Effects Of Data Aggregation In Wireless Sensor Networks

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.

3) Secure data aggregation: Fine grain sensing is one of the important compensation of a wireless sensor network which is provided by the large and dense sets of nodes .So to avoid overwhelming amounts of traffic, the sensed values must be aggregated and the aggregation may take place in many places in the network depending on the architecture of the wireless sensor network. For example, the system may average the temperature of a geographic region, combine sensor values to compute the location and velocity of a moving object, or aggregate data to avoid false alarms in real-world event detection. All aggregation locations must be secured [8].

Large amounts of data streams are generated in resource-constrained environments. Sensor networks represent a typical example. These devices

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.

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.

This protocol gives longer network life time and vitality sparing contrasted with LEACH protocol TL-LEACH: its works in three stages, cluster head packaging, and Cluster setup and data transmission. In this protocol the creator enhance the LEACH in which a portion of the CHs chose amid setup stage in LEACH were picked again as the level-2 CHs, which have the correspondence with the base station.

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,

S. Yi, et al [7] in this thesis, proposed PEGASIS (Power- efficient gathering in sensor data networks), a greedy protocol for expanding the network lifetime of the WSNs. Clustering protocols enable sensor nodes to lessen data packets by data aggregation on WSN.

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

LEACH-B: Authors proposed decentralized algorithms of cluster formation in which sensor node just thinks about possess position and position of definite beneficiary and not the position of all sensor nodes. Filter B works in following stages: Cluster head selection algorithm, Cluster development and data transmission with numerous gets to. Every sensor node picks its CH by assessing the vitality scattered in the way between conclusive recipient and itself. It gives preferred energy efficiency over LEACH.

A Wireless Sensor Network (WSN) has a large number of energy constrained sensor nodes that have the capability to compute and communicate. They are used to identify the events of interests and transfer the data to the sink node.

Clustering of Wireless Sensor Network is important to increase the network scalability. Cluster Based Wireless sensor Network (CWSN) are organised in hierarchical manner. In CWSN a leader node called Cluster Head (CH) is responsible for aggregation of data from the leaf nodes which are present in the Cluster. In this paper we will discuss how to transmit the data securely and efficiently over the network.

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