A Speed Control-Based Big Data Collection Algorithm (SCBDCA) Using Clusters and Portable Sink WSNs

A Speed Control-Based Big Data Collection Algorithm (SCBDCA) Using Clusters and Portable Sink WSNs

Rajkumar Krishnan, Jeyalakshmi V., V. Ebenezer, Ramesh G.
DOI: 10.4018/978-1-7998-5068-7.ch010
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WSNs collects a huge amount of heterogeneous information and have been widely applied in various applications. Most of the information collecting techniques for WSNs can't keep away from the hotspot trouble. This problem affects the connectivity of the community and reduces the life of the entire community. Hence, an efficient speed control based data collection algorithm (SCBDCA) using mobile sink in WSNs is proposed. A tree construction technique is introduced based on weight such that the origin nodes of the built timber are described as rendezvous points (RPs). Also, other unique type of nodes named sub or additional rendezvous points (ARPs or SRPs) is chosen in accordance to their traffic consignment and hops to origin nodes in the network. Mobile sink gathers the information from the cluster head (CH) and is controlled by speed control mechanism. Simulation results among different existing procedures exhibit that the SCBDCA can extensively stabilize the consignment of the communication network, decrease the energy consumption, and extend the lifetime in the communication network.
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WSN contains numerous minute and minimum energy sensors that utilize radio frequencies to function allotted sensing jobs. WSNs locate their purposes in various areas that encompass affected person monitoring and sickness investigation, pollution supervising and source detection, equipment supervising and fault prediction, tide monitoring and sea searching. Large range of sensors is arranged in a Field of Interest (FoI) in speculator manner in such WSNs. The sensors nodes are frequently placed in huge amount randomly to assure trustworthiness in stochastic deployment. In data gathering process, a sensor node consumes plenty of energy in communication phase, particularly for a huge quantity of diverse information. Furthermore, in multi-hop transmission, sensors close to the sink devour more power as they are accountable for accepting and transferring information from the entire network. It gives the problem of uneven power utilization among sensors in the network, (i.e.) the hotspot problem. To solve this difficulty and stable the power utilization in the network, some Mobile Elements (MEs) like sink or information collector have been taken for information aggregation. In many information aggregation procedures, the latency is predictable if the MEs function for gathering information through shortest path in the network. Gathering of data in WSN in depicted in figure 1.

Figure 1.

Data gathering in WSN


Mobile information collecting procedures will be separated into two types: homogeneous (uniform) and heterogeneous sensor network. In uniform sensor arrangement, the sensors with minimum distance to the BS or sink path are fixed as polling spot for the MEs to see in the communication network. The different sensor network made up of fixed sensors, super nodes, MEs and a fixed BS. The super nodes usually have greater assets to perform as Rendezvous Points (RPs) and Sub Rendezvous Points (SRPs) for information collection. The range and place of these super nodes ought to be restricted to reduce the MEs tour size which shortens the information collecting delay in the communication network.

The main contributions of the paper include the following key points: Clustering and Cluster Head (CH) selection by taking remaining power and the utilization of the nodes to its nearby nodes.

  • Both RP and SRP selection after positive collection series and balancing the energy utilization.

  • Controlling the speed of the mobile sink using speed control mechanism.

The remaining part of this paper is prepared as follows: part 2 describes the literature of data gathering algorithms. In part 3, the network model and the details of proposed scheme, Speed Control based Data Collection Algorithm (SCBDCA) using mobile sink in WSNs is given. The part 4 illustrates the simulation outcomes and performance investigation. As a final point, the conclusion and future work are introduced in part 5.


Some related papers on mobile information collecting in WSNs are discussed and grouped into two classes in this section: one-hop communication gathering where one or many MEs sees every sensors and accumulate its information solely by using one-hop path and multi-hop communication gathering where the MEs solely go to a division of sensors or some specific places and other sensors have to transmit their information through multi-hop route. Multi-hop communication gathering again classified into two types based totally on the quantity of information required to be gathered: neighboring information gathering where only collects information from origin nodes required to be gathered and complete information gathering where information of the entire arrangement required to be gathered.

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