A survey on clustering algorithms for wireless sensor networks ameer ahmed abbasi a, mohamed younis b a department of computing, alhussan institute of management and computer science, dammam 31411, saudi arabia b department of computer science and electrical engineering, university of maryland, baltimore county, baltimore, md 21250, usa. With the rapid development in ubiquitous smart sensors, wireless sensor networks have started to evolve into numerous applications including. In general the hardware components in a wireless sensor network include analogtodigital converters, sensor circuits, microprocessors, and wireless transceivers. Algorithms, strategies, and applications mohammad abu alsheikh1,2, shaowei lin2, dusit niyato1 and hweepink tan2 1school of computer engineering, nanyang technological university, singapore 639798 2sense and senseabilities programme, institute for infocomm research, singapore 8632.
Evolutionary intelligence is the place to discover advances in the field of evolutionary intelligence. Kulkarni, anna forster, and ganesh kumar venayagamoorthy, computational intelligence in wireless sensor networks. Application of computational intelligence techniques in. Networks and all the sensor nodes have contact with the base station. This dynamic behavior is either caused by external factors or initiated by the system designers themselves.
Low power devices consists of one or more sensors, a processor, memory, a power supply, a radio and an actuator. Swarm intelligence based routing protocol for wireless sensor. These networks are relatively affordable and allow measurements to be taken remotely, in realtime and with minimal human intervention. The main players in a wsn environment are motes, base stations, actuators and gateways. Member, ieee and ganesh kumar venayagamoorthy, senior member, ieee. However, clusterbased wsns are vulnerable to selective forwarding attacks. Some of the wsn applications consists of a large number of sensor. Wireless sensor networks wsns are networks of distributed autonomous devices that can sense or monitor physical or environmental conditions cooperatively. 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. The job of wsn is to monitor a field of interest and gather certain information and transmit them to the base station for post data analysis. It is an information technology which integrates latest technological achievements in the network, microelectronics and communications.
Ni 19 mar 2015 1 machine learning in wireless sensor networks. Wireless sensor network, computational intelligence. Wireless sensor networks wsns have become a key technology for the iot and despite obvious benefits, challenges still exist regarding security. However, satisfying quality of service qos requirements of the diverse application domains remains a challenging issue due to heterogeneous traffic flows. Sensor nodes are usually deployed in large number that work independently in unattended harsh environments. A survey on localization in wireless sensor networks. Coverage and kcoverage optimization in wireless sensor. The journal is devoted to the timely publication and dissemination of both the theoretical and practical aspects of populationbased searches for artificial intelligence. Computational intelligence and sensor networks for biomedical systems 2. The number of sensor nodes in a sensor network can be several orders of magnitude higher than the nodes in an ad hoc network. Paradigms of computational intelligence ci have been successfully used in recent. Many improvements are done in wireless sensor network. The computational intelligence in sensor networks studies in computational intelligence, 1 st edition is an informative book that reveals about applications of computational intelligence in sensor networks.
Energy conservation in wireless sensor networks using data reduction approaches. To adapt to such conditions, sensor networks often adopt machine learning techniques to eliminate the need for unnecessary redesign. Key management schemes in wireless sensor networks. Computational intelligence algorithms for optimisation of wireless sensor networks a thesis submitted in partial fulfilment of the requirements for the degree of doctor of philosophy by muyiwa olakanmi oladimeji student id 3023261 supervised by dr sandra dudley school of engineering, london south bank university march, 2017. Computational intelligence for wireless sensor networks. Wsns face various problem, communication failures, storage and computational constraints and limited power supply. Mar 16, 2019 with the rapid development in ubiquitous smart sensors, wireless sensor networks have started to evolve into numerous applications including healthcare, medical, agriculture, transportation, industry, internet of things, and smart cities. Sathish department of computer science periyar university, salem. Wsns are used in numerous applications such as environmental monitoring, habitat monitoring, prediction and detection of natural calamities, medical monitoring and structural health monitoring. A survey, ieee communications surveys and tutorials, vol. Applications and clustering algorithms article pdf available in international journal of computer applications 7315 july 20 with.
Abstractwireless sensor networks wsns are networks of distributed. May 30, 2012 wireless sensor network my seminar ppt 1. A wireless sensor network consists of autonomously and spatially distributed sensors to monitor physically environmental conditions. With the rapid development in ubiquitous smart sensors, wireless sensor networks have started to evolve into numerous applications including healthcare, medical, agriculture, transportation, industry, internet of things, and smart cities. Pdf wsn has been directed from military applications to various civil applications. For different application areas, there are different technical issues that researchers are currently resolving. Energy efficient clustering algorithms in wireless sensor networks.
The node in the chromosome, which dissipates maximum energy is selected as critical node. Introduction the evolution and advance in micro electromechanical systems mems has led to the development of reliable, low cost, small size micro sensors 1. Editorial computational intelligence in wireless sensor and. Pallavi r, 2, shreya animesh, 3, preetesh shivam, 4, raghunandana alse. Energy efficient hierarchical clustering approaches in. Wireless sensor and actuator networks wsans are heterogeneous networks composed of many different nodes that can cooperatively sense the environment, determine an appropriate action to take, then change the environments state after acting on it. Wireless sensor networks emergence and growth a survey. Computational intelligence in wireless sensor networks. Wsns face many challenges, mainly caused by communication failures, storage and computational constraints and. This paper describes leach protocol, their advantages, disadvantages etc. Due to constraint resources, typically the scarce battery power, these.
Wireless sensor network wsn is a set of tiny nodes that are equipped with embedded computing devices interfacing with sensorsactuators. Analysis of routing protocols in ad hoc and sensor wireless. The main challenge facing the operation of wsn is saving energy to prolong the network lifetime. Multihop wireless sensor network is a mature research field that covers many topics and different classes of networks. Wsn has been directed from military applications to various civil applications. The growing demand of usage of wireless sensors applications in different aspects makes the qualityofservice qos to be one of paramount issues in wireless sensors applications. It addresses the study of the collective behaviors of systems made by many components that coordinate using decentralized controls and selforganization.
Wireless sensor networks routing protocols swarm intelligence ant colony routing beeinspired routing abstract swarm intelligence is a relatively novel. Shahzad, analysis of routing protocols in adhoc and sensor wireless networks based on swarm intelligence, int. Wsns face many challenges, mainly caused by communication failures, storage and computational constraints and limited power supply. Computational intelligence algorithms for optimisation of. Energy aware routing and clustering economic usage of energy is important in wsns because replacing or recharging the batteries on the nodes may be impractical, expensive or dangerous. Different computational intelligence ci techniques are used to alter wsn dynamic nature. A wireless sensor network has been designed to perform the highlevel of information processing tasks like detection, classification and tracking. Wireless sensors nodes in the network sense extract data from the various surrounding environment, sequence the sensed data locally, and then transfer the data to a base station for further processing through wireless communication. The current state of the art of sensor networks is captured in this article, where solutions are dis. The book serves as a guide for surveying several stateoftheart wsn. Energy conservation in a wsn maximizes network life time and is addressed through efficient reliable wireless communication, intelligent sensor placement to. Abstractwireless sensor networks monitor dynamic environments that change rapidly over time.
Wireless sensor network, computational intelligence, clustering algorithms 1. Classical and swarm intelligence based routing protocols. Keywords clustering, computational intelligence, wireless sensor networks. A survey on qos mechanisms in wsn for computational. Computational intelligence in sensor networks by bijan. A survey on sensor networks eecs instructional support. Computational intelligence in wireless sensor and ad hoc. Sensors free fulltext a data clustering algorithm for. Download computational intelligence in sensor networks by bijan bihari mishra pdf ebook free. Energy conservation in wireless sensor networks using data.
Inexpensive millimeterwave communication channel using glow discharge detector and satellite dish antenna. Computational intelligence ci paradigms are suitable to adapt for wsn. Sensor networks are computer networks of many, spatially distributed devices using sensor s to monitor conditions at different locations, such as temperature, sound, vibration, pressure, motion, or pollutants. Computational intelligence in wireless sensor and ad hoc networks. Heterogeneous wsns consists of different sensor devices with different capabilities. A wireless sensor network is a network of distributed autonomous devices that can sense or monitor physical or environmental conditions cooperatively. A survey on clustering algorithms for wireless sensor networks. Pdf quality of service in wireless sensor networks.
The book serves as a guide for surveying several stateoftheart wsn scenarios in which ci approaches have. The number of sensor nodes in a sensor network can be several orders of magnitude higher than the nodes in an ad hoc. Wireless sensor networks wireless sensor networks wsns9 is a paradigm of networks that contains sensing, computation, and wireless communications capabilities with small nodes. Index termsclustering, computational intelligence, data aggregation.
Computational intelligence routing for lifetime maximization. In wireless sensor networks, sensor nodes are typically powerconstrained with limited lifetime, and thus it is necessary to know how long the network sustains its networking operations. However, many applications are not ready for real world. However, many applications are not ready for real world deployment. International journal of computational intelligence and informatics, vol. As more devices are connected to the internet, new cyber attacks are emerging which join wellknown.
Ozturk, cluster based wireless sensor network routing using artificial bee colony algorithm, wireless netw. Despite previous results and a vast literature on the topic, many problems related to modern network infrastructures such as coverage, deployment, routing, broadcasting, mobility, and energy consumption are still challenging, as solving them to optimality is certainly far from. Kulkarni et al computational intelligence in wireless sensor networks. Wireless sensor network wsn is one of the most promising technologies for some realtime applications because of its size, costeffective and easily deployable nature. Big data analytics for sensornetwork collected intelligence. Big data analytics for sensornetwork collected intelligence explores stateoftheart methods for using advanced ict technologies to perform intelligent analysis on sensor collected data. Security issues and challenges in wireless sensor networks. Computational intelligence and wireless sensor networks is organized to address various issues such as computational intelligence, wireless sensor networks, artificial intelligence, neural networks, radio frequency identification, internet of things, autonomous driving, parallel processing, machine learning and gps technologies to develop the. The optimization of the performance of wireless sensor networks in terms of area coverage is a critical issue for the successful operation of every wireless sensor network. Wireless sensor networks wsns are collections of compactsize. This helps wireless sensor networks balance energy effectively and efficiently to prolong their lifetime. Also explore the seminar topics paper on computational intelligence in wireless sensor networks with abstract or synopsis, documentation on advantages and disadvantages, base paper presentation slides for ieee final year computer science engineering or. Wireless sensor networks can be an integral part of military command, control, communications, computing, intelligence, surveillance.
The wireless sensors continuously monitor the physical process and transmit information to the base station. Destination of critical node is changed to a randomly selected node. A survey yawar abbas bangash, qamar ud din abid, alshreef abed ali a, yahya e. Computational intelligence techniques for wireless sensor. Application of computational intelligence techniques in wireless sensor networks the state of the art. Quality of service guarantee in wireless sensor networks wsns is difficult and more challenging due to the fact that the resources available of sensors and the various applications running over these networks have. Security is very essential in wireless sensor network. A wireless sensor network may contain hundreds or even tens of thousands of inexpensive sensor devices that can communicate with their neighbors within a. The differences between sensor networks and ad hoc networks are 4.
In, a lowcost data gathering and decision making approach have been developed using fuzzy set theory for wireless body sensor networks. In general the hardware components in a wireless sensor network include analogtodigital converters, sensor circuits, microprocessors, and wireless. May 11, 2016 computational intelligence for wireless sensor networks. Ijcsns international journal of computer science and network security, vol. The energy of nodes, communication computing and storage capability in wireless sensor networks are limited. Editorial computational intelligence in wireless sensor and ad hoc networks sergiotoral, 1 cipriandobre, 2 bernabedorronsoro, 3 mesutgunes, 4 anddanielg. Alsalhi abstract wireless sensor networks wsns have facilitated human life in different.
The book serves as a guide for surveying several stateoftheart wsn scenarios in which ci approaches have been employed. Citeseerx document details isaac councill, lee giles, pradeep teregowda. An extensive survey of ci applications to various problems in wsns from various research areas and publication venues is presented in the. Bhawnesh kumar, vinit kumar sharma, distance based cluster head selection algorithm for wireless sensor network. Explore computational intelligence in wireless sensor networks with free download of seminar report and ppt in pdf and doc format. The sensor networks can be used for various application areas e. Among the techniques covered are rulebased systems, artificial neural. A survey of security issues in wireless sensor networks. Uniform crossover is used with swapping probability of 0.
A survey on sensor networks university of california. International journal of computational intelligence and. They generally use shortrange wireless transmitters and they act autonomously but cooperatively to route data, hopbyhop towards a central node called sink, or base station. This book emphasizes the increasingly important role that computational intelligence ci methods are playing in solving a myriad of entangled wireless sensor networks wsn related problems. Introduction wireless sensor network is a network of distributed. Machine learning algorithms for wireless sensor networks. Clustering is an efficient technique used for managing energy consumption. Dynamic cluster head selection using fuzzy logic on cloud. A sensor network is an infrastructure composed of sensing measuring, computing, and communication elements that gives a user or administrator the ability to instrument, observe, and react to events and phenomena in a specific environment akkaya and younis, 2005, sohraby et al. This article pursues the maximization of area coverage and area kcoverage by using computational intelligence algorithms, i. Pdf computational intelligence in wireless sensor networks. Reina 1 department of electronic engineering, university of seville,sevilla, spain. Applications and clustering algorithms is a seminar presentation by computer engineering students 2017.
Decision making on the gathered data from the biosensors improves the data quality and transmission overhead. Also explore the seminar topics paper on computational intelligence in wireless sensor networks with abstract or synopsis, documentation on advantages and disadvantages, base paper presentation slides for ieee final year computer science engineering or cse students. In 1st international conference on wireless communication, vehicular technology, information theory and aerospace electronic systems technology, pages 15, 2009. To illustrate this point, the differences between sensor networks and ad hoc networks are. We examine wireless sensor networks, fixed sensor networks, mobile ad hoc networks and cellular net works. The rising field of wireless sensor network wsn has potential benefits for realtime monitoring of a physical phenomenon. In clusterbased wireless sensor networks, cluster heads chs gather and fuse data packets from sensor nodes. Large number of heterogeneous sensor node devices spread over a large field.
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