A tree cluster-based data-gathering algorithm for industrial ws ns with a mobile sink
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The document presents a tree-cluster-based data-gathering algorithm (tcbdga) for wireless sensor networks (WSNs) with a mobile sink to address the hotspot problem, which affects network connectivity and lifetime. It introduces a novel weight-based tree construction method, utilizing rendezvous points and sub rendezvous points for efficient data collection. Simulation results demonstrate that tcbdga significantly balances network load, reduces energy consumption, and prolongs network lifetime compared to other algorithms.
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A tree cluster-based data-gathering algorithm for industrial ws ns with a mobile sink
- 1. Logic Mind Technologies Vijayangar (Near Maruthi Medicals), Bangalore-40 Ph: 8123668124 // 8123668066 A Tree-Cluster-Based Data-Gathering Algorithm for Industrial WSNs with a Mobile Sink Abstract Wireless sensor networks (WSNs) have been widely applied in various industrial applications, which involve collecting a massive amount of heterogeneous sensory data. However, most of the data-gathering strategies for WSNs cannot avoid the hotspot problem in local or whole deployment area. Hotspot problem affects the network connectivity and decreases the network lifetime. Hence, we propose a tree-cluster-based data-gathering algorithm (TCBDGA) for WSNs with a mobile sink. A novel weight-based tree-construction method is introduced. The root nodes of the constructed trees are defined as rendezvous points (RPs). Additionally, some special nodes called sub rendezvous points (SRPs) are selected according to their traffic load and hops to root nodes. RPs and SRPs are viewed as stop points of the mobile sink for data collection, and can be reselected after a certain period. The simulation and comparison with other algorithms show that our TCBDGA can significantly balance the load of the whole network, reduce the energy consumption, alleviate the hotspot problem, and prolong the network lifetime.
- 2. SYSTEM SPECIFICATION Software Specification Operating system : Linux (Ubuntu) Software : Network Simulator 2.35 Programming languages : Tool Command Language, AWK, C++ Hardware Specification Main processor : Dual Core Hard disk capacity : 80GB Cache memory : 2 GB PROJECT FLOW: First Review: Literature Survey Paper Explanation Design of Project Project Enhancement explanation Second Review: Implementing 40% of Base Paper Third Review Implementing Remaining 60% of Base Paper with Future Enhancement (Modification) For More Details please contact Logic Mind Technologies Vijayangar (NearMaruthi Medicals), Bangalore-40 Ph: 8123668124 // 8123668066 Mail: logicmindtech@gmail.com