Lifetime Maximization Of Wireless Sensor Network Using Load Balancing

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.

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

Nowadays, Wireless sensor networks (WSNs) are getting more and more involved in our society, researchers and manufacture. As the use of WSNs increases the more challenges rise to make them immune and life longer. Therefore, both fields industry and academia invest money to improve the capability of the security integrity, confidentiality, and authentication. Since WSNs are distributed in unfrequented and abandoned venues, the physical security is unconcerned or less concern. The most concern is the lifetime of Wireless sensor networks, sensors have limited source of power. Thus, economizing energy will keep sensors live longer, the less power means more efficiency. Moreover, secure data is important as well, since no one attends where sensors are located, it is easy to manipulate data or steal it. Cryptography provides high security to WSNs, using algorithms to encrypt and decrypt the sent data is

A wireless sensor network (WSN) consists of distributed sensors to monitor environmental conditions such as temperature, sound, vibration, pressure, motion or detect dimensions, to pass their data through the network to a base station for processing. Advantages of WSN over a wired system considered in elimination of wiring cost, sensors can be installed in harsh environments. Each sensor node is a combination of Radio transceiver with an internal antenna or connection to an external antenna micro-controller, electronic circuit for interfacing with the sensors, energy source, usually a battery or an embedded form of energy harvesting. Drawback of using sensors is having limited power to consume, a memory that is

Wireless sensor networks are often referred to as self-adaptable or self-organizing and self-mending or self-healing networks. The self-organizing property of the network facilitates for a node to join the network without any intervention automatically. The nodes in a network can reconstruct their link organizations and can form an alternative paths whenever a node in that link fails or gets damaged. The implementation of these two properties are very precise to the network topology and the network characteristics like scalability, cost, performance and various other issues are decided by the implementation capability of the properties. The sensor nodes in the wireless sensor networks does not require any engineering and are easily deployable. The sensor nodes often with multi hop connections are responsible for

In most cases, the sensors forming these networks are deployed randomly and left unattended to and are expected to perform their mission properly and efficiently. As a result of this random deployment, the WSN has usually varying degrees of node density along its area. Sensor networks are also energy constrained since the individual sensors, which the network is formed with, are extremely energy-constrained as well. The communication devices on these sensors are small and have limited power and range.

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

Wireless sensor networks typically consist of a large number of sensor nodes with limited onboard battery resources which are difficult to recharge or replace. Thus the reduction of energy consumption for end-to-end data rate and maximization of network lifetime have become chief research concern. In recent years, many techniques have been proposed for improving the energy efficiency in wireless sensor networks. Among these techniques, V-MIMO technique has been considered as one of the effective ways to save energy. In WSN a node has two communication related energy consuming roles, one role is to serve as a packet generating source node (SN), and the other role is to relay packets for the other nodes, which are both energy consuming operations. This is why the energy minimization is required to extend the lifetime of the WSN.

Abstract :- Due to recent improvement technologies in wireless communication ,there has been a fastest growth in wireless sensor networks technologies during the past few years. Many different architectures as well as algorithms and applications have been determined and implemented. The efficiency of these wireless sensor networks is as much as dependent on routing protocol directly affecting the network life and in wireless sensor network every sensor has a limited transmission range of every sensor node to obtain the sensing data. Due to this limitation of wireless sensor network Clustering of node is most popular techniques preferred in routing operations. In this paper, cluster based energy efficient clustering technique based on artificial bee colony algorithm and genetic algorithm is presented to increase the network lifetime. The name of artificial bee colony algorithm is come from bees cause It has been inspired by collective behavior of Bees as seeking food. To minimize the energy consumption it is significant to plan a data collection path with the minimum length to complete the data collection work. So in this paper, we determine that this problem which can be solve as traveling salesman problem, it 's also called as

T. Gui in 2016 [39] studied the mechanism of SMO in the field of WSNs in the paper “A Novel Cluster-based Routing Protocol Wireless Sensor Networks using Spider Monkey Optimization.” The study additionally showed the change in traditional routing protocols in term of low-energy consumption and system quality of the network. SMO-C protocol suggested in the paper worked for Wireless sensor networks to minimize global energy consumption.

Wireless distributed sensor systems will enable the reliable monitoring of a variety of environments for both civil and military applications. We look at communication protocols, which can have significant impact on the overall energy dissipation of these networks Based on our findings that the conventional protocols of direct transmission, minimum- transmission-energy, multihop routing, and static clustering may not be optimal for sensor networks. We are working on LEACH (Low-Energy Adaptive Clustering Hierarchy), a clustering-based protocol that utilizes randomized rotation of local cluster base stations (cluster-heads) to evenly distribute the energy load among the sensors in the network. LEACH uses localized coordination to enable scalability and robustness for dynamic networks and incorporates data fusion into the routing protocol to reduce the amount of information that must be transmitted to the base station. We are trying to make its life time more reliable than that of past working. [5]

In addition to one or more sensors, each node in a sensor network is typically equipped with a radio transceiver or other wireless communications device, a small microcontroller, and an energy source, usually a battery. The size a single sensor node can vary from shoebox-sized nodes down to devices the size of grain of dust.[1] The cost of sensor nodes is similarly variable, ranging from hundreds of dollars to a few cents, depending on the size of the sensor network and the complexity required of individual sensor nodes.[1] Size and cost constraints on sensor nodes result in corresponding constraints on resources such as energy, memory, computational speed and bandwidth.[1]

To solve the problems of flooding, an approach known as gossiping, has been proposed [ref]. Gossiping uses a simple forwarding method and does not need costly topology maintenance. It uses a randomized rule to forward data packets. Each sensor node transmits the incoming data packet to a randomly selected neighbor. After receiving the data packet, the neighbor randomly chooses one of its own neighbors and transmits the packet to the neighbor chosen. This process continues until the data packet reaches its destination or the hop count is exceeded. Gossiping limits the number of data packets that each sensor node is sent to its neighbor to one copy which avoids the implosion problem. However, random selection of neighboring node is an unsafe

Energy dissipation reduction:In WSNs, energy efficiency is a key design issue that needs to beenhanced in order to improve the life span of the network. The proposed protocol (EEHCBF)is able to route data efficiently in terms of energy.