Chain‐routing scheme with compressive sensing‐based data acquisition for Internet of Things‐based wireless sensor networks

Abstract

The emerging Internet of Things (IoT)-based systems that integrate diverse types of sensors, mobiles and other technologies to physical world is becoming increasingly popular for use in wide varieties of applications. Compressive sensing (CS)-based information acquisition and in-network compression provide an effective method for accurate data recovery at the base station (BS) with reduced cost of communication. In this study, how CS can be combined with routing protocols for gathering data in IoT-based Wireless Sensor Networks (WSNs) in an energy-efficient manner are examined. A novel chain-routing scheme with CS based data acquisition is introduced that includes the following new algorithms: (1) Seed Estimation Algorithm (SEA) to find the best measurement matrix by selecting the best-estimated seed, (2) Chain Construction Algorithm (CCA) to organise the network nodes during transmitting and receiving process, (3) Compression approach with reduced consumption of energy that improves the lifetime of the network by minimising the local data traffic, and (4) Reconstruction Algorithm (RA) that reconstructs the original data with minimum reconstruction error. Here, extensive simulation and analysis results prove the performance of our proposed method in improving the network lifetime 35% better than the ECST algorithm and 93% better than the PEGASIS algorithm. In addition, the proposed reconstruction algorithm exceeds the other reconstruction algorithms performance. 1 | INTRODUCTION The gaining popularity of Internet of Things (IoT) makes it an emerging field of research where researchers attempt to connect/interact everyday items to the Internet [1,2]. IoT sensors or computing networks can be embedded in living as well as inanimate objects, including clothing, food, plants, animals and vehicles. The augmentation of these objects with computational capabilities extends their functions and promises to transform numerous fields such as health, logistics, military and entertainment industries [3-6]. In last few years, Wireless Sensor Network (WSN) applications in particular surveillance, transportation and monitoring applications have attracted a number of researchers [7-10]. WSN is considered as the most crucial IoT component in which the IoT devices can communicate wirelessly [11-13]. However, limited power, storage and processor of IoT devices are considered the main challenges that hinder the development of IoT applications. Framing effective routing protocols for IoT network is a crucial aspect. The massive energy constraints of densely integrated sensor nodes motivated the development of several routing protocols for IoT-based Wireless Sensor Networks (WSNs). Chain-based routing protocols are considered as one of the energy efficient solutions for IoT network, in which the nodes in IoT network are arranged to create a chain. A chain can be built by the WSN nodes on their own by adopting a greedy strategy initiated from any node in the network or can be built by the base station (BS) which will compute and broadcas...

EE-TLT: Energy-efficient routing protocol using two-level tree-based clustering in wireless sensor network

“…Each node then finds the nearest node to connect to the branched-chain using the greedy algorithm. Aziz et al [32] proposed an efficient energy routing scheme by combining a chain formation algorithm and data fusion, a data compression method that reduces the data packet size before forwarding it to the BS, thereby prolonging the network lifetime. Experimental results show that this scheme is more efficient than PEGASIS and ETCS protocols due to not using data compression.…”

“…We employ the energy dissipation model, which is similar to [32], [42] for consuming energy in wireless communication. Whenever a node transfers a packet containing q-bit data among two micro-sensor nodes with distance d, the energy used by the radio is calculated as follows:…”

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“…Internet to make our life easier [1], [2], [3], [4], [5], [6], [7], [8], [9], [10], [11], [12]. IoT has become a significant industrial and academic research field in recent years.…”