Terms Of Network Lifetime Research Articles

RPL based on triangle module operator for AMI networks

The routing protocol for low-power and lossy networks (RPL) has been used in advanced metering infrastructure (AMI) which could provide two-way communication between smart meters and city utilities. To improve the network performance of AMI networks, this paper proposed an improved algorithm of RPL based on triangle module operator (IAR-TMO). IAR-TMO proposes membership functions of the following five typical routing metrics: end-to-end delay, number of hops, expected transmission count (ETX), node remaining energy, and child node count. Moreover, IAR-TMO uses triangle module operator to fuse membership functions of these routing metrics. Then, IAR-TMO selects preferred parents (the next hop) based on the triangle module operator. Theoretical analysis and simulation results show that IAR-TMO has a great improvement when compared with two recent representative algorithms: ETXOF (ETX Objective Function) and OF-FL (Objective Function based on Fuzzy Logic), in terms of network lifetime, average end-to-end delay, etc. Consequently, the network performances of AMI networks can be improved effectively.

Energy efficient link stable routing in internet of things

In future communication networks with Internet of Things (IoT), each of the smart devices will be able to communicate with other smart devices ubiquitously throughout the time clock. These smart devices contain limited amount of energy, memory, and processing power. Additionally, short range radios are very susceptible to noise, multi route distortion, and interference. In this context this paper proposes an energy efficient link stable routing (EELSR) to conserve energy of the smart devices and to account link stability for enhancing the network lifetime. In order to verify the correctness of the proposed routing, first, analytical models for link stability, and residual energy of a route have proposed, second, an optimal route selection algorithm that uses residual energy of a route, link stability of a route, and route distance, has been designed. The performance of the proposed EELSR is evaluated and compared with AODV and REL in the terms of network life time, packet delivery ratio, routing success probability, and route setup delay. EELSR outperforms the state of art routing algorithms.

Cluster-Head Restricted Energy Efficient Protocol (CREEP) for Routing in Heterogeneous Wireless Sensor Networks

A magnanimous number of collaborative sensor nodes make up a Wireless Sensor Network (WSN). These sensor nodes are outfitted with low-cost and low-power sensors. The routing protocols are responsible for ensuring communications while considering the energy constraints of the system. Achieving a higher network lifetime is the need of the hour in WSNs. Currently, many network layer protocols are considering a heterogeneous WSN, wherein a certain number of the sensors are rendered higher energy as compared to the rest of the nodes. In this paper, we have critically analysed the various stationary heterogeneous clustering algorithms and assessed their lifetime and throughput performance in mobile node settings also. Although many newer variants of Distributed Energy-Efficiency Clustering (DEEC) scheme execute proficiently in terms of energy efficiency, they suffer from high system complexity due to computation and selection of large number of Cluster Heads (CHs). A protocol in form of Cluster-head Restricted Energy Efficient Protocol (CREEP) has been proposed to overcome this limitation and to further improve the network lifetime by modifying the CH selection thresholds in a two-level heterogeneous WSN. Simulation results establish that proposed solution ameliorates in terms of network lifetime as compared to others in stationary as well as mobile WSN scenarios.

CIRCLES ROUTING PROTOCOL FOR WIRELESS SENSOR NETWORK

Abstract: Wireless Sensor Network (WSN) is an emerging technology for monitoring physical world.WSN consists of large number of sensor nodes operated by battery mostly in harsh environment. These wireless nodes are very limited in battery power and communication processes. Gathering sensed information in an efficient manner is critical to operate the sensor network for a long period time. In this paper, a new Routing Protocol CRP (Circles Routing Protocol) is proposed. The CRP is developed for achieving QoS (Quality of Service) in terms of network life time, power consumption, packet delivery, and network throughput by distributing the energy load among all sensor nodes. The dynamic behavior of the proposed CRP depends on executing the following steps.Firstly, CRP cutting down the playground into many clusters by using the advantage of the grid construction to physically partition the playground into many small individual clusters. Secondly, CRP electing one node in each cluster, as a Cluster Head (CH), form a circular chain within each cluster to collect and fuse data from the other nodes. Thirdly, CRP collecting every four adjacent clusters in one group called inter four clusters. Then, CRP constructing a circular chain within these four clusters containing the four CH nodes. Fourthly, CRP electing one of these CH nodes as an inter CH node to collect and fuse data from the other CH nodes. Finally, CRP constructing a circular chain containing the four inter CH nodes. Then CRP electing one of inter CH nodes to be the outer CH node which collects and fuses the datafrom the other nodes and subsequently transmit this data to the Base Station (BS). In the performanceanalysis, we use the NS-2 Simulator as a simulation technique to study and analysis the performance ofCRP protocol. To verify from the correctness of the obtained performance results, we compare the CRPresults with those obtained from LEACH (Low-Energy Adaptive Clustering Hierarchy) and PEGASIS(Power-Efficient Gathering in Sensor Information System) protocols.

An Improved Clustering Protocol for Energy Heterogeneous WSN

This paper studies on the problem that the unreasonable choice of clustered routing protocol cluster head of energy heterogeneous WSN and the overload of some cluster head node which are far away from the base station in remote communication. And an improved clustering routing protocol based on energy and density for heterogeneous wireless sensor networks is proposed. Firstly, the optimal number of cluster head is got according to the network energy consumption model, and the node density factor is modified. Then, the new threshold is established by considering the residual energy of the node, the node density and the distance from the node to the BS. The cluster head communicates with the BS by using a single hop and a hybrid way through a relay node to reduce the cluster head load of the remote base station. Finally, the simulation results based on OMNet++ and Matlab show that the improved protocol has better performance in terms of network lifetime and network energy consumption compared with existing protocols.

Study on the effect of sink moving trajectory on wireless sensor networks

Wireless sensor networks are developing very fast in recent years, due to their wide potential applications. However there exists the so-called hot spot problem, namely the nodes close to static sink node tend to die earlier than other nodes since they have heavier burden to forward. The introduction of mobile sink node can effectively alleviate this problem since sink node can move along certain trajectories, causing hot spot nodes more evenly distributed. In this paper, we make extensive experimental simulations for circular sensor network, with one mobile sink moving along different radius circumference. The whole network is divided into several clusters and there is one cluster head (CH) inside each cluster. The ordinary sensors communicate with CH and CHs construct a chain until the sink node. Simulation results show that the best network performance appears when sink moves along 0.25 R in terms of network lifetime.

ENERGY EFFICIENT DISTRIBUTED CLUSTERING AND SCHEDULING ALGORITHM FOR WIRELESS SENSOR NETWORKS WITH NON-UNIFORM NODE DISTRIBUTION

Abstract- The lifetime of Randomly Distributed wireless sensor networks gets effected do to the imbalanced energy consumption in sensor nodes. In order to balance the energy consumption among sensor nodes an energy efficient clustering algorithm is proposed in this paper. EECS is divided into two cluster setup phase and steady state phase. The cluster head is selected by new cluster election algorithm which uses local information of sensor nodes. The allocation of time slots for member nodes is done as per data available in sensor nodes in steady state phase. The simulation results of EECS algorithm is better than EADC and SA-EADC algorithm in terms of network lifetime and energy consumption.

EAPC: Energy-Aware Path Construction for Data Collection Using Mobile Sink in Wireless Sensor Networks

Data collection is one of the paramount concerns in wireless sensor networks. Many data collection algorithms have been proposed for collecting data in particular monitoring regions. However, the efficiency of the paths for such data collection can be improved. This paper proposes an energy-aware path construction (EAPC) algorithm, which selects an appropriate set of data collection points, constructs a data collection path, and collects data from the points burdened with data. EAPC is intended to prolong the network lifetime, it accounts for the path cost from its current data collection point to the next point and the forwarding load of each sensor node. Performance evaluation reveals that the proposed EAPC has more efficient performance than existing data collection mechanisms in terms of network lifetime, energy consumption, fairness index, and efficiency index.

Energy efficient wireless sensor network with efficient data handling for real time landslide monitoring system using fuzzy data mining technique

Wireless sensor network (WSN) is one of the emerging areas which are extensively being used for development of real time monitoring systems. Landslides are the major cause of loss of life, human settlements, agriculture, forestland, and lead to damage of communication routes. In this paper, we propose new landslide monitoring system with maximising the life time of sensor nodes by avoiding link failure in routing protocol. The cluster-based routing protocol with the sensor nodes is capable of data acquisition, data storage, data processing, and wireless data transmission. Then, collected data's are aggregated using fuzzy data mining technique which maximise lifetime of all sensor nodes in the network area. The proposed approach is implemented and results are obtained through NS-2 simulation shows that the proposed algorithm performs better than other landslide monitoring systems in terms of network life time, sensor node life time, data transmission and energy consumption.

Comparison and Analysis on Artificial Intelligence Based Data Aggregation Techniques in Wireless Sensor Networks

In modern era WSN, data aggregation technique is the challenging area for researchers from long time. Numbers of researchers have proposed neural network (NN) and fuzzy logic based data aggregation methods in Wireless Environment. The main objective of this paper is to analyse the existing work on artificial intelligence (AI) based data aggregation techniques in WSNs. An attempt has been made to identify the strength and weakness of AI based techniques. In addition to this, a modified protocol is designed and developed. And its implementation also compared with other existing approaches ACO and PSO. Proposed approach is better in terms of network lifetime and throughput of the networks. In future an attempt can be made to overcome the existing challenges during data aggregation in WSN using different AI and Meta heuristic based techniques.

Comparative Analysis of Bio inspired Optimization Techniques in Wireless Sensor Networks with GA-PSO Approach

Objectives: This research paper is fixated to evaluate the performance of wireless sensor network by employing Bio inspired optimization techniques. In this work, it has been proposed to explore the possibilities of optimization procedures in order to improve the performance of wireless sensor networks. Methods/Analysis: We seek to optimize the Quality of service in wireless sensor network via routing. In order to raise the lifetime of the wireless sensor network load balancing of cluster heads is implemented here in this research work with this the energy consumption could be reduced long with less Error Rate and less Routing Overhead, Minimization of End to end delay and improving Throughput. Findings: In this work, the performance analysis has been evaluated for the different optimization techniques like Genetic algorithm, Particle Swarm optimization, and bacterial foraging optimization and Hybrid approach of GA-PSO optimization. First of all, the optimization techniques such as GA, PSO and BFO are adopted separately on WSN setup and after that the hybridization of GA and PSO is employed. In the existing work Load balancing was employed with GA optimization but in this work other techniques are also taken along with hybridization of GA and PSO. A comparison on the performance analysis of all the optimization algorithms is specified and to infer which of the techniques performs better in order to maximizing the network lifetime and minimizing the end to end delay of the wireless sensor network so that packets transferring is carried efficiently with a reduced amount of error rate so that there will be a lesser chance of the node failure and extend the network lifetime for the awareness of routing optimization. Improvement: Further hybridization of other optimization techniques can be implemented for the improvements of wireless sensor networks. Keywords: Wireless Sensor Networks, Network Performance in Terms of Network Lifetime and End to End Delay, BFO, GA, GA-PSO, PSO

NetBAN, a concept of network of BANs for cooperative communication: energy awareness routing solution

In this paper, a NetBAN which is a concept of network of body area networks (BANs) or wireless body area networks (WBANs) is introduced and a routing solution intending to help a group of WBANs to cooperate for relaying packets according to the energy consumption rate and the communication link quality is proposed. The main goal is to provide to the sensors a technique that helps them deliver their data even when the coordinator's battery is very low or empty or else the connection to the access point is lost, what leads to balancing energy consumption between cooperating coordinators. For this purpose, an energy threshold-based technique is used and energy-aware optimised link state routing (EA-OLSR) is defined and used. Simulation results show interesting performances in terms of network lifetime with a gain of about 30% and data delivery about 20%.

Compressed Sensing Based Joint Rate Allocation and Routing Design in Wireless Sensor Networks

Compressed sensing for wireless sensor networks has attracted a lot of research attention in the last decade for its advantages in energy saving, robustness, and so on. Nevertheless, existing solutions mostly focus on the data compression performance while neglecting the energy efficiency. In this paper, we first present the joint resource allocation problem formulation based on compressed sensing. Then a distributed algorithm to compute the sampling rate and routes utilizing local network status is proposed. We conduct extensive experiments based on meteorological wireless sensor networks to verify the merit of our mechanism; it is shown that the proposed mechanism is able to achieve very high efficiency in terms of network lifetime and sensing quality compared with existing approaches.

Pre-Scheduled and Self Organized Sleep-Scheduling Algorithms for Efficient K-Coverage in Wireless Sensor Networks.

The K-coverage configuration that guarantees coverage of each location by at least K sensors is highly popular and is extensively used to monitor diversified applications in wireless sensor networks. Long network lifetime and high detection quality are the essentials of such K-covered sleep-scheduling algorithms. However, the existing sleep-scheduling algorithms either cause high cost or cannot preserve the detection quality effectively. In this paper, the Pre-Scheduling-based K-coverage Group Scheduling (PSKGS) and Self-Organized K-coverage Scheduling (SKS) algorithms are proposed to settle the problems in the existing sleep-scheduling algorithms. Simulation results show that our pre-scheduled-based KGS approach enhances the detection quality and network lifetime, whereas the self-organized-based SKS algorithm minimizes the computation and communication cost of the nodes and thereby is energy efficient. Besides, SKS outperforms PSKGS in terms of network lifetime and detection quality as it is self-organized.

Sensor selection for extending lifetime of multi-channel cooperative sensing in cognitive sensor networks

Wireless cognitive sensor networks (WCSNs) are composed of tiny, low-power and low-cost sensors. An important function of these networks is to sense the channels in order to find the spectrum holes. Sensors cannot sense more than one channel simultaneously because they do not have high-speed Analog-to-Digital-Converters (ADCs) which need high-power batteries. Therefore, it is a challenging issue to select cooperative sensors to sense different channels so that all the channels can be sensed simultaneously. On the other hand, lifetime extending in a WCSN is an important issue; it has attracted the most attention recently. In this paper, a tuneable receiver is used for sensors so that they can sense different channels in different sensing periods. To reduce energy consumption, node selection is proposed so that only sufficient nodes perform sensing the channels while the sensing quality constraints are met. A subset of nodes to sense every channel is selected in a way that the residual energy of sensors is balanced and the network lifetime is maximized. The problem can be solved based on the convex optimization framework. Closed form priorities of sensors to sense different channels are determined based on their residual energy, distance and detection probability. Then efficient dynamic sensor selection algorithms are proposed for multi-channel CSS. Simulation results show the advantages of the proposed algorithms in finding the efficient answer. In addition, in terms of network lifetime, success percentage, and energy consumption, the proposed algorithms are compared with the other sensor selection methods.

EA-CRP: A Novel Energy-aware Clustering and Routing Protocol in Wireless Sensor Networks

This paper proposes a novel energy-aware and layering-based clustering and routing protocol (EA-CRP) for gathering data in WSNs. The main goal of EA-CRP is to reduce the energy consumption among all sensor nodes in the network. To achieve this goal, EA-CRP employs an innovative multilayered architecture. More specifically, we divide the field into a number of layers where the width of a layer not only decreases towards the base station, but also is composed of a certain number of clusters (sub layers). The proposed design not only shortens the communication distance between nodes, but also decreases the amount of communication overhead required for setting up clusters. Furthermore, a multi-hop routing algorithm for inter-cluster communications is proposed which basically considers the tradeoff between distance and the energy of relaying nodes. The effectiveness of EA-CRP is verified through comparing its results with those obtained from previous relevant protocols. Interestingly, our experimental results show that EA-CRP has superior performance in term of network lifetime, energy efficiency, and scalability.

Distributed Gateway Selection for M2M Communication in Cognitive 5G Networks

M2M communication is an important component for future wireless networks. M2M systems consist of a large number of devices that can operate with minimum or no human intervention. However, spectrum demand rises exponentially with the increase in the number of connected devices. Cognitive 5G networks are key to address the issue of spectrum scarcity. Further, use of multiple gateways in cognitive 5G networks for M2M communication can increase system throughput, coverage, and energy efficiency. Nevertheless, using multiple gateways for the secondary M2M devices may cause interference to the primary M2M devices. Existing gateway selection protocols for cognitive M2M communication mostly use single channel CSMA, and thus are not efficient in terms of reducing the interference. Thus, in this article, we propose a DGAP based on multi-channel CSMA for M2M communication in 5G networks. Further, we propose a Lo-DGAP, where each gateway transmits only the worst primary M2M device information rather than transmitting all neighboring primary M2M device information. The proposed Lo-DGAP increases the throughput of the system by reducing the message header payload and is also energy- efficient. Simulation results demonstrate the effectiveness of the proposed schemes in terms of network lifetime and energy consumption.

A rule based delay constrained energy efficient routing technique for wireless sensor networks

In wireless sensor networks (WSN), the nodes are used to collect and gather the data from different environments. Hence, the network consumes more energy which is the main and challenging issue in WSNs. Since the sensor is operating under battery, recharging is impossible and hence the lifetime of each sensor is an important issue. Therefore, it is necessary to introduce new and efficient techniques to extend the network lifetime. In this paper, a new delay constrained energy efficient routing technique is proposed for performing effective routing in WSNs. This approach introduces a delay constraint based reliable routing approach which reduces the energy consumption by constructing efficient clusters without increasing the end-to-end delay. Moreover, the proposed technique called the rule based clustering for routing model provides better performance in terms of network lifetime than the other existing techniques since they consume more energy during the formation of clusters and finding the shortest path. Moreover, additional overhead on the cluster head selection is tackled also using rules in this proposed model in an efficient manner by building balanced clusters. The main advantage of the proposed approach is that it extends the lifetime of the network and increases the throughput, energy efficiency, link quality and scalability. The experimental verification of this technique has been carried out using MATLAB simulations and proved that this model increases the packet delivery rate, network performance and reduces the delay and energy consumption.

An Energy Efficient and Trust Aware Framework for Secure Routing in LEACH for Wireless Sensor Networks

Wireless Sensor Network (WSN) is an advanced technology and has been used widely in many applications such as health monitoring, environment monitoring, military purpose etc. Nature of this network is that they are often placed in an open environment and are susceptible to various attacks. Traditional cryptography methods are not supportable in WSNs as they have high energy and resource constraints. Trust management has been proved to be an effective measure to enhance security as well as to handle threats for WSNs. Trust can be defined as level of reliableness in a node. Low Energy Adaptive Clustering (LEACH) is a cluster based routing protocol for WSN which is superior to direct communication protocol and known for its minimum transmission energy. However, LEACH itself has some limitations related to security. In this paper, an energy efficient and trust aware framework for secure routing in LEACH (EETA-LEACH), has been proposed that improves LEACH protocol by introducing trust to provide secure routing, while maintaining originality of LEACH protocol. This approach is a combination of trust-based routing module and trust management module that works together to select trusted Cluster Head (CH). The simulation results demonstrate that proposed scheme is better in terms of network lifetime and Packet Delivery Ratio (PDR). It is verified that malicious nodes will not be selected as CH and trust value of a malicious node decreases with time.

An efficient trajectory based routing scheme for delay-sensitive data in wireless sensor network

Exploiting sink mobility for balancing the energy dissipation of sensor nodes and preventing energy holes is a growing trend in the field of wireless sensor network (WSN). The mobile sink moves throughout the network and collects data in a single-hop fashion resulting in less energy consumption of the sensor nodes. Despite the advantage of this scheme, data forwarding to the mobile sink during an emergency situation is a major issue that should be dealt with. For efficient data delivery within the stipulated deadline, the sensor node which has sensed a delay-intolerant data needs to forward the data towards the mobile sink. In this paper, a Moore curve based trajectory of the mobile sink has been considered for efficient sink based data collection. This work is also motivated by anycast forwarding of delay sensitive data to the mobile sink before the sensed data lose its relevance, where the node follows a strict sleep-wake pattern. We have evaluated the effectiveness of the proposed trajectory based data collection scheme by simulation using MATLAB. The delay-intolerant data routing scheme (DRS) shows that the data reaches the mobile sink within the given deadline while restricting the energy dissipation of the sensor nodes to a minimum. This have been verified by extensive simulations which show that when compared to static sink, the usage of a mobile sink improves the network lifetime by almost 12%. This work has also been compared with an existing work (PMDD) to show its validity. The simulation results depict that DRS shows an improvement of about 25%–29% in terms of network lifetime.