Intelligent Agent based Resource Scheduling in Wireless Sensor Networks

Wireless Sensor Network consists of sensor nodes which are small and deployed in different geographical areas for different applications. Sensor nodes are mainly constrained with resources in terms of battery, communication range and bandwidth etc. In order to prolong the wireless sensor network life span, effective utilization of resources is very critical. Hence effective resource management is a challenging task in wireless sensor network which involves resource identification, scheduling, allocation and sharing. In this paper, an intelligent agent based resource scheduling mechanism using type-2 fuzzy logic to resolve the scheduling issues involving the bandwidth and energy of wireless sensor network is proposed. Proposed agent based resource scheduling mechanism consists of node agency and sink agency. Node and sink agency consists of a mobile agent and static agent. Sink agency periodically collects the node information such as available energy, bandwidth and neighbor list collected by node agency. Based on these parameters, sink agency schedules the available resource using type-2 fuzzy logic system inference. Proposed algorithm helps to schedule the available resources effectively by handling uncertainty in resources of wireless sensor network. Our simulation results demonstrate that the proposed scheme enhances the performance in terms of resource information acquisition delay, resource scheduling computational delay, and scheduled sensor rate etc.

[1]  Jean-Marie Bonnin,et al.  Wireless sensor networks: a survey on recent developments and potential synergies , 2013, The Journal of Supercomputing.

[2]  Padmalaya Nayak,et al.  A Fuzzy Logic-Based Clustering Algorithm for WSN to Extend the Network Lifetime , 2016, IEEE Sensors Journal.

[3]  Ridha Bouallegue,et al.  Interval type 2 fuzzy localization for wireless sensor networks , 2016, EURASIP J. Adv. Signal Process..

[4]  Archana Raut,et al.  A Survey on Scheduling Schemes with Security in Wireless Sensor Networks , 2016 .

[5]  Ian F. Akyildiz,et al.  Wireless sensor networks: a survey , 2002, Comput. Networks.

[6]  Gurudatt Kulkarni,et al.  Energy Management in Wireless Sensor Network , 2013, 2013 UKSim 15th International Conference on Computer Modelling and Simulation.

[7]  Tajana Simunic,et al.  Resource Management in Heterogeneous Wireless Sensor Networks , 2011, J. Low Power Electron..

[8]  Weizhe Zhang,et al.  A Trusted Real-Time Scheduling Model for Wireless Sensor Networks , 2016, J. Sensors.

[9]  Jeremy V. Pitt,et al.  Cognitive Agent Based Critical Information Gathering and Dissemination in Vehicular Ad hoc Networks , 2013, Wirel. Pers. Commun..

[10]  Yang Xiao,et al.  Energy-efficient node scheduling algorithms for wireless sensor networks using Markov Random Field model , 2016, Inf. Sci..

[11]  P. O. S. Inha,et al.  Overview of Wireless Sensor Network: A Survey , 2014 .

[12]  Sukrati Dixit,et al.  A Review on Routing and Scheduling Algorithm in Wireless Sensor Network , 2016 .

[13]  Sunilkumar S. Manvi,et al.  Regression based critical information aggregation and dissemination in VANETs: A cognitive agent approach , 2014, Veh. Commun..

[14]  Li-Xin Wang,et al.  A New Look at Type-2 Fuzzy Sets and Type-2 Fuzzy Logic Systems , 2017, IEEE Transactions on Fuzzy Systems.

[15]  Calle Torres,et al.  ENERGY CONSUMPTION IN WIRELESS SENSOR NETWORKS USING GSP , 2006 .

[16]  Jerry M. Mendel,et al.  Critique of “A New Look at Type-2 Fuzzy Sets and Type-2 Fuzzy Logic Systems” , 2017, IEEE Transactions on Fuzzy Systems.

[17]  Sandeep Sharma,et al.  A Review of Various Scheduling Techniques Considering Energy Efficiency in WSN , 2017 .

[18]  Yourong Chen,et al.  A sensor node scheduling algorithm for heterogeneous wireless sensor networks , 2019, Int. J. Distributed Sens. Networks.

[19]  S. S. Manvi,et al.  Multiagent driven dynamic clustering of vehicles in VANETs , 2012, J. Netw. Comput. Appl..

[20]  Giancarlo Fortino,et al.  Agent-based Development of Wireless Sensor Network Applications , 2011, WOA.

[21]  Padmalaya Nayak,et al.  Energy Efficient Clustering Algorithm for Multi-Hop Wireless Sensor Network Using Type-2 Fuzzy Logic , 2017, IEEE Sensors Journal.

[22]  Jeremy V. Pitt,et al.  Multiagent based information dissemination in vehicular ad hoc networks , 2009, Mob. Inf. Syst..