Reinforced energy aware mobile sink path optimization strategies with enhanced security in wireless sensor networks

Abstract

Wireless Sensor Network (WSN) consists of numerous sensor nodes newlinerandomly deployed within a sensing environment, crucial for applications such newlineas environmental air pollution monitoring systems, military surveillance, newlineprecision agriculture, and smart city infrastructure etc. These sensor nodes are newlineconstrained by limited energy, bandwidth, and processing power, making newlineenergy-efficient and reliable communication a significant challenge. In a typical newlinemulti-hop WSN, the source node detects data and transmits it to a static sink newlinenode through intermediary gateway nodes. This method consumes considerable newlineenergy, especially for nodes near the sink, leading to faster node depletion, newlineuneven energy usage, and ultimately a reduced network lifetime. This creates an newline energy hole problem near the sink node, which negatively impacts data newlinereliability and long-term network sustainability. To address this, Mobile Sink newline(MS) deployment is introduced as a promising solution. By dynamically moving newlinearound the network and gathering data at pre-determined locations called newlineRendezvous Points (RPs), the MS balances energy consumption, reduces newlinetransmission load on static nodes, and prolongs network lifetime. However, this newlinedynamic mobility introduces its own set of challenges including the need for newlinereal-time path optimization, minimizing communication latency during newlinemovement, and avoiding redundant data collection. The primary objective of this newlineresearch is to devise an optimal MS path-planning strategy that minimizes energy newlineconsumption, reduces packet delivery delays, and extends network lifetime newline