ODT: Optimal deadline-based trajectory for mobile sinks in WSN: A decision tree and dynamic programming approach

Self Cite

Summary Network performance can be improved by using a mobile sink (MS) to collect sensed data in a wireless sensor network. In this paper, we design an efficient trajectory for MS, collecting data from sensor nodes in a multihop fashion, with the aim of prolonging the network lifetime. Considering event‐driven applications, we present an approach to jointly determine the optimal trajectory for MS and data paths and transmission rates from source nodes to MS, without considering any rendezvous points. In these applications, an MS is supposed to harvest the data from source nodes in a given time‐slot. We first show that this problem is in form of a mixed integer nonlinear programming model, which is NP‐hard. Then, to achieve an approximate solution, we divide the mentioned problem into 2 simple subproblems. In fact, after determining an approximate zone for the trajectory of MS, the optimal data paths and transmission rates from source nodes to the MS are obtained through a mathematical optimization model. Finally, to illustrate the efficiency of the proposed approach, we compare the performance of our algorithm to an rendezvous point–based and also the state‐of‐the‐art approach in different scenarios.

Section: Related Workmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

𝒩

to MS in a multihop manner.…”

Section: Problem Descriptionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Multihop data gathering in wireless sensor networks with a mobile sink

Tashtarian

Sohraby

Varasteh

2017

Self Cite

Energy aware tree‐based sink relocation routing protocol to improve the lifetime of wireless sensor networks

Keerthika

Hency

2021

Summary In wireless sensor network (WSN), the design of routing protocols focuses mainly on the energy efficiency based on the application of the network. Over the past years, researchers developed many solutions to protract the life expectancy of the network by reducing the consumption of energy by each node. One of the main approaches is the usage of sink in mobility; this reduces the hotspot problem and energy consumption. Aiming at this problem, the paper proposes a new routing algorithm which supports the sink mobility with energy aware tree‐based sink relocation routing protocol (TBSR) using adaptive fuzzy decision‐making approach (AF‐MADM). In TBSR, a self ‐organized routing tree is formed, which reduces the consumption of energy. In the beginning, the clustering process is employed using fuzzy possibilistic C‐means (FPCM) algorithm. Further, the fuzzy analytic hierarchy process (FAHP) with multiplicative exponential weighting model is developed for optimal decision making to select the root node. Then the selected root node creates a routing tree based on the distance and energy of the sensor nodes. Then each node uses its cluster information and the distance of the neighbors to select the parent node. For relocating the sink node, the proposed protocol calculates the energy along with hop count and path capacity. These methods make TBSR an energetic and analogous protocol. Results show that the proposed TBSR improves on the energy consumption and the lifetime of the network compared with existing protocols. The simulation is carried out in OMNET++ platform.

DDC‐OMDC: Deadline‐based data collection using optimal mobile data collectors in Internet of Things

Wala

Kumar

Chauhan

et al. 2023

Summary Mobile data collectors (MDCs) are very efficient for data collection in internet of things (IoT) sensor networks. These data collectors collect data at rendezvous points to reduce data collection latency. It is paramount to determine these points in an IoT network to collect data in real time. It is important to consider IoT network characteristics to collect data on a specific deadline. First, the disconnected IoT sensor network is a real challenge in IoT applications. Second, it is essential to determine optimal data collection points (DCPs) and MDCs simultaneously to collect data in real time. In this study, Deadline‐based Data Collection using Optimal Mobile Data Collectors (DDC‐OMDC) scheme is proposed that aims to collect data in a disconnected network with the optimal number of mobile data collectors in a specific deadline for delay‐intolerant applications. DDC‐OMDC works in two phases. In the first phase, the optimal number of MDCs is determined to collect data at the optimal data collection points to guarantee one‐hop data collection from each cluster. The optimal mobile data collectors are determined using optimal DCPs, data collection stopping time, and a specific deadline. In the second phase, the optimal data collection trajectory is determined for each MDC using the nearest neighbor heuristic algorithm to collect data in real time. The simulation results show that the proposed scheme outperforms in collecting data in real time and determines optimal mobile data collectors and optimal data collection trajectory to collect data in a specific deadline for delay‐intolerant applications.