Hybrid energy-efficient multi-path routing for wireless sensor networks

Sajwan, Mohit; Gosain, Devashish; Sharma, Ajay K.

doi:10.1016/j.compeleceng.2018.03.018

Cited by 76 publications

(41 citation statements)

References 13 publications

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“…Further, the authors have optimized ASPLR approach using a genetic algorithm and enhanced the network lifetime. HEEMP eliminates the problem of unbalanced cluster formation by partitioning the network into balance clusters in which BS computes chance of election (CE) metrics for each node based on the residual energy and node degree . BS also ensures that the selected CHs are at minimum distance apart so as to have a balanced distribution of clusters inside the network.…”

Section: Related Workmentioning

confidence: 99%

“…() But, in the centralized scheme, for instance, enhanced and cluster routing algorithm (ECRA) and hybrid energy‐efficient multi‐path (HEEMP), the BS aggregates all the essential information of all the sensing nodes using Global Positioning System (GPS) to configure the routing structure of the network. () However, these result in loaded message overhead that further causes heavy traffic in the network. To circumvent of loaded overhead, the authors carried out and proposed a modified distributed scheme and is an extension of the current existing distributed GSTEB approach.…”

Section: Introductionmentioning

confidence: 99%

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A distributed, multi‐hop, adaptive, tree‐based energy‐balanced routing approach

Arora

Sharma²,

Sachdeva

2019

Int J Communication

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To accomplish the primary objective of data sensing and collection of wireless sensor networks (WSN), the design of an energy efficient routing algorithm is very important. However, the energy constrained sensing nodes along with the intrinsic properties of the (WSN) environment makes the routing a challenging task. To overcome this routing dilemma, an improved distributed, multi-hop, adaptive, tree-based energy-balanced (DMATEB) routing scheme is proposed in this paper. In this scheme, a relay node is selected in view of minimum distance and high energy from a current sensing node. Further, the parent node is chosen among the selected relay nodes on the basis of high residual energy and less power consumption with due consideration of its associated child nodes.As each sensing node itself selects its parent among the available alternatives, the proposed scheme offers a distributive and adaptive approach. Moreover, the proposed system does not overload any selected parent of a particular branch as it starts acting as a child whenever its energy lowers among the other available relay nodes. This leads to uniform energy utilization of nodes that offers a better energy balance mechanism and improves the network lifespan by 20% to 30% as compared with its predecessors. KEYWORDS energy efficient routing, tree-based structure, wireless sensor network Int J Commun Syst. 2019;32:e3949.wileyonlinelibrary.com/journal/dac

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Section: Related Workmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

A distributed, multi‐hop, adaptive, tree‐based energy‐balanced routing approach

Arora

Sharma²,

Sachdeva

2019

Int J Communication

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“…This study have analyzed the various traditional route and CH selection protocols in previous section and has observed that even after having such a vast variety of routing and CH election protocols there are some limitations that still need to overcome anyhow. In traditional routing approach HEEP [1], the author had developed HEEP with an objective to enhance the network lifetime by reducing the load of the nodes as the election of route from CH to sink node was performed by the sink node or BS itself. The CH election was done on the basis of the following three parameters are Residual energy of the nodes, Node degree and Initial energy of the nodes.…”

Section: Problem Formulationmentioning

confidence: 99%

“…On the contrary, this shows the way to an issue that the sensor network protocols and techniques must have the self-organizing feature. The sensor nodes in the network have an inbuilt embedded processor that performs the locally carried out calculations automatically and also enables a sensor to transmit the processed data packets instead of raw or unprocessed data [1]. The transmissions of data from one node to another node take place by applying the process of routing.…”

Section: Introductionmentioning

confidence: 99%

A Hybrid Energy Efficient Reactive Multipath Routing for Wireless Sensor Network

2019

IJITEE

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The efficiency of the wireless sensor network (WSN) can be evaluated by using various factors such as lifetime of the network, number of dead nodes, number of alive nodes, throughput of the network etc. All these factors are highly influenced by CH and route formation process as the election of right node for CH and route is quite tedious task to perform. Thus a large number of researches has been conducted in previous years. Few of the previous approaches have been discussed in this study and it is analyzed that the traditional HEEMP approach in quite effective to enhance the network lifetime but has a weak data communication and transmission strategy. Thus a novel approach is developed in this work by using the traditional HEEMP approach. The modification in the proposed work is done in terms of data gathering and data transmission strategy. Only the relevant and meaningful data packets are transmitted to the BS. The performance analysis of the proposed and traditional HEEMP protocol is compared and proposed work is found to be effective than the HEEMP protocol in terms of lifetime of the network.

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“…Chanak et al [19] discussed the balance of energy consumption among deployed sensors in a WSN. The energy-optimal routing problem in WSNs has recently been studied by several works [20][21][22]. The improvement of energy consumption by clustering method in a WSN has also been discussed by some works [23,24].However, the measured values of energy consumption in real-life WSN systems are usually uncertain and imprecise.…”

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confidence: 99%

Solving Multi-Objective Fuzzy Optimization in Wireless Smart Sensor Networks under Uncertainty Using a Hybrid of IFR and SSO Algorithm

et al. 2018

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Wireless (smart) sensor networks (WSNs), networks made up of embedded wireless smart sensors, are an important paradigm with a wide range of applications, including the internet of things (IoT), smart grids, smart production systems, smart buildings and many others. WSNs achieve better execution efficiency if their energy consumption can be better controlled, because their component sensors are either difficult or impossible to recharge, and have a finite battery life. In addition, transmission cost must be minimized, and signal transmission quantity must be maximized to improve WSN performance. Thus, a multi-objective involving energy consumption, cost and signal transmission quantity in WSNs needs to be studied. Energy consumption, cost and signal transmission quantity usually have uncertain characteristics, and can often be represented by fuzzy numbers. Therefore, this work suggests a fuzzy simplified swarm optimization algorithm (fSSO) to resolve the multi-objective optimization problem consisting of energy consumption, cost and signal transmission quantity of the transmission process in WSNs under uncertainty. Finally, an experiment of ten benchmarks from smaller to larger scale WSNs is conducted to demonstrate the effectiveness and efficiency of the proposed fSSO algorithm.Energies 2018, 11, 2385 2 of 23 the WSN system fails because nodes deplete their limited battery power. In other words, a critical restriction in any WSN system is energy consumption. Therefore, numerous investigations of WSNs have had a primary focus on energy consumption.Optimizing energy efficiency (EE) in a WSN, which is defined as the ratio of output over energy consumption, has been the subject of a great number of studies. Mekonnen et al. [2] proposed a prototype of a WSN applied in a video surveillance system to optimize energy consumption. Trapasiya and Soni [11] addressed the goal of retransmission energy reduction in WSNs. Quang and Kim [12] proposed a gradient routing in an industrial WSN to optimize energy consumption. Setiawan et al. [13] came up with an energy management policy to maximize energy transfer efficiency for a WSN. Liu et al. [14] optimally designed a WSN to minimize energy consumption.The minimization of energy consumption in WSNs has also been investigated by many researches [15][16][17][18]. Chanak et al. [19] discussed the balance of energy consumption among deployed sensors in a WSN. The energy-optimal routing problem in WSNs has recently been studied by several works [20][21][22]. The improvement of energy consumption by clustering method in a WSN has also been discussed by some works [23,24].However, the measured values of energy consumption in real-life WSN systems are usually uncertain and imprecise. Fuzzy set theory can effectively resolve these uncertain and imprecise problems. In studies of energy consumption for WSNs, few researchers have presented fuzzy-based methods to solve uncertainty problems in such systems. Collotta et al. [25] considered the turning on/off of devices as the output of a Fuzz...

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Hybrid energy-efficient multi-path routing for wireless sensor networks

Cited by 76 publications

References 13 publications

A distributed, multi‐hop, adaptive, tree‐based energy‐balanced routing approach

A distributed, multi‐hop, adaptive, tree‐based energy‐balanced routing approach

A Hybrid Energy Efficient Reactive Multipath Routing for Wireless Sensor Network

Solving Multi-Objective Fuzzy Optimization in Wireless Smart Sensor Networks under Uncertainty Using a Hybrid of IFR and SSO Algorithm

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