• Journal of Information Processing Systems
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• v.20 no.2
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• pp.252-262
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• 2024

The multi-hop wireless sensor network (WSN) suffers from energy limitation and eavesdropping attacks. We propose a simple and energy-efficient convergecast mechanism using inter-flow random linear network coding that can provide confidentiality to the multi-hop WSN. Our scheme consists of two steps, constructing a logical tree of sensor nodes rooted at the sink node, with using the Bloom filter, and transmitting sensory data encoded by sensor nodes along the logical tree upward to the sink where the encoded data are decoded according to our proposed multi-hop network coding (MHNC) mechanism. We conducted simulations using OMNET++ CASTALIA-3.3 framework and validated that MHNC outperforms the conventional mechanism in terms of packet delivery ratio, data delivery time and energy efficiency.

• International Journal of Computer Science & Network Security
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• v.24 no.10
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• pp.109-114
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• 2024

Wireless Sensor Networks (WSN) includes a large number of small sensor nodes and low cost, which are randomly located in a region. The wireless sensor network has attracted much attention from universities and industry around the world over the past decades, with features denser levels of node deployment, self-configuration, uncertainty of sensor nodes, computing, and memory constraints. Black-hole attack is one of the most known attacks on this network. In this study, the combination of fuzzy logic and particle swarm optimization (PSO) algorithms is proposed as an effective method for detecting black-hole attack in the AODV protocol. In the current study, a new function has been proposed in order to determine the membership of fuzzy parameters based on the particle swarm optimization algorithm. The proposed method was evaluated in different scenarios and was compared with other state of arts. The simulation result of this method proved the better performance in both detection rate and delivered packet rate.

• Journal of KIISE:Information Networking
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• v.33 no.1
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• pp.76-90
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• 2006

Sensor network consists of a large number of sensor nodes that are densely deployed either inside the phenomenon or very close to it. The life time of each node in the sensor network significantly affects the life time of whole sensor network. A node which drained out its battery may incur the partition of whole network in some network topology The life time of each node depends on the battery capacity of each node. Therefore if all sensor nodes in the network live evenly long, the life time of the network will be longer. In this paper, we propose Cluster-Based Power-Efficient Routing (CBPER) Protocol which provides scalable and efficient data delivery to multiple mobile sinks. Previous r(luting protocols, such as Directed Diffusion and TTDD, need to flood many control packets to support multiple mobile sinks and many sources, causing nodes to consume their battery. In CBPER, we use the fact that sensor nodes are stationary and location-aware to construct and maintain the permanent grid structure, which makes nodes live longer by reducing the number of the flooding control packets. We have evaluated CBPER performance with TTDD. Our results show that CBPER is more power-efficient routing protocol than TTDD.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.8
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• pp.3621-3640
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• 2016

In the process of k-coverage of the target node, there will be a lot of data redundancy forcing the phenomenon of congestion which reduces network communication capability and coverage, and accelerates network energy consumption. Therefore, this paper proposes a novel energy balanced k-coverage control algorithm based on probability model (EBKCCA). The algorithm constructs the coverage network model by using the positional relationship between the nodes. By analyzing the network model, the coverage expected value of nodes and the minimum number of nodes in the monitoring area are given. In terms of energy consumption, this paper gives the proportion of energy conversion functions between working nodes and neighboring nodes. By using the function proportional to schedule low energy nodes, we achieve the energy balance of the whole network and optimizing network resources. The last simulation experiments indicate that this algorithm can not only improve the quality of network coverage, but also completely inhibit the rapid energy consumption of node, and extend the network lifetime.

• Journal of Advanced Marine Engineering and Technology
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• v.39 no.2
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• pp.187-194
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• 2015

Accurate relative location estimation is a key requirement in indoor localization systems based on wireless sensor networks (WSNs). However, although these systems have applied not only various optimization algorithms but also fusion with sensors to achieve high accuracy in position determination, they are difficult to provide accurate relative azimuth and locations to users because of cumulative errors in inertial sensors with time and the influence of external magnetic fields. This paper based on ultra-wideband positioning system, which is relatively suitable for indoor localization compared to other wireless communications, presents an indoor localization system for estimating relative azimuth and location of location-unaware nodes, referred to as target nodes without applying any algorithms with complex variable and constraints to achieve high accuracy. In the proposed method, the target nodes comprising three mobile nodes estimate the relative distance and azimuth from two reference nodes that can be installed by users. In addition, in the process of estimating the relative localization information acquired from the reference nodes, positioning errors are minimized through a novel modified rounding estimation technique in which Kalman filter is applied without any time consumption algorithms. Experimental results show the feasibility and validity of the proposed system.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.4
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• pp.1866-1888
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• 2017

Efficient energy consumption in WSN is one of the key design issues for improving network stability period. In this paper, we propose a new Heterogeneity-aware Energy-efficient Clustering (HEC) technique which considers two types of heterogeneity - network lifetime and of sensor nodes. Selection of cluster head nodes is done based on the three network lifetime phases: only advanced nodes are allowed to become cluster heads in the initial phase; in the second active phase all nodes are allowed to participate in cluster head selection process with equal probability, and in the last dying out phase, clustering is relaxed by allowing direct transmission. Simulation-based performance analysis of the proposed technique as compared to other relevant techniques shows that HEC achieves longer stable region, improved throughput, and better energy dissipation owing to judicious consumption of additional energy of advanced nodes. On an average, the improvement observed for stability period over LEACH, SEP, FAIR and HEC- with SEP protocols is around 65%, 30%, 15% and 17% respectively. Further, the scalability of proposed technique is tested by varying the field size and number of sensing nodes. The results obtained are found to be quite optimistic. The impact of energy heterogeneity has also been assessed and it is found to improve the stability period though only upto a certain extent.

• International journal of advanced smart convergence
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• v.6 no.1
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• pp.57-67
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• 2017

In this paper, propose an algorithm to improve network lifetime by equally consuming energy of LEACH - Mobile sensor nodes. LEACH is one of energy efficient protocols. However, we did not consider the mobility of nodes. Therefore, the transmission reception success rate of the moving data is reduced. LEACH-Mobile is a protocol that has improved the drawbacks of these LEACH. However, since LEACH-Mobile has a larger number of data packets and consumes more energy than LEACH, it has a disadvantage that the lifetime of the network is short. In order to improvement these disadvantage, Based on the average of the remaining energy of the node, cluster heads are elected with a number of nodes whose energies are larger than the average of the remaining energy from the member nodes. After that, by trying to increase the lifetime of the network by equalizing the remaining energy. In to confirm whether improve the lifetime of the network, In this paper, the number of nodes and the position of all nodes are varied for each specific round, the rest energy is equalized, and the algorithm which uniformly selected the cluster head is compared with LEACH.

• Journal of Korea Multimedia Society
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• v.10 no.2
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• pp.269-277
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• 2007

Network clustering has been proposed to provide that sensor nodes minimize energy and maximize a network lifetime by configuring clusters, Although dynamic clustering brings extra overhead like as head changing, head advertisement, it may diminish the gain in energy consumption to report attribute tasks by using cluster heads. Therefore, this paper proposes a new routing algorithm which configures cluster to reduce the number of messages when establishing paths and reports to the sink by way of cluster heads when responding sens ing tasks. All sensor nodes only broadcast bitmap once and maintain a bitmap table expressed by bits, allowing them to reduce node energy and to prolong the network lifetime. After broadcasting, each node only updates the bitmap without propagation when the adjacent nodes broad cast same query messages, This mechanism makes nodes to have abundant paths. By modifying the query which requests sensing tasks, the size of cluster is designed dynamically, We try to divide cluster by considering the number of nodes. Then, all nodes in a certain cluster must report to the sub- sink node, The proposed routing protocol finds easily an appropriate path to report tasks and reduces the number of required messages for the routing establishment, which sensor nodes minimize energy and maximize a network lifetime.

• Journal of KIISE:Information Networking
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• v.35 no.4
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• pp.337-344
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• 2008

Underwater acoustic sensor networks exhibit characteristics such as high propagation delay and low data rates, which are different from those of terrestrial wireless networks. Therefore, the conventional protocols used in wireless networks can be restrictive and inefficient when applied to underwater acoustic sensor networks. In this paper, we propose a medium access control protocol (MAC) to enhance the energy efficiency and throughput in underwater acoustic sensor networks. The proposed protocol employs a slot-based competition mechanism that reserves a time slot to send a data packet in advance. In the proposed protocol, collision between nodes can occur due to competition to obtain a slot. However, the proposed protocol minimizes the collisions between nodes because the nodes store the reservation information of the neighboring nodes, this reduces unnecessary energy consumption and increases throughput. We perform a simulation to evaluate the performance of the proposed protocol with regard to the energy consumption, the number of collision, channel utilization, throughput and transmission delay. We compare the proposed protocol with the conventional protocol, and the performance results show that the proposed protocol outperforms the conventional protocol.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.17 no.1
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• pp.167-172
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• 2017

Mobile nodes are used for prolonging the life-time of the entire wireless sensor networks and many studies that use drones to collected data have been actively conducted with the development of drone related technology. In case of associating a drone and tactical wireless sensor networks, real-time feature and efficiency are improved. The previous studies so focus on reducing drone's flight distance that the energy consumption of sensor nodes is unbalanced. This unbalanced energy consumption accelerates the network partition and increases drone's flight distance. In this paper, we proposed a new selection scheme considered drone's flight distance and nodes' life-time to solve this problem when rendezvous nodes that collect data from their cluster and directly communicate with a drone are selected.