Wireless Sensor Networks ( Wsns )

In the location-based routing, sensor nodes are distributed randomly in an interesting area. They are positioned mostly by utilizing of Global position system. The distance among the sensor nodes is evaluated by the signal strength obtained from those nodes and coordinates are computed by interchanging information among neighbouring nodes. Location-based routing networks are;

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.

Because the first deployment model can cause network slowdowns and affect the normal workflow, it doesn’t make a viable solution. The other deployments models, build in WIPS functionality in the access points and WIPS with dedicated sensors are more common, if not the most widely used and that why it will be my main focus for the analysis.

In this section, we present the details of proposed protocol. Our protocol implements the idea of probabilities for cluster heads selection based on initial energy and residual energy of sensor nodes as well as the average energy of the sensor network.

The high level requirements for the network are to: measure and record sensor data and process data to actuate the environment. Given these requirements, this section will discuss how these requirements were met as well as provide some system metrics.

A group of wireless sensor nodes (devices) dynamically constructs a temporary network without the exercise of any pre-existing network infrastructure or centralized administration. The main goal of ad-hoc networking is multihop broadcasting in which packets are transferred from source node to destination node through the intermediate nodes (hops). The main function of multi hop WSN is to enable communication between two terminal devices through a bit of middle nodes, which are transferring information from one level to another level. On the foundation of network connectivity, it dynamically gets to determine that which nodes should get included in routing, each node involved in routing transmit the data to further

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.

A complete topology layout for a network covers an end-to-end networking solution. The design of the network has to

Phase 1—forwarding packets towards the target region: when a node receives a packet, it checks that any neighbor node is closer to the target region than itself. If there is more than one, the nearest neighbor to the target region is selected as

This paper covers the online sensor selection in which the sensor network and relations between sensors dynamically change by time and a model which is working for selection of sensors at time may not work for the sensor selection at time , . The selection model of this paper is similar to model discussed in section 3 (i.e. Online distributed sensor selection) but it is based on a well defined special centralized algorithm (central server calculates the utility function and decides which sensors should be selected).

The main problem in wireless sensor network is energy consumption. Because of energy consumption lifetime of wireless sensor network is decreased. In wireless sensor network, all sensor nodes generate data and send data to a single node called as sink (base station), via multi-hop transmissions. When all the sensor nodes collect data and forward that data to a single base station through multi-hop routing, the traffic pattern is highly non-uniform, this procedure puts a high burden on the sensor nodes which are close to the base station. Some strategies are used that balance the energy consumption of the nodes and helps to ensure maximum network lifetime by balancing the load are proposed and analysed.

Abstract— Wireless sensor networks (WSNs) is the collection of physical measurements in a geographical area. It tracks the spatial-average of the sensor measurements in a region. Since it is highly vulnerable to sensor faults and measurement noise the average operation is not robust. In this paper the proposed computational efficient method is used to compute a weight average of sensor measurement. It takes consideration of sensor faults and sensor noise. WSN uses random projections of sensor to compress data and send the compressed data to the data fusion center. The computation efficient method uses the data fusion center for direct work with the compressed data stream. The fusion center performed decompression at the time of computed weighted average. Thus, it reduces the computational requirements. Hence the proposed method gives better accuracy and more efficient for the WSN.

A Wireless Sensor Network is one kind of wireless network includes a large number of circulating, self-directed, minute, low powered devices named sensor nodes called motes. These networks certainly cover a huge number of spatially distributed, little, battery-operated, embedded devices that are networked to caringly collect, process, and transfer data to the operators, and it has controlled the capabilities of computing & processing. Nodes are the tiny computers, which work jointly to form the networks. The sensor node is a multi-functional, energy efficient wireless device. The applications of motes in industrial are widespread. A collection of sensor nodes collects the data from the surroundings to achieve specific

There are a lot scenarios need different sensor nodes to collaborate and integrated on the air into networks to facilitate applications. The scaled-down censoring system presented below is an example of those wireless sensor networks (WSN). In this system sensors are different between corridors area and manufacturing area, since they need different precise level. Those sensors combined together by different wireless AP and provide services to different applications inside and outside the plant. This is where virtualization shines. Virtualization creates an uniformed environment in heterogeneous sensor networks. It bridge the gap between infrastructure and applications. And the network and sensor virtualization can achieved by the middleware. Middleware hide unnecessary details and complexity of the underlying heterogeneous infrastructures, like different sensor nodes and different wireless AP in the presented scenario.

A sensor network consists of a large number of sensor nodes, which are arranged either inside the phenomenon to be monitored or very close to it. Sensor networks denote an important improvement over traditional sensor networks, which are deployed in two means as shown below [26]: