• Journal of the Korea Society for Simulation
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• v.14 no.4
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• pp.95-106
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• 2005

Recent advances in wireless sensor networks have led to many routing protocols designed for energy-efficiency in wireless sensor networks. Despite that many routing protocols have been proposed in wireless sensor networks, a single routing protocol cannot be energy-efficient if the environment of the sensor network varies. This paper presents a fuzzy logic based Adaptive Routing (FAR) algorithm that provides energy-efficiency by dynamically changing protocols installed at the sensor nodes. The algorithm changes protocols based on the output of the fuzzy logic which is the fitness level of the protocols for the environment. A simulation is performed to show the usefulness of the proposed algorithm.

• International Journal of Computer Science & Network Security
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• v.22 no.1
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• pp.139-148
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• 2022

Research into wireless sensor networks (WSNs) is a trendy issue with a wide range of applications. With hundreds to thousands of nodes, most wireless sensor networks interact with each other through radio waves. Limited computational power, storage, battery, and transmission bandwidth are some of the obstacles in designing WSNs. Clustering and routing procedures have been proposed to address these concerns. The wireless sensor network's most complex and vital duty is routing. With the Greedy Perimeter Stateless Routing method (GPSR), an efficient and responsive routing protocol is built. In packet forwarding, the nodes' locations are taken into account while making choices. In order to send a message, the GPSR always takes the shortest route between the source and destination nodes. Weighted directed graphs may be constructed utilising four distinct distance metrics, such as Euclidean, city block, cosine, and correlation distances, in this study. NS-2 has been used for a thorough simulation. Additionally, the GPSR's performance with various distance metrics is evaluated and verified. When compared to alternative distance measures, the proposed GPSR with correlation distance performs better in terms of packet delivery ratio, throughput, routing overhead and average stability time of the cluster head.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2018.05a
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• pp.649-651
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• 2018

Since the ubiquitous sensor network is not connected to external power source and operated by its own battery, it is required to maximize the network life using the efficient energy utilization. In a conventional hop count based routing protocol, most sensor nodes are designed with a constant transmission power. In this paper, we propose a routing protocol that prolongs the network lifetime by balancing the power consumption among the nodes by controlling the transmit power according to the residual power of the nodes, and compared the performance of the proposed routing protocol through computer simulations.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.9
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• pp.4272-4286
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• 2016

In resource constrained sensor networks, usage of efficient routing protocols can have significant impact on energy dissipation. To save energy, we propose an energy efficient routing protocol. In our approach, which integrates clustering and routing in sensor networks, we perform network coding during data routing in order to achieve additional power savings in the cluster head nodes. Efficacy of the proposed method in terms of the throughput and end-to-end delay is demonstrated through simulation results. Significant network lifetime is also achieved as compared with other techniques.

• International Journal of Computer Science & Network Security
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• v.22 no.10
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• pp.67-72
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• 2022

A wireless sensor network (WSN), with its constrained sensor node energy supply, needs an energy-efficient routing technique that maximises overall system performance. When rumours are routed using a random-walk routing algorithm, which is not highly scalable, spiral pathways may appear. Because humans think a straight line is the quickest route between two sites and two straight lines in a plane are likely to intersect, straight-line routing (SLR) constructs a straight path without the aid of geographic information. This protocol was developed for WSNs. As a result, sensor nodes in WSNs use less energy when using SLR. Using comprehensive simulation data, we show that our upgraded SLR systems outperform rumour routing in terms of performance and energy conservation.

• Journal of Information Technology Services
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• v.6 no.1
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• pp.141-149
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• 2007

Sensor node's mobility brings new challenges to data dissemination in large sensor networks. Frequent location updates of sensor nodes can lead to both excessive drain of sensor's limited battery supply and increased collisions in wireless transmissions. Conventional studies for routing protocols in wireless sensor networks are not enough to cover energy consumption and migration of sensor nodes. This study proposes a dynamic routing protocol based on the SPIN considering energy consumption and the migration, and also shows the effectiveness of the proposed routing protocol.

• International Journal of Computer Science & Network Security
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• v.22 no.7
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• pp.91-102
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• 2022

With the evolution of wireless sensor network (WSN) technology, the routing policy has foremost importance in the Internet of Things (IoT). A systematic routing policy is one of the primary mechanics to make certain the precise and robust transmission of wireless sensor networks in an energy-efficient manner. In an IoT environment, WSN is utilized for controlling services concerning data like, data gathering, sensing and transmission. With the advantages of IoT potentialities, the traditional routing in a WSN are augmented with decision-making in an energy efficient manner to concur finer optimization. In this paper, we study how to combine IoT-based deep learning classifier with routing called, Kriging Regressive Deep Belief Neural Learning (KR-DBNL) to propose an efficient data packet routing to cope with scalability issues and therefore ensure robust data packet transmission. The KR-DBNL method includes four layers, namely input layer, two hidden layers and one output layer for performing data transmission between source and destination sensor node. Initially, the KR-DBNL method acquires the patient data from different location. Followed by which, the input layer transmits sensor nodes to first hidden layer where analysis of energy consumption, bandwidth consumption and light intensity are made using kriging regression function to perform classification. According to classified results, sensor nodes are classified into higher performance and lower performance sensor nodes. The higher performance sensor nodes are then transmitted to second hidden layer. Here high performance sensor nodes neighbouring sensor with higher signal strength and frequency are selected and sent to the output layer where the actual data packet transmission is performed. Experimental evaluation is carried out on factors such as energy consumption, packet delivery ratio, packet loss rate and end-to-end delay with respect to number of patient data packets and sensor nodes.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2009.10a
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• pp.517-520
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• 2009

Healthcare application system has been actively researched to apply WSN technology to healthcare area with a mobile sensor node of low cost, low power, and small size. Sensor node has the problem for transmission range of RF power and time delay of the wireless routing connectivity between sensor nodes. In this paper, we proposes a new method utilizing mobile sensor nodes with relay sensor nodes for quick network routing changing using query technique in healthcare system. A query processor to control and manage the routing changing of sensor nodes in a wireless sensor network was designed and implemented. The user's PC transmits the beacon message which will change the quick link routing according to activity status of patient in wireless sensor network. We describe the implementation for query protocol that is very effective of power saving between sensor nodes.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.5
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• pp.666-669
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• 2020

Energy harvesting sensor networks have the ability to collect energy from the environment to overcome the power limitations of traditional sensor networks. The sensor network, which has a limited transmission range, delivers data to the destination node through a multi-hop method. The routing protocol should consider the power situation of nodes, which is determined by the residual power and energy harvesting rate. At this time, if only considering the magnitude of the power, power imbalance can occur among nodes and it can induce instantaneous power shortages and reduction of network lifetime. In this paper, we designed a routing protocol that considers the balance of power as well as the residual power and energy harvesting rate.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.12
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• pp.4451-4466
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• 2014

We present joint radio selection and relay scheme that delivers data from a source to a sink in heterogeneous stationary sensor networks consisting of various radio interfaces. The proposed scheme finds the optimal relay nodes and their corresponding radio interfaces that minimize energy consumption throughout the network while satisfying the end-to-end packet deadline requirement. We formulate the problem of routing through radio interface selection into binary integer programs, and obtain the optimal solution by solving with an optimization solver. We examine a trade-off relationship between energy consumption and packet delay based on network level simulations. We show that given the end-to-end deadline requirement, our routing algorithm finds the most energy-efficient routing path and radio interface across mesh hops. We demonstrate that the proposed routing scheme exploits the given packet delivery time to turn into network benefit of reducing energy consumption compared to routing based on single radio interface.