Wireless Sensor Networks

The Hierarchical Power Aware Routing (HPAR) is a power aware routing protocol that divides the network into a group of sensors called zones [12]. In this, the cluster zones are formatted, then the decision is made that how message is routed so the battery life can be maximized. This protocol provides an approximation algorithm called max-min ZPmin algorithm. In this algorithm by applying Dijkshtra algorithm the path who consumes less power is found. Then the second path is found that maximizes the minimal residual power. The advantage is that it provides both transmission power and maximizes battery

Abstract—Wireless Sensor Network (WSN) is basically a wireless network in which sensor nodes are distributed in any environment condition, to collect the data or information such as temperature, pressure, wind, sea level etc. and accordingly data or information will be passed to the main location. Reliable Trust and Reputation of a node stands for the measure of trust over a certain period of time which can be useful to evaluate the risk of attack from that particular node. We have combined all these parameters in order to risk of attack from a particular node.

Sensor network got tremendous focus due to its less cost and small size and which can be placed anywhere. A sensor network consists of number of sensor nodes dispersed in a specific geographical area. These sensor nodes communicate using wireless transceivers. These networks are widely used

W..Heinzelman, A. Chandrakasan and H. Balakrishnan, "Energy-Efficient Communication Protocol for Wireless Microsensor Networks", In Proc. 33rd HICS, 4-7 Jan, 2000, Vol 2, pp. 10.

With the furtherance of computer networks extending boundaries and joining distant locations, wireless sensor networks (WSN) emerged as the new frontier in developing opportunities in order to collect and process data from remote locations. A wireless sensor network is a collection of nodes organized in a cooperative manner. Multiple sensor nodes arranged in proximity to sense an event and subsequently transmit sensed and collected information to a remote processing unit or base station. The nodes are able to communicate wirelessly and often self-organize after being deployed in an ad hoc fashion. More than 1000s or even 10,000 nodes are expected. Currently, wireless sensor

Due to limited and non-rechargeable energy provision, the energy resource of sensor networks should be managed wisely to extend the lifetime of sensors. Sensor networks have recently emerged as a platform for several important surveillance and control applications .Each sensor has an onboard radio that can be used to send the collected data to interested parties. One of the advantages of wireless sensors networks (WSNs) is their ability to operate unattended in harsh environments in which contemporary human-in-the-loop monitoring schemes are risky, inefficient and sometimes infeasible. Therefore, sensors are expected to be deployed randomly in the area of interest by a relatively uncontrolled means, e.g. dropped by a helicopter, and to collectively form a network in an ad-hoc manner. In order to achieve high energy efficiency and increase the network scalability, sensor nodes can be organized into clusters. Data collected from sensors are sent to the cluster head first, and then forwarded to the base station. Network lifetime can be defined as the time elapsed until the first node (or the last node) in the network depletes its energy (dies).

For that reason, it is vital to consider network coverage and energy consumption in the design of WSN layouts.

In this paper, I will mainly focus on analyzing and evaluating the current Wireless Sensor Networks (WSN). This paper starts with an overview on fundamentals of wireless sensor networks, thus providing the necessary background required for understanding their

heterogeneous scheme in which all sensor nodes have a different amount of energy as each node is assigned with various task [20] such as SEP[21], DEEC[22]. In this paper, we propose and analyze a novel cluster head selection scheme based on the deployment of nodes in different regions for heterogeneous wireless sensor networks (HWSNs) which is named as RBETSSEP.

Abstract: We analyze the wireless sensor networks protocols and present a classification and comparison of routing protocols. Several routing protocols have been projected to maximize the sensor networks life span. Nevertheless, most of these solutions attempt to determine an energy efficient path and don’t account for energy consumption balancing in sensor network. This frequently leads to network partitioning. The aim of this paper is to evaluate, analyze and compare three routing protocols (LEACH, CBR and MBC) that balance energy consumption, through a mathematical model and simulations. This paper will present a performance comparison of protocols LEACH, CBR and MBC based on parameters such as packet loss, average energy consumption, average control overhead, and better adaptivity to a mobile environment by using the NS-2 simulator.

Multiple autonomous, tiny, low-cost and low-power sensor nodes comprise a wireless sensors network (WSN). The sensors nodes are equipped with various types of sensors such as thermal , acoustic, chemical, pressure, weather and optical sensors which gather information from various nodes and collaborate to forward sensed data to base stations for further processing. WSNs designers have to address common issues related to data aggregation, data reliability,

A wireless sensor network (WSN) is a collection of large number of sensor nodes and at least one base station. The sensor node is an autonomous small device that consists of mainly four units that are sensing, information gathering, processing and communication. In wireless sensor network there of many issues that are much affects in communication, processing and in deployments. The main issue is its coverage and connectivity problem. Most of the times communications does not prohibited properly amongst sensors and base station due lacking of ranges problem. Full coverage and connectivity means that every location in the field is covered by at least one node and

Abstract: Wireless sensor networks (WSN) have grabbed much attention in recent years due to their potential use in many applications. One such application is deploying WSN in underground mines to monitor the miner 's physical signals as well as the environment they are exposed to. However, due to the resource constraints of sensor nodes and the adhoc-formation of the network, in addition with an unattended deployment, pose un-conventional demands provoke the need for special techniques for design and management of WSN. Because of the restrictions caused by the lossy dielectric walls and ceilings in the underground mines, the radio signal propagation characteristics are significantly different from those of terrestrial wireless channels. In this paper, underground WSN is designed considering worker’s safety in under-ground, increased energy efficiency and productivity as main goals.

Wireless sensor networks (WSNs) are presented their abilities in many vital applications such as wildlife tracking, checking heart rates of human, military applications, traffic monitoring, etc, [1]. Wireless sensors have limited resources, including limited storage, limited processing facility, and communication capability. In addition, each sensor node is powered by a battery, which has a finite size and cannot be recharged or replaced due to environmental conditions [2-5]. Actually, Sensor nodes depend on their finite resources to survive. Due to these reasons, it is important to enhance the energy efficiency of nodes to improve the quality of the application service REF. The first problem of WSNs is to minimize energy consumption in

Current the new arrival of generation of wires sensor network has been provided for several applications because of modern period which brought the integration of the smallest physical sensors, embedded of small controllers called microcontrollers and radio interfaces on one and only single chip fabrication. All of these functions brought a wide range of application for sensor networks. The integration into wearable wires body area network has been incorporated with a big number of physiological sensors. In addition the idea of micro-sensing and wires and wires linked to the network nodes promises several new application areas like, health ,home, environment ,sport house and others. We briefly illustrate these applications and for more details, the reader should refer to [29].