A Number Of Studies And Researches Showing The Improvement Within The Protocol Of Wireless Sensor Networks

Geographic Adaptive Fidelity (GAF): Geographic Adaptive Fidelity is an energy-aware location based routing algorithm planned for mobile ad-hoc networks but has been used to WSNs. Geographic Adaptive Fidelity conserving energy by switching off redundant sensors nodes. In this routing protocol, the entire network is classified into number of static zones and a virtual grid is made for the covered region. Every node utilizes its GPS-indicated location to link itself with a point in the virtual grid. Nodes linked to the same point on the grid are assumed equivalent with respect to packet routing costs. Nodes within a zone cooperate by choosing one node to show the zone for a period of time whereas the rest of the nodes sleep. A sample situation is considered from

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.

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 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.

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

After electing CHs, every CH announces all sensor nodes in the network that it is the new CH. When each node receives the announcement, it chooses its desired cluster to join based on the signal strength of the announcement from the CHs to it. So, the sensor nodes inform their appropriate CH to join it. Afterwards, the CHs based on a TDMA approach assign the time slot to each node so that a member can send its data to its CH in this period. The sensor nodes can initiate sensing and transmitting data to the CHs during the steady state phase. The CHs also aggregate data received from the nodes in their cluster before sending these data to the BS via a single hop fashion. D. Hybrid Energy Efficient Distributed Clustering [HEED] Younis and Fahmy proposed an iterative clustering protocol, named HEED. HEED is different from LEACH in the way CHs are elected. Both, electing the CHs and joining to the clusters, are done based on the combination of two parameters. The primary parameter depends on the nodes residual energy. The alternative parameter is the intra cluster “communication cost”. Each node computes a communication cost depending on whether variable power levels, applied for intra cluster communication, are permissible or not. If the power level is fixed for all of the nodes, then the communication cost can be proportional to (i) node

This algorithms segment the all nodes into clusters of unequal size, and clusters closer to the sink have littler sizes than those more wireless far from the sink. Therefore CHs nearer to the sink can preserved some vitality for the inter cluster data sending. Vitality devoured by cluster heads per round in EEUC much lower than that of LEACH standard yet like HEED protocol.

Sensor network protocols have a unique capability self-organizing. Another interesting feature of wireless sensor networks is that the sensor nodes cooperate with each other. Sensor nodes have an in-built processor, using which before transmission raw data is processed. These features facilitate wide range of applications of wireless sensor networks like biomedical, environmental, military, event detection and vehicular telematics.

However, a group of sensors collaborating with each other can accomplish a much bigger task efficiently. They can sense and detect desired events/data from a field of interest, and then communicate with each other in an optimal fashion to perform data aggregation, and then route the aggregated data to sinks or base stations that can make application-specific decisions and link to the outside world via the Internet or satellites. One of the primary advantages of deploying a wireless sensor network is its ease-deployment and freedom from having a complicated wired communication backbone that is often inconvenient of deployment in the remote area.

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

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,

Development in Wireless Communication and networking has led to development of many applications like Bluetooth, Near Field Communications and Wireless Sensor Networks. A wireless sensor network is essentially a network of nodes which consist of a power supply, sensors which usually sense the ambient conditions and processors for storing and processing information collected and a transceiver unit which is used to transmit and receive information from other nodes. In addition it might have a GPS system which provides location based services. This Wireless Sensor network is divided into 3 main parts: Bottom nodes, cluster heads and network coordinators. The data collected by a node is transmitted to its cluster head, in turn, the data collected by the cluster head is sent to the network coordinator and data at the network coordinator can be sent to nearby clusters using a router and internet.

Low Energy Aware Cluster Hierarchy (LEACH) is one of the hierarchical routing protocols that uses very limited amount of energy and increases the lifetime of the network. Transfer of Data through Wireless Sensor Network is a challenging task today particularly with the existence of Denial of Service (DoS) attacks, Flooding attack, Black hole attach and Gray hole attack. All attacks mentioned above are implemented and their impacts on the performance of the LEACH in terms of different metrics including packet

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