A novel dynamic clustering approach for energy hole mitigation in Internet of Things‐based wireless sensor network

Summary Technological advancements in the area of the Internet of Things have fostered the development of multi‐hop architectures pertaining to applications seeking large network areas. However, while exploiting such applications, the sensor devices being used are made to communicate through multi‐hop routing techniques, burdening the relay nodes. Hence, it leads to a hot‐spot problem, as the nodes passing on the data, that is, relay nodes, consume their energy at a large magnitude. To solve this issue, in this paper, we propose a novel optimized routing technique to mitigate hot‐spot problem (NORTH) for wireless sensor network (WSN)‐based IoT. We employ the tunicate swarm algorithm (TSA) to optimize the cluster‐based routing, specifically the selection of cluster head (CH) of each cluster by using some novel parameters. These parameters include energy status, a distance of a node from the sink and other nodes, load balancing, node proximity, and average energy stock of the network. We investigate two network scenarios, that is, when a sink is placed inside the network and otherwise, to give an optimized solution for every case. Further, to mitigate the hot‐spot problem, the relay node is selected in a cluster with the same mechanism as CH, which performs the task of data forwarding. The simulation analysis of NORTH reveals the supremacy of the proposed work against the recently proposed algorithms, based on various performance metrics, namely, network longevity, stability duration, throughput, and the network's remaining energy.

Section: Related Workmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

“…The performance is compared to the recently proposed algorithms for hot‐spot problem mitigation. These algorithms are CIRP, 5 DECEM, 1 MEEC, 18 IDHR, 18 and GAOC 8 …”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

A novel optimized routing technique to mitigate hot‐spot problem (NORTH) for wireless sensor network‐based Internet of Things

Yadav

Poongoodi

2022

“…Due to advancements in various areas such as sensing, communication, microelectronics, and embedded systems, the Internet of Things (IoT) has expanded its scope to include a multitude of applications, ranging from habitat to environment monitoring, agricultural to healthcare, military to industrial, and many more 1,2 . On the basis of IoT, smart cities are formed utilizing intelligent information processing, 3 universal connectivity, 4 ubiquitous sensing, 5 and real‐time monitoring 6 .…”

Section: Introductionmentioning

confidence: 99%

Cognitive Long‐range: Towards efficient public communication infrastructure for Internet of Things

Mousavi

Khademzadeh

Rahmani

2022

Summary The most common Internet of Things (IoT) scenarios entail devices with limited energy resources and need to be connected to the Internet via wireless networks. This has driven the recent development of low‐power wide‐area networks (LPWANs) and the rise of the Long Range (LoRa) technology. The LoRa protocol has a simple modulation scheme that ensures low power consumption, high convergence, and resistance against interference. In most LPWAN technologies, several physical layer challenges arise, such as low data rates, spectral inefficiency, and increased interference. As a physical layer solution, the cognitive radio (CR) offers a possible way of resolving these challenges. CR allows wireless networks to operate without the need for a dedicated spectrum. Regarding the variety of end‐user requirements, developing a public communication network that can support such diverse and heterogeneous applications is necessary to reduce the implementation costs than developing a dedicated communication network for each application. This paper proposes a Cognitive LoRa (C‐LoRa) protocol that utilizes unlicensed and licensed frequencies as well as interference mitigation to improve the QoS of LoRa. To extract the priority list of traffic patterns, C‐LoRa incorporates the Analytic Hierarchy Process (AHP) algorithm. The priority list enables real‐time applications to receive optimal spectrum allocation. C‐LoRa can be efficiently implemented as a public communication infrastructure for heterogeneous IoT devices. The addition of licensed channels improves the overall QoS and decreases the average waiting time in queues. The platform layer of C‐LoRa consists of a cognitive engine that sends traffic priority lists to cognitive spectrum allocators. The IoT application servers are connected to the cloud platform layer via SNMP, HTTP, and other desired protocols. Access gateways equipped with a cognitive spectrum allocator are always connected to a power supply and serve as a transparent bridge to the cognitive engine at the platform layer, converting RF packets to IP packets and vice versa.

A two‐level clustering mechanism for energy enhancement in Internet‐of‐Things‐based wireless sensor networks

Obaidat

Alshamali

Jararweh

2021

Summary Wireless sensors are considered the key elements in enabling efficient Internet of Things (IoT) networking and services. One of the key objectives in designing a WSN is increasing network lifetime by reducing the overall network energy consumption. To achieve this, several techniques have been proposed to extend the network lifetime, such as clustering. Clustering divides the network into several clusters, each with its own member nodes and a cluster‐head (CH) node. In this paper, a novel clustering mechanism is developed with the objective of extending network lifetime through load balancing in wireless sensor networks (WSNs). This is achieved by electing a new node to a provides specific tasks in the WSN to decrease energy consumption and enhance network lifetime. This node is called a relay node that is responsible of delivering the received data packets from the CHs, and then forwards them to the central node (sink). Unlike previous clustering schemes, the proposed algorithm consists of three main processes: CH selection, relay node selection, and medium access control processes. These processes depend on energy level and user's distributions. The performance of the proposed algorithm is investigated through simulation experiments in terms of network lifetime under various network parameters. The results reveal that the proposed mechanism significantly enhances network lifetime compared to previously proposed algorithms.