Agent Based Multipath Routing in wireless sensor networks

Ramadan, Rabie A.

doi:10.1109/ia.2009.4927501

Cited by 18 publications

(5 citation statements)

References 15 publications

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“…This section deals with the second solution developed for the deployment problem, the ACO technique. In ACO [22][23][24], to find a solution to the deployment problem, ants build solutions incrementally by walking randomly through a connected graph G(P,E), where P denotes the set of the deployment points and E represents a set of all undirected links connecting the deployment points and the sink node. To construct a solution to the deployment problem, each ant k starts its tour at each mobile node location and then consecutively builds the connected covers through transitioning among the deployment points in the construction graph.…”

Section: Ant Colony Optimization Based Solutionmentioning

confidence: 99%

Efficient Node Deployment of Large-Scale Heterogeneous Wireless Sensor Networks

et al. 2021

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Wireless Sensor Networks (WSNs) became essential in developing many applications, including smart cities and Internet of Things (IoT) applications. WSN has been used in many critical applications such as healthcare, military, and transportation. Such applications depend mainly on the performance of the deployed sensor nodes. Therefore, the deployment process has to be perfectly arranged. However, the deployment process for a WSN is challenging due to many of the constraints to be taken into consideration. For instance, mobile nodes are already utilized in many applications, and their localization needs to be considered during the deployment process. Besides, heterogeneous nodes are employed in many recent applications due to their efficiency and cost-effectiveness. Moreover, the development areas might have different properties due to their importance. Those parameters increase the deployment complexity and make it hard to reach the best deployment scheme. This work, therefore, seeks to discover the best deployment plan for a WSN, considering these limitations throughout the deployment process. First, the deployment problem is defined as an optimization problem and mathematically formulated using Integer Linear Programming (ILP) to understand the problem better. The main objective function is to maximize the coverage of a given field with a network lifetime constraint. Nodes’ mobility and heterogeneity are added to the deployment constraints. The importance of the monitored field subareas is also introduced in this paper, where some subareas could have more importance than others. The paper utilizes Swarm Intelligence as a heuristic algorithm for the large-scale deployment problem. Simulation experiments show that the proposed algorithm produces efficient deployment schemes with a high coverage rate and minimum energy consumption compared to some recent algorithms. The proposed algorithm shows more than a 30% improvement in coverage and network lifetime.

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Section: Ant Colony Optimization Based Solutionmentioning

confidence: 99%

Efficient Node Deployment of Large-Scale Heterogeneous Wireless Sensor Networks

et al. 2021

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“…Multi-path-based data aggregation techniques (Vidhyapriya & Vanathi, 2007;Ramadan, 2009) build multiple paths among sensor nodes for data transmission and data aggregation. In these techniques, one node sends its data to multiple neighbors instead of one neighbor.…”

Section: Multi-path-based Data Aggregation Techniquesmentioning

confidence: 99%

QoS-Aware Chain-Based Data Aggregation in Cooperating Vehicular Communication Networks and Wireless Sensor Networks

Taghikhaki

Zhang

Meratnia

et al. 2015

Transportation Systems and Engineering

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Vehicular Communication Networks (VCNs) and Wireless Sensor Networks (WSNs) are emerging types of networks, which have individually been extensively explored. However, their cooperation and exploring advantages offered by their integration are poorly explored. Such integration helps better investigate impacts of human mobility and transportation behaviors on safety and well-being of cities, their residents, their surrounding environments, and ecology. In this chapter, the authors propose a QoS-Aware Chain-based data Aggregation (QoS-ACA) technique for wireless sensor networks cooperating with vehicular communication networks, which fast, reliably, and energy efficiently aggregates sensor data and sends the aggregated value to the road side units. Ensuring quality of service parameters has been put forward as an essential consideration for wireless sensor networks, which are often deployed in unattended and open environments and are characterized by their limited resources. To this end, in-network data aggregation is an efficient solution to save energy and bandwidth and to provide meaningful information to end-users.

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“…This protocol provides reliability and low energy consumption. Agent based multipath routing presented in [33] which describe the use of agents to reduce the complexity in routing technique. The agents also reduce the communication cost.…”

Section: Related Workmentioning

confidence: 99%

“…The proposed scheme is compared with an existing basic DV-hop localization scheme and agent based multipath routing scheme [33]. In this section we describe the simulation model, performance parameters and result analysis.…”

Section: Simulationmentioning

confidence: 99%