Nt1310 Unit 5 Paper

3.6.3 Location-Based Routing: 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;

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.

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

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.

B. Geographic and Energy Aware Routing (GEAR) Yu et al. proposed a protocol named Geographic and Energy Aware Routing (GEAR)[10], that utilize energy aware neighbor selection for routing a packet towards the targeted region. In order to disseminate the packet inside the destination region, this protocol uses recursive geographic forwarding or the restricted flooding algorithm.

[6] Tarique Haider1 and Mariam Yusuf “A Fuzzy Approach to Energy Optimized Routing for Wireless Sensor Networks”

Abstract—Hierarchical routing is a promising approach for point-to point routing with very small routing state. While there are many theoretical analyses and high-level simulations demonstrating its benefits, there has been little work to evaluate it in a realistic wireless sensor network setting. Based on numerous proposed hierarchical routing infrastructures, we

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.

A Wireless Sensor Network usually is formed by numerous wireless sensor devices. Routing is an important mechanism which will help the data to get forwarded to the right destination. Internet Protocol is an important protocol which helps in routing process. Generally the nodes in a Wireless Sensor Network are integrated and routing using IP version 4 is difficult as the address space is limited. IP version 4 uses 32 bit addressing mechanism which is not sufficient to complete the routing process. The other option is the use of Internet Protocol version 6.

Introduction 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,

1. Introduction Due to the advancement in micro-electro-mechanical systems and microelectronics and correspondingly wide applications of wireless sensor networks, there has been given tremendous attentions by researchers in recent years. In result there is development of low-cost, low-power, multifunctional sensor nodes that are small in size and communicate untethered in short distances. These tiny sensor nodes, which consist of sensing, data processing, and communicating components, leverage the idea of sensor networks based on collaborative effort of a large number of nodes. Sensor nodes in such a network are often powered with onboard batteries with limited energy. It is impractical or infeasible to replenish energy via replacing batteries on these sensors in most applications. As a result, it is well perceived that a sensor network should be deployed with high density in order to prolong the network lifetime. A sensor network is composed of a large number of sensor nodes, which are densely deployed either inside the phenomenon or very close to it. The position of sensor nodes need not be engineered or pre-determined. This allows random deployment in inaccessible terrains or disaster relief operations. On the other hand, this also means that sensor network protocols and algorithms must possess self-organizing capabilities. Another unique feature of sensor networks is the cooperative effort of sensor nodes. Sensor nodes are fitted with an on-board processor. Instead of

A wireless sensor network (WSN) consists of hundreds to thousands of low-power multi-functional sensor nodes, operating in an unattended environment, and having sensing, computation and communication capabilities. The basic components [1] of a node are a sensor unit, an

Data Aggregation in Wireless Sensor Networks Introduction Wireless sensor networks are usually deployed in infrastructure-less environment with the sensor nodes themselves being battery powered (low powered) devices so, data aggregation is an attractive method to reduce the power requirements of the individual sensor nodes that sense, record and transmit the data about their surroundings. Data aggregation may refer to any number of methods that allow for the reduction of the volume of data that the sensor nodes must exchange by combining data from multiple sources and removing redundancies, thereby reducing the power consumption by the sensor nodes.

An adaptive clustering approach to dynamic load balancing and energy efficiency in wireless sensor networks HEBM (Hierarchical Energy-Balancing Multipath routing protocol for Wireless Sensor Networks)[70],introduce a novel hierarchical approach. It is proposed to degrading the general network energy consumption and balancing the energy clearing away among the sensor nodes, consequently, prolong the lifetime of the network. In order to achieve these two valuable approaches, the cluster-heads are carefully designed and distributed appropriately over the area of interest which. Moreover, nodes radio is turned off periodically according to sleeping control rules,

A wireless sensor network can be composed of a large number of nodes, constituting a