be directly converted into the illumination requirements of the PV energy harvester, making the IPEHPM easy to use IPEHPM powered IoT experiments with a low-power CO2 gas sensor have demonstrated that the IPEHPM is suitable for IoT-based building ventilation applications, where the CO2 concentration level is measured every 150 s at the indoor lighting condition down to 200 lux

Design and Implementation of a Cloud Enabled Random Neural Network-Based Decentralized Smart Controller With Intelligent Sensor Nodes for HVAC

Abstract: Building energy management systems (BEMSs) monitor and control the heating ventilation and air conditioning (HVAC) of buildings in addition to many other building systems and utilities. Wireless sensor networks (WSNs) have become the integral part of BEMS at the initial implementation phase or latter when retro fitting is required to upgrade older buildings. WSN enabled BEMS, however, have several challenges which are managing data, controllers, actuators, intelligence, and power usage of wireless components (which might be battery powered). The wireless sensor nodes have limited processing power and memory for embedding intelligence in the sensor nodes. In this paper, we present a random neural network (RNN)-based smart controller on a Internet of Things (IoT) platform integrated with cloud processing for training the RNN which has been implemented and tested in an environment chamber. The IoT platform is modular and not limited to but has several sensors for measuring temperature, humidity, inlet air coming from the HVAC duct and PIR. The smart RNN controller has three main components: 1) base station; 2) sensor nodes; and 3) the cloud with embedded intelligence on each component for different tasks. This IoT platform is integrated with cloud processing for training the RNN. The RNN-based occupancy estimator is embedded in sensor node which estimates the number of occupants inside the room and sends this information to the base station. The base station is embedded with RNN models to control the HVAC on the basis of setpoints for heating and cooling. The HVAC of the environment chamber consumes 27.12% less energy with smart controller as compared to simple rule-based controllers. The occupancy estimation time is reduced by our proposed hybrid algorithm for occupancy estimation that combines RNN-based occupancy estimator with door sensor node (equipped with PIR and magnetic reed switch). The results show that accuracy of hybrid RNN occupancy estimator is 88%.

Energy Harvesting Hybrid Acoustic-Optical Underwater Wireless Sensor Networks Localization.

Abstract: Underwater wireless technologies demand to transmit at higher data rate for ocean exploration. Currently, large coverage is achieved by acoustic sensor networks with low data rate, high cost, high latency, high power consumption, and negative impact on marine mammals. Meanwhile, optical communication for underwater networks has the advantage of the higher data rate albeit for limited communication distances. Moreover, energy consumption is another major problem for underwater sensor networks, due to limited battery power and difficulty in replacing or recharging the battery of a sensor node. The ultimate solution to this problem is to add energy harvesting capability to the acoustic-optical sensor nodes. Localization of underwater sensor networks is of utmost importance because the data collected from underwater sensor nodes is useful only if the location of the nodes is known. Therefore, a novel localization technique for energy harvesting hybrid acoustic-optical underwater wireless sensor networks (AO-UWSNs) is proposed. AO-UWSN employs optical communication for higher data rate at a short transmission distance and employs acoustic communication for low data rate and long transmission distance. A hybrid received signal strength (RSS) based localization technique is proposed to localize the nodes in AO-UWSNs. The proposed technique combines the noisy RSS based measurements from acoustic communication and optical communication and estimates the final locations of acoustic-optical sensor nodes. A weighted multiple observations paradigm is proposed for hybrid estimated distances to suppress the noisy observations and give more importance to the accurate observations. Furthermore, the closed form solution for Cramer-Rao lower bound (CRLB) is derived for localization accuracy of the proposed technique.

Fuzzy-Logic Based Distributed Energy-Efficient Clustering Algorithm for Wireless Sensor Networks.

Abstract: Due to the high-energy efficiency and scalability, the clustering routing algorithm has been widely used in wireless sensor networks (WSNs). In order to gather information more efficiently, each sensor node transmits data to its Cluster Head (CH) to which it belongs, by multi-hop communication. However, the multi-hop communication in the cluster brings the problem of excessive energy consumption of the relay nodes which are closer to the CH. These nodes’ energy will be consumed more quickly than the farther nodes, which brings the negative influence on load balance for the whole networks. Therefore, we propose an energy-efficient distributed clustering algorithm based on fuzzy approach with non-uniform distribution (EEDCF). During CHs’ election, we take nodes’ energies, nodes’ degree and neighbor nodes’ residual energies into consideration as the input parameters. In addition, we take advantage of Takagi, Sugeno and Kang (TSK) fuzzy model instead of traditional method as our inference system to guarantee the quantitative analysis more reasonable. In our scheme, each sensor node calculates the probability of being as CH with the help of fuzzy inference system in a distributed way. The experimental results indicate EEDCF algorithm is better than some current representative methods in aspects of data transmission, energy consumption and lifetime of networks.

Resilience of DoS Attacks in Designing Anonymous User Authentication Protocol for Wireless Sensor Networks

Abstract: Wireless sensor networks (WSNs) include spatially allotted autonomous instruments that employ sensors to check environmental or physical conditions. These autonomous instruments or nodes blend with routers or gateway to make several WSN-based real-time applications. In many critical applications, an external user can directly access the real-time data from sensor node. In this context, before offering access, the legitimacy of the user is required to be verified through a secure authentication scheme. Since, in WSN-based real-time applications, the privacy of the user is greatly important, the authentication scheme for such environment should be anonymous. Till now, impressive efforts have been made in designing lightweight anonymous authentication protocol for WSN-based real-time applications. However, most of such protocols are vulnerable to DoS attacks, which are occurred due to the loss of synchronization between the participants. Furthermore, to rebuilt synchronization between the participants, a protocol may need to compromise un-link-ability property. Therefore, it can be argued that the problem of DoS attack has not been addressed properly in the existing literatures. In this paper, we present a way to deal with DoS attacks in designing lightweight anonymous authentication protocol for WSN-based real-time applications without compromising any anonymity support. We argue that our proposed solution can easily be incorporated with the existing schemes to be resilient to DoS attacks.

Ambient Backscatterers Using FM Broadcasting for Low Cost and Low Power Wireless Applications

Abstract: Nowadays, the explosive growth of Internet-of-Things-related applications has required the design of low-cost and low-power wireless sensors. Although backscatter radio communication is a mature technology used in radio frequency (RF) identification applications, ambient backscattering is a novel approach taking advantage of ambient signals to simplify wireless system topologies to just a sensor node and a receiver (RX) circuit eliminating the need for a dedicated carrier source. This paper introduces a novel wireless tag and RX system that utilizes broadcast frequency modulated (FM) signals for backscatter communication. The proposed proof-of-concept tag comprises of an ultralow-power microcontroller (MCU) and a RF front-end for wireless communication. The MCU can accumulate data from multiple sensors through an analog-to-digital converter, while it transmits the information back to the RX through the front-end by means of backscattering. The front-end uses ON–OFF keying modulation and FM0 encoding on ambient FM station signals. The RX consists of a commercial low-cost software-defined radio which downconverts the received signal to baseband and decodes it using a suitable signal processing algorithm. A theoretical analysis of the error rate performance of the system is provided and compared to bit-error-rate measurements on a fixed transmitter-tag-RX laboratory setup with good agreement. The prototype tag was also tested in a real-time indoor laboratory deployment. Operation over a 5-m tag-reader distance was demonstrated by backscattering information at 2.5 kb/s featuring an energy per packet of $36.9~\mu \text{J}$ .

A Wearable Wireless Sensor Network for Indoor Smart Environment Monitoring in Safety Applications

Abstract: This paper presents the implementation of a wearable wireless sensor network aimed at monitoring harmful gases in industrial environments. The proposed solution is based on a customized wearable sensor node using a low-power low-rate wireless personal area network (LR-WPAN) communications protocol, which as a first approach measures CO2 concentration, and employs different low power strategies for appropriate energy handling which is essential to achieving long battery life. These wearables nodes are connected to a deployed static network and a web-based application allows data storage, remote control and monitoring of the complete network. Therefore, a complete and versatile remote web application with a locally implemented decision-making system is accomplished, which allows early detection of hazardous situations for exposed workers.

Rendezvous based routing protocol for wireless sensor networks with mobile sink

Abstract: In wireless sensor networks, the sensor nodes find the route towards the sink to transmit data. Data transmission happens either directly to the sink node or through the intermediate nodes. As the sensor node has limited energy, it is very important to develop efficient routing technique to prolong network life time. In this paper we proposed rendezvous-based routing protocol, which creates a rendezvous region in the middle of the network and constructs a tree within that region. There are two different modes of data transmission in the proposed protocol. In Method 1, the tree is directed towards the sink and the source node transmits the data to the sink via this tree, whereas in Method 2, the sink transmits its location to the tree, and the source node gets the sink's location from the tree and transmits the data directly to the sink. The proposed protocol is validated through experiment and compared with the existing protocols using some metrics such as packet delivery ratio, energy consumption, end-to-end latency, network life time.

Optimized Multi-Constrained Quality-of-Service Multipath Routing Approach for Multimedia Sensor Networks

Abstract: Modern multimedia sensor networks impose strict constraints on both the delay and energy consumption when time-critical data must be reported to the sink within a limited bandwidth without any loss. Failure to transmit an event to the sink occurs for many reasons, including inherence limitations of sensors, power consumption, and reliability. We propose a mathematical model for a novel quality-of-service (QoS) routing-determination method. The proposed scheme enables determining the optimal path to provide appropriate shared radio satisfying the QoS for a wide range of real-time intensive media. The mathematical model is based on the Lagrangian relaxation method, to control adaptive switching of hop-by-hop QoS routing protocols. The embedded criteria for each objective function are used to decide which path from source to sink will be selected. Simulation results show that, compared with existing routing protocols, the approach proposed in this paper significantly improves the packet received ratio, energy consumption, and average end-to-end delay of the sensor node.