Conference Paper

Bio-Inspired Routing in Wireless Sensor Networks

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Abstract

In order to increase network life time scalable, efficient and adaptive routing protocols are need of current time. Many energy efficient protocols have been proposed, the Clustering algorithm is also a basic technique used for energy efficiency.In this paper we propose an energy efficient routing protocol that is based on Artificial Bee Colony (ABC) algorithm of Bio Inspired.The presented protocol efficiently utilized characteristics of ABC algorithm such as foraging principle and waggle dance of honey bees. Waggle dance technique is used to find Routing Node (RN) that has maximum energy.Simulation results proves increase network life time and high throughput with minimum delay.

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... A wireless sensor network (WSN) comprises sensors that are spatially distributed [1] and deployed in an area called the sensor field [2]. Each sensor collects data and sends it to a central aggregation unit known as the base station (BS) or sink [3]. WSNs have a wide spectrum of applications, including environmental monitoring, target tracking, healthcare monitoring, and machine automation [1,4,5]. ...
... The basic components of a sensor node are shown in Figure 1. The sensors are limited in power, storage, and range [3]. They can perform: (1) computation, (2) communication, and (3) sensing [1]. ...
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Wireless Sensor Networks (WSNs) draw the attention of researchers due to the diversity of applications that use them. Basically, a WSN comprises many sensor nodes that are supplied with power by means of a small battery installed in the node itself; the node can also be self-charged by a solar cell. Sometimes it is impossible to change the power supply of battery-operated nodes. This dictates that sensor nodes must utilize the energy they have in an optimal manner. Data communication is the main cause of energy dissipation. In this context, designing protocols for WSNs demands more attention to the design of energy-efficient routing protocols that allow communications between sensor nodes and their base station (BS) with the least cost. LEACH is a prominent hierarchical cluster-based routing protocol. It groups sensor nodes into clusters to reduce energy dissipation. On the other hand, LEACH-C is a protocol based on LEACH that claims to improve energy dissipation over LEACH. In this paper, a successful attempt was made to compare these two protocols using MATLAB. The results show that LEACH-C has better performance than LEACH in terms of power dissipation.
... A novel nature-inspired algorithm named the salp swarm algorithm (SSA) is presented in [15] for accurate node localization in WSNs and is compared with four other optimization algorithms, namely the firefly algorithm, butterfly optimization algorithm, particle swarm optimization, and grey wolf optimizer based on its performance and simulation results [16]. An energy-efficient routing technique based on the artificial cee colony (ABC) algorithm that mimics the foraging behavior and waggle dance of bees is proposed in [17]. ...
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... In the presented work, the proposed novel routing scheme explicitly concentrates on the challenges of IBNNs by taking into account the fundamental disparity between the communication load and limited available resources of NBSs. In line with the vast applicability of bio-inspired solutions such as swarm intelligence algorithms for low energy and computational devices [15]- [17], they have been used in various applications, including energy-efficient clustering [18]- [20], node localization [21], [22], and improved data collection [23] in wireless sensor networks. Moreover, in the context of the internet of things and vehicular ad-hoc networks, bio-inspired routing techniques efficiently handle the frequently changing topology issues and enable the design of low complexity routing protocols [24], [25]. ...
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An Intrabody Nanonetwork (IBNN) is constituted by nanoscale devices that are implanted inside the human body for monitoring of physiological parameters for disease diagnosis and treatment purposes. The extraordinary accuracy and precision of these nanoscale devices in cellular level disease diagnosis and drug delivery are envisioned to advance the traditional healthcare system.However, the feature constraints of these nanoscale devices, such as inadequate energy resources, topology-unawareness, and limited computational power, challenges the development of energy-efficient routing protocol for IBNNs. The presented work concentrates on the primary limitations and responsibilities of IBNNs and designs a routing protocol that incorporates characteristics of Exponential Weighted Moving Average (EWMA) Based Opportunistic Data Transmission (EWMA-ODT) and Artificial Colony Algorithm Based Query Response Transmission (ABC-QRT) approaches for efficiently handling the routing challenges of IBNNs. In EWMA-ODT, the moving Nano Biosensors (NBSs) employ the EWMA method attributes to aggregate detected data by assigning high weightage to the recent detected information. Later, the aggregated data is transmitted to the Nano Router (NR) when the direct data transmission opportunity is available, the reception of aggregated briefs NR about the condition of the network after the last successful interaction with minimum energy consumption. Whereas, the ABC-QRT approach introduces the ABC algorithm for the selection of those optimal NBSs that have maximum fitness value for satisfying the data transmission demand of the external healthcare system with minimal traffic overhead. The simulation results validate that the joint contribution of these approach enhances IBNNs life time and reduces end-to-end delay as compared to the flooding scheme.
... In the presented work, the proposed novel routing scheme explicitly concentrates on the challenges of IBNNs by taking into account the fundamental disparity between the communication load and limited available resources of NBSs. In line with the vast applicability of bio-inspired solutions such as swarm intelligence algorithms for low energy and computational devices [15]- [17], they have been used in various applications, including energy-efficient clustering [18]- [20], node localization [21], [22], and improved data collection [23] in wireless sensor networks. Moreover, in the context of the internet of things and vehicular ad-hoc networks, bio-inspired routing techniques efficiently handle the frequently changing topology issues and enable the design of low complexity routing protocols [24], [25]. ...
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An Intrabody Nanonetwork (IBNN) is constituted by nanoscale devices that are implanted inside the human body for monitoring of physiological parameters for disease diagnosis and treatment purposes. The extraordinary accuracy and precision of these nanoscale devices in cellular level disease diagnosis and drug delivery are envisioned to advance the traditional healthcare system. However, the feature constraints of these nanoscale devices, such as inadequate energy resources, topology-unawareness, and limited computational power, challenges the development of energy-efficient routing protocol for IBNNs. The presented work concentrates on the primary limitations and responsibilities of IBNNs and designs a routing protocol that incorporates characteristics of Exponential Weighted Moving Average (EWMA) Based Opportunistic Data Transmission (EWMA-ODT) and Artificial Colony Algorithm Based Query Response Transmission (ABC-QRT) approaches for efficiently handling the routing challenges of IBNNs. In EWMA-ODT, the moving Nano Biosensors (NBSs) employ the EWMA method attributes to aggregate detected data by assigning high weightage to the recent detected information. Later, the aggregated data is transmitted to the Nano Router (NR) when the direct data transmission opportunity is available, the reception of aggregated briefs NR about the condition of the network after the last successful interaction with minimum energy consumption. Whereas, the ABC-QRT approach introduces the ABC algorithm for the selection of those optimal NBSs that have maximum fitness value for satisfying the data transmission demand of the external healthcare system with minimal traffic overhead. The simulation results validate that the joint contribution of these approaches enhances IBNNs lifetime and reduces end-to-end delay as compared to the flooding scheme.
Thesis
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The smart grid plays a vital role in decreasing electricity cost via Demand Side Management (DSM). Smart homes, being a part of the smart grid, contribute greatly for minimizing electricity consumption cost via scheduling home appliances. However, user waiting time increases due to the scheduling of home appliances. This scheduling problem is the motivation to find an optimal solution that could minimize the Peak to Average Ratio (PAR) and electricity cost with minimum user waiting time. There are many studies on Home Energy Management (HEM) for cost minimization and peak load reduction. However, none of the systems gave sufficient attention to tackle multiple parameters (i.e., electricity cost and peak load reduction) at the same time where user waiting time is considered to be minimum for residential consumers with multiple homes. 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Energy efficient routing protocol for Wireless Sensor Networks (WSNs) is one of the most challenging task for researcher. Hierarchical routing protocols have been proved more energy efficient routing protocols, as compare to flat and location based routing protocols. Heterogeneity of nodes with respect to their energy level, has also added extra lifespan for sensor network. In this paper, we propose a Centralized Energy Efficient Clustering (CEEC) routing protocol. We design the CEEC for three level heterogeneous network. CEEC can also be implemented in multi-level heterogeneity of networks. For initial practical, we design and analyze CEEC for three level advance heterogeneous network. In CEEC, whole network area is divided into three equal regions, in which nodes with same energy are spread in same region.
Conference Paper
Wireless distributed microsensor systems will enable the reliable monitoring of a variety of environments for both civil and military applications. In this paper, we look at communication protocols, which can have significant impact on the overall energy dissipation of these networks. Based on our findings that the conventional protocols of direct transmission, minimum-transmission-energy, multi-hop routing, and static clustering may not be optimal for sensor networks, we propose LEACH (Low-Energy Adaptive Clustering Hierarchy), a clustering-based protocol that utilizes randomized rotation of local cluster based station (cluster-heads) to evenly distribute the energy load among the sensors in the network. LEACH uses localized coordination to enable scalability and robustness for dynamic networks, and incorporates data fusion into the routing protocol to reduce the amount of information that must be transmitted to the base station. Simulations show the LEACH can achieve as much as a factor of 8 reduction in energy dissipation compared with conventional outing protocols. In addition, LEACH is able to distribute energy dissipation evenly throughout the sensors, doubling the useful system lifetime for the networks we simulated.
Article
Data aggregation is important in energy constraint wireless sensor networks which exploits correlated sensing data and aggregates at the intermediate nodes to reduce the number of messages exchanged network. This paper considers the problem of constructing data aggregation tree in a wireless sensor network for a group of source nodes to send sensory data to a single sink node. The ant colony system provides a natural and intrinsic way of exploring search space in determining data aggregation. Moreover, we propose an ant colony algorithm for data aggregation in wireless sensor networks. Every ant will explore all possible paths from the source node to the sink node. The data aggregation tree is constructed by the accumulated pheromone. Simulations have shown that our algorithm can reduce significant energy costs.
Article
The clustering Algorithm is a kind of key technique used to reduce energy consumption. It can increase the scalability and lifetime of the network. Energy-efficient clustering protocols should be designed for the characteristic of heterogeneous wireless sensor networks. We propose and evaluate a new distributed energy-efficient clustering scheme for heterogeneous wireless sensor networks, which is called DEEC. In DEEC, the cluster-heads are elected by a probability based on the ratio between residual energy of each node and the average energy of the network. The epochs of being cluster-heads for nodes are different according to their initial and residual energy. The nodes with high initial and residual energy will have more chances to be the cluster-heads than the nodes with low energy. Finally, the simulation results show that DEEC achieves longer lifetime and more effective messages than current important clustering protocols in heterogeneous environments.
Article
In recent years, there has been a growing interest in wireless sensor networks. One of the major issues in wireless sensor network is developing an energy-efficient clustering protocol. Hierarchical clustering algorithms are very important in increasing the network’s life time. Each clustering algorithm is composed of two phases, the setup phase and steady state phase. The hot point in these algorithms is the cluster head selection. In this paper, we study the impact of heterogeneity of nodes in terms of their energy in wireless sensor networks that are hierarchically clustered. We assume that a percentage of the population of sensor nodes is equipped with the additional energy resources. We also assume that the sensor nodes are randomly distributed and are not mobile, the coordinates of the sink and the dimensions of the sensor field are known. Homogeneous clustering protocols assume that all the sensor nodes are equipped with the same amount of energy and as a result, they cannot take the advantage of the presence of node heterogeneity. Adapting this approach, we introduce an energy efficient heterogeneous clustered scheme for wireless sensor networks based on weighted election probabilities of each node to become a cluster head according to the residual energy in each node. Finally, the simulation results demonstrate that our proposed heterogeneous clustering approach is more effective in prolonging the network lifetime compared with LEACH.
Conference Paper
In this paper, we propose a novel hierarchical clustering approach for wireless sensor networks to maintain energy depletion of the network in minimum using Artificial Bee Colony Algorithm which is a new swarm based heuristic algorithm. We present a protocol using Artificial Bee Colony Algorithm, which tries to provide optimum cluster organization in order to minimize energy consumption. In cluster based networks, the selection of cluster heads and its members is an essential process which affects energy consumption. Simulation results demonstrate that the proposed approach provides promising solutions for the wireless sensor networks.
Article
In this paper, a family of ant colony algorithms called DAACA for data aggregation has been presented which contains three phases: the initialization, packet transmission and operations on pheromones. After initialization, each node estimates the remaining energy and the amount of pheromones to compute the probabilities used for dynamically selecting the next hop. After certain rounds of transmissions, the pheromones adjustment is performed periodically, which combines the advantages of both global and local pheromones adjustment for evaporating or depositing pheromones. Four different pheromones adjustment strategies are designed to achieve the global optimal network lifetime, namely Basic-DAACA, ES-DAACA, MM-DAACA and ACS-DAACA. Compared with some other data aggregation algorithms, DAACA shows higher superiority on average degree of nodes, energy efficiency, prolonging the network lifetime, computation complexity and success ratio of one hop transmission. At last we analyze the characteristic of DAACA in the aspects of robustness, fault tolerance and scalability.
Hexagonally sectored routing protocol for wireless sensor networks
  • A J Joseph
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A. J. Joseph and U. Hari, "Hexagonally sectored routing protocol for wireless sensor networks," in International Journal of Engineering Research and Technology, vol. 2, ESRSA Publications, 2013.
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Energyefficient communication protocol for wireless microsensor networks
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Cluster based wireless sensor network routing using artificial bee colony algorithm
  • D Karaboga
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D. Karaboga, S. Okdem, and C. Ozturk, "Cluster based wireless sensor network routing using artificial bee colony algorithm," Wireless Networks, vol. 18, no. 7, pp. 847-860, 2012.