Micro Electro Mechanical Systems And Microelectronics And Exponentially Wide Applications Of Wireless Sensor Networks

maximization of network lifetime [8]. This protocol is also divided into two phase: 1. Clustering and 2. Routing of aggregated data. In clustering phase, a fixed topological arrangement is done by sensor nodes. In the data aggregation phase, heuristic is proposed. The advantage is that it provides energy efficiency and network lifetime also be increased.

A WSN is a type of wireless networks that consists of collection sensor nodes which are tiny devices. Each sensor node of the network has different processing capability. It may contain multiple types of memory (program, data and flash memories), have a RF transceiver, have a power source (e.g., batteries and solar cells), and accommodate various sensors and actuators. The nodes communicate wirelessly and often self-organize after being deployed in an ad hoc fashion [13, 14]. Optimum need of each sensor node is to maximize its own utility function. Also the whole network requires resource assignments balance to perform in a useful and efficient way. This chapter presents a brief survey on WSNs showing its types, characterizing features, protocols and applications.

Abstract - Wireless Sensor Networks (WSN) comprises of several tiny, low-cost, resource constrained sensor nodes. These nodes are placed in harsh environments and generally are used for air pollution monitoring, water quality monitoring, industrial monitoring, health monitoring and more. Routing is difficult in such surroundings primarily due to the unique constraints the wireless sensor networks suffer from. Wireless sensor network is highly dynamic, making existing routing protocols ineffective. This paper concentrates on energy efficiency of the protocols. Both the protocol presented are hierarchical and cluster based. Both have sensor nodes and a base station (BS). The BS selects the Cluster Heads (CH) among themselves. CH is the elected sensor node which passes on the sensor data collected by sensor nodes of its cluster to either BS or other CH. All candidate nodes for becoming CH are listed, based on the various factors like relative distance of the candidate node from the Base Station, outstanding energy level, possible number of neighboring sensor nodes the

Autonomous sensors nodes to monitor physical or environmental conditions, such as temperature, sound, vibration, pressure, motion or pollutants and to cooperatively pass their data through the network to a receiver (destination) [1] [7].

With the recent technological advancements in smaller sensor devices with ubiquitous sensing and monitoring capabilities, Wireless Sensor Networks (WSN) are evolving as one of the most significant technologies of 21st century (Ruiz-Garcia, Lunadei, Barreiro, & Robla, 2009). Though wired networks provide more stable and reliable communication, wireless networking does provide more advantages with connectivity without being tethered. WSN with dense wireless networks of small, low cost sensors for collecting and disseminating environment data has facilitated connecting, monitoring and controlling of physical environments and environmental conditions such as temperature, humidity, pressure from remote locations with better accuracy which are not possible with wired networks (Potnis & Rajeshwari, 2015). Moreover, with the unique characteristics of flexibility, energy efficiency, distributed intelligence, low cost and most importantly with very good sensing and monitoring capabilities, WSNs are serving wide range of applications in various fields including remote environmental monitoring, home security, industry applications, military purposes such as target tracking by preparing and providing a ubiquitous computing environment (Ruiz-Garcia et al., 2009).

The basic suggestion of anytime and anywhere computing leads to the new field called mobile computing. The major stimuli for the growth of mobile computing are due to advancement in wireless technology. The improvement in wireless transmission techniques lead to the development of the WSN. A wireless Sensor network includes various application areas like environment monitoring, military applications and context aware computing environments etc.

The wireless sensor networks have deployed in different data intensive applications including video or audio surveillance, agriculture precision, monitoring of habita. A wireless sensor network with a medium sized can get 1Gigabytes per year from habitat biologically. As the storage capacity is limited for sensor nodes, the data that is excess should get transmitted to base station for analysis and archiving. The sensor nodes should operate in power supplies with limitations like solar panels or small batteries. So that the main problem that is faced by the data-intensive wireless sensor networks is reducing consumption of energy of nodes such that the generated data will be transferred to base

Sensor nodes can be used for continuous sensing, event detection, event ID, location sensing, and local control of sensors. We classify the applications in military, environment, health, home and many commercial areas. It is possible to expand this classification with more categories such as space exploration, chemical process industries and disaster relief. Most of the sensor network routing techniques and sensing tasks require the knowledge of location with high accuracy without losing information. Thus, it is important that a sensor node has a location finding system. A mobilizer may sometimes be

Abstract—In wireless sensor network (WSN), many novel architectures, protocols, algorithms and applications have been proposed and implemented for energy efficiency. The efficiency of these networks is highly dependent on routing protocols which directly affecting the network life-time. Cluster formation in sensor network is one of the most popular technique for reducing the energy consumption and expand the lifetime of the sensor network. There are various cluster formation techniques used in wireless sensor network. In which, Particle Swarm Optimization (PSO) is simple and efficient optimization algorithm, which is used to form the energy efficient clusters with optimal selection of cluster head. The comparison is made with the well-known cluster based protocols developed for WSN, LEACH (Low Energy Adaptive Clustering Hierarchy) and LEACH-C as well as the traditional K-means clustering algorithm. A comparative analysis shown in the paper and come to the conclusion based on some parameters.

The grouping of various sensor nodes makeup a huge Wireless Sensor Network (WSN). These wireless sensor networks are employed in environments where human reach is difficult. The sensor nodes are small, inexpensive, battery powered devices which are capable of local processing and wireless communication. These sensors cooperatively work with each other to sense some physical circumstances and then the information is gathered and processed to get pertinent results. The information that is gathered is sent to the main location.

At present, Wireless Sensor Network has becoming a hot technological topic with the development of computer science and wireless communication technology, wireless sensor network (WSNs) is a system shaped by a substantial number of sensor nodes, each one furnished with sensors to recognize physical phenomena, for example, heat, light, movement, or sound. Utilizing diverse sensors, WSNs can be implemented to backing numerous applications including security, diversion, mechanization, mechanical checking, and open utilities also state management. however, numerous WSN gadgets have serious asset demands as far as vitality, computation, and memory, brought about by a need to cutoff the expense of the substantial number of gadgets needed for some applications and by organization

In sensor network node deployment falls into two classifications either a dense deployment or a meager deployment. In dense deployment in the focused on field, high quantities of sensor nodes are available. While in an inadequate deployment we have lesser nodes. Dense deployment is utilized to distinguish multiple sensors. At the point when expense of item expands it can be utilized there.

ABSTRACT: Wireless sensor networks is a self-configured network means any node can join it or leave it at any time. it is a self-healing and self-organizing. Self-healing networks allow nodes to reconfigure their link associations and find other pathways around powered-down nodes or failed nodes. Self-organizing allows a network automatically join new node without the need for manual interference. In this paper, we are using actor nodes to solve energy hole problem so that we can reduce energy consumption and can enhance throughput of network.

A sensor network has large number of sensor nodes, which are appropriately deployed or place either inside the experiment or very near to it. A sensor network is a network consisting of distributed wireless automatic devices using sensors to coordinately monitor physical or surrounding conditions, such as temperature, sound, stress/ pressure, movements or pollutants etc at different locations and time. The development of wireless sensor networks was originally motivated by military applications such as battlefield surveillance. The wireless sensor networks nowadays can be used in many more application areas, including environment and domain monitoring, medical applications, intelligent home systems, and traffic commanding.

A wireless sensor network (WSN) comprises of a large number of independently distributed sensor nodes in which sensors employed at each and every node. These sensors are used to monitor physical or environmental conditions, and can easily pass their data through the sensor network to the main site. Each sensor node consists of a sensing system for information acquisition, real-time data processing, a power supply unit, and wireless communicating modules, which is a basic system of a WSN. Each time the physical conditions vary according to the time and space, WSNs starts real-time data processing and sends the data.