Research On Energy Harvesting Opportunistic Sensor Networks With Hybrid Topology Using Fuzzy Entropy Analysis

In recent years,the demand for wireless sensor networks has increased for many industrial applications such as fault diagnosis and monitoring,surveillance monitoring,industrial control systems,commodity consumption monitoring and plant automation,etc.In addition,in industrial applications,wireless sensor networks have many medical,military,civil and environmental applications as well body area network monitoring,civil structure monitoring,target tracking in battlefields,earthquake and flood monitoring,forest fire monitoring etc.The technological progression in the field of highly integrated digital sensor electronics,small scale microprocessors,low power transceivers and radio frequency devices,collectively resulted in the design of efficient wireless sensors.The existence of these miniaturized wireless sensor devices is only possible if appropriate energy management techniques and energy replenishment measures are taken in advance,so that these sensor nodes can efficiently collaborate with each other for data sensing,data collection and aggregation purposes.A novel,scalable network architecture is required in which sensor nodes can be re-organized into disjoint clusters to form two-tier topology.This novel network architecture should help in reducing the overall communication overhead and improving the energy efficiency.The high computational power required by sink nodes in wireless sensor networks lead to fast battery draining after a few rounds of communication,sensing,and aggregation.In order to increase the network lifetime of sensor nodes,the sink node‘s energy should be replenished in a timely manner.The highly efficient data transmission could be achieved if the sensor nodes can undergo status transition if they are idle,thus saving battery power for next round of operations.In this context,an asynchronous sleep/awake cycle strategy in which sensor nodes operate according to schedule suited for the scenario,is proposed.Although it might affect the link stability but it also creates an opportunistic node connection to exist between the sensor nodes.The critical network traffic in the neighborhood area networks(NAN)of Smart Grids(SGs)includes both delay-sensitive and delay-tolerant data for real-time and non-real-time usage.The delay-sensitive data is related to monitoring the power load requirements in NAN whereas the delay-tolerant data is related to changing that power load in the NAN.To facilitate these traffic requirements,the proposed asynchronous sleep/awake strategy of sensor nodes can be used to create an opportunistic node connections between the sensor nodes.A novel opportunistic algorithm―Energy-Efficient Multi-Disjoint path Opportunistic Routing(EMOR)‖ is developed as the baseline architecture model to facilitate the opportunistic node connections in clustering environment;then a novel hesitant fuzzy entropy based clustering scheme(HFECS)is designed for opportunistic cluster formation and cluster head election procedure.The dynamic entropy weight coefficient method in HFECS helps in selecting the best possible cluster head after the formation of optimized number of clusters in the network.This is achieved by incorporating two levels of hierarchy in the network and three levels of energy heterogeneity in sensor nodes.After cluster formation,HFECS uses the same techniques for performing data fusion to reduce the redundant information flow from the first-second hierarchical levels.The numerical simulation carried out revealed that EMOR achieves 84%,307% 107% and 18% consume less energy than Ex OR,RPRDC,DCBONC,and POFA algorithms.In addition to it,EMOR achieves 117%,165%,5.81 % and 377% improvement gain in network lifetime against Ex OR,RPRDC,DCBONC,and POFA algorithms.HFECS achieves 13.64%,0%,8.7%and 8.7% improvement in average energy consumed over SEP-E,DEEC-E,EBCS and TEEN respectively at 1500 rounds of communication.Similarly,HFECS achieves34.19%,57.58%,6.67% and 52.38% improvement gain in network lifetime against SEP-E,DEEC-E,EBCS and TEEN respectively for network size of 250x250 m.Likewise,a novel opportunistic algorithm ―Delay-Aware Energy-Efficient Opportunistic Ring Routing(DA-EEORR)‖ is designed to aid the opportunistic node connections in ring routing environment using restricted search space mechanism.The restricted search space mechanism allows searching for next-hop node in terms of minimum distance and better energy-efficiency in a confined search area.Two searching areas (?)Towards Search Space‘ and (?)Away Search Space‘ are defined in our model.The (?)Towards Search Space‘ is used to search next-hop node towards the base station in order to send data aggregation request packet whereas the (?)Away Search Space‘ is used to search next-hop node away from base station in order to send data aggregation reply packet.The high tier nodes in DA-EEORR store the updated sink position while low-tier nodes retrieve the updated position of mobile sink from the high-tier nodes.The empirical formulation and control strategy of DA-EEORR could help in resolving the control packet overhead,anchor node placement and mobile sink advertisement issues.DA-EEORR achieves 10.9%,11.71%,18.33% and 1.8%improvement gain in terms of energy consumption against VGB,ring routing,LBRR and DA-EERR for a sink mobility of 15 km/hr.Additionally,DA-EEORR gains 14.89%,16.01%,19.45% and 4.98% improvement in terms of energy consumption against VGB,ring routing,LBRR and DA-EERR for a node density of 500.DA-EEORR achieves29.17%,40%,11.28% and 3.33% improvement gain in terms of network lifetime against VGB,ring routing,LBRR and DA-EERR for a sink mobility of 15 km/hr.Additionally,DA-EEORR gains 24.12%,36.13%,11.05% and 0.2% improvement in terms of network lifetime against VGB,Ring routing,LBRR and DA-EERR for a node density of 500 respectively.In order to address the problems like energy replenishment and to achieve energy neutral operations in wireless sensor networks,a novel harvested energy scavenging model is developed based on hybrid renewable energy sources i.e.solar and Radio frequency(RF)etc.The harvested energy scavenging model uses the concept of simultaneous wireless information and power transfer(SWIPT)to transfer energy wirelessly from a sensor node to its neighbouring sensor node using radio waves.This harvested energy model is designed in accordance with the requirements of ring opportunistic routing and cluster based opportunistic routing.Besides,the residual energy of a sensor node,the rate of gaining ambient energy should also be considered before estimating the sleep/awake schedule of a sensor node.Hence,a novel Harvested Energy Scavenging and Transfer capabilities in Opportunistic Routing(HESTOR)protocol is proposed which is based on a hybrid(ring + cluster)topology.In HESTOR,the dynamic architecture is initially supported by the formation of a virtual ring structure and then a two-tier routing topology is used in the virtual ring as an overlay by grouping nodes into clusters.The hardware based experiments of harvested energy flow in HESTOR are performed in LABVIEW.It consists of a solar and RF energy harvesters,a power management module(PMM),a super-capacitor,an energy aware interface(EAI),and a sensor node built with a DC9003 mote including an integrated LTC5800Mote-on-Chip microcontroller and a chip antenna.The energy and power profiles for different sensor readings during wakeup process,initialization process,data sensing,negotiating and data transmission process were noted.The experiments reveal that the total power consumed for 7-layer processes(wakeup till transmission process)is50.71 m W in which the maximum power is consumed by high voltage processes.The improvement gain of 57.75 % is achieved in terms of total power after introducing energy aware interfaces(EAI)between power management module and the sensing load.Moreover,EAI also helps in reducing the time factor for 7 layer processes i.e.time reduction of 2.79 sec is achieved with an improvement gain of 13.28%.As far as numerical simulation is concerned,the evaluation of HESTOR is performed in OMNET++ using cross platform library(MEX-API)for simulating WSNs.We have utilized low rate,low cost,short range,flexible and low power consumption standard IEEE 802.15.4for our PHY and MAC layer.In addition to it,we have also utilized the IEEE 802.15.4MAC Layer specifications for data rate and data packet size.The performance improvement of HESTOR against DA-EEORR is 2.38% for energy consumption in data transmissions.Foregoing in view,the optimum results for energy consumption in HESTOR are achieved when the network maintenance frequency is 1/24 i.e.once per 24 rounds of communications.However,it was also observed that 60% of the sensor nodes were alive when data sampling frequency Fs=2 i.e.2x3600=7200 times per hour.In addition to it,if Fs is large and the node density is low,then the energy consumed by a distant apart CH would be quite more than the sum of energy being harvested and received through energy transfer,hence resulting in low live node count.It is pertinent to mention that the individual simulation results are the average over 25 simulation runs and the length of each run is 2500 sec in HESTOR simulation.The results stayed within5–8% of the sample mean when subjected to 95% confidence interval.Furthermore,the sustainable operation of sensor nodes depends on the nodes‘adaptability with the environment.Sectional failure and thermal exposure can cause significant damage to sensor nodes.Different units of a sensor node behave differently when exposed in sunlight for long period of time i.e.,the performance of a typical transceiver is degraded with the increase in temperature.In this regard,a qualitative measurement model is required based on the diurnal temperature variations of the environment in which sensor nodes are deployed.Foregoing in view,a novel,dynamic,self-organizing Hesitant Fuzzy Linguistic Term Analysis using emerging techniques like relative thermal entropy and energy welfare,is proposed to overcome the CH decision making problems and network lifetime bottlenecks.The link and path connectivity in HFLTS is estimated using energy routing cost and asynchronous sleep/awake scheduling.The lower the energy routing cost,the higher will be link and path connectivity between sensor nodes.The state evaluation of a node will be(?)optimistic‘ if its node‘s gain degree is greater than the threshold and the normalized energy welfare is greater than the half of the maximum value of energy welfare.Likewise,the state evaluation of a node will be (?)pessimistic‘ if its node‘s gain degree is less than the threshold and normalized value of energy welfare is less than half of the maximum value of energy welfare.HFLTS Analysis is performed to make the sensor nodes evaluate their current state and make suitable role transition based on energy welfare and node gain degree.The numerical simulation results of HFLTS analysis reveal that FLOC leads to an improvement in network lifetime by 247.11% compared to BMAC,by 68.56% compared to SOPC,and by 77.2% compared to RL-Sleep.Consequently,the research on Energy harvesting opportunistic sensor networks with hybrid topology using Fuzzy Entropy Analysis helps in establishing the basis for multi-sourced harvested energy opportunistic sensor networks.The measurement method of SWIPT in HESTOR model provides an important theoretical and practical basis for its application in EHWSNs.The HFE and HFLTS analysis help in reducing the hesitancy and uncertainty in the opportunistic sensor networks by incorporating multi-attribute decision modelling.