Hyunduk Kim

Distance Based Pre-cluster Head Selection Scheme for a Chain-Based Protocol

PEGASIS, a chain-based protocol, forms chains from sensor nodes so that each node transmits and receives from a neighbor. In this way, only one node (known as a HEAD) is selected from that chain to transmit to the sink. Although PEGASIS is able to balance the workload among all of the nodes by selecting the HEAD node in turn, a considerable amount of energy may be wasted when nodes which are far away from sink node act as the HEAD. In this study, DERP (Distance-based Energy-efficient Routing Protocol) is proposed to address this problem. DERP is a chain-based protocol that improves the greedy-algorithm in PEGASIS by taking into account the distance from the HEAD to the sink node. The main idea of DERP is to adopt a pre-HEAD (P-HD) to distribute the energy load evenly among sensor nodes. In addition, to scale DERP to a large network, it can be extended to a multi-hop clustering protocol by selecting a “relay node” according to the distance between the P-HD and SINK. Analysis and simulation studies of DERP show that it consumes up to 80% less energy, and has less of a transmission delay compared to PEGASIS.

Distance Based Energy Efficient Clustering Method in Wireless Sensor Networks

In the past decade, various hierarchical clustering methods have been proposed in order to efficiently minimize the energy consumption of sensor nodes. The energy consumption of such clustering methods heavily depends on the size of clusters and the number of member nodes. Existing methods form clusters by considering the distance between the sink node and each node. However, if clusters are formed based only on the distance, the numbers of nodes in clusters are not uniformly distributed, resulting in unbalanced cluster structures. To address the problem, we propose a method to build the optimal clusters by adjusting the size of clusters and number of nodes that are included, according to the distance between a sink node and normal nodes.

A context aware cooperative communication method in wireless sensor networks

In wireless sensor networks, the clustering methods proposed to improve the energy efficiency of a sensor network can lead to severe energy consumption by the cluster heads. Furthermore, in the case where an unbalanced cluster structure is generated, the overall lifetime of the sensor networks is significantly reduced. Moreover, existing cooperative communication methods, for example, CoopLEACH, waste energy because of the unilateral cooperative communication method, which does not consider the distance between the sink and cluster heads. To solve these problems, this paper proposes a novel method that transmits and collects data according to the density of the nodes and the distance between the sink and cluster heads. Through extensive performance studies, we observed that our method is 12% more energy-efficient than CoopLEACH.

Adaptive Mobile Sink Path Based Energy Efficient Routing Protocol for Wireless Sensor Network

In this paper, we propose a novel approach to optimize the movement of mobile sink node, called AMSP(Adaptive Mobile Sink Path) for mobile sensor network environments. Currently available studies usually suffer from unnecessary data transmission resulting from random way point approach. To address the problem, we propose a method which uses the Hilbert curve to create a path. The proposed method guarantees shorten transmission distance between the sink node and each sensor node by assigning orders of the curve according to sensor node density. Furthermore, The schedule of the sink node is informed to all of the sensing nodes so that the Duty Cycle helps the network be more energy efficient. In our experiments, the proposed method outperforms the existing works such as TTDD and CBPER by up to 80% in energy consumption.

Energy efficient clustering using tree balancing algorithms in wireless sensor networks

Various hierarchical clustering schemes have been proposed in order to efficiently maintain the energy consumption of sensor nodes. Most of these schemes, however, are hardly applicable in practice since these schemes might produce unbalanced clusters or randomly distributed clusters without consideration for the distribution of sensor nodes. To overcome the limitations of such hierarchical clustering schemes, we propose a novel scheme called CUTA (Clustering Using Tree-balancing Algorithm) that exploits node split and merge algorithms of tree-based indexing structures to efficiently construct clusters. Our extensive performance studies show that CUTA produces highly balanced clustering in an energy efficient way and achieves up to 1.4 times higher performance than the previous clustering schemes, under various operational conditions.

An Energy-Aware Cooperative Communication Scheme for Wireless Multimedia Sensor Networks

Numerous clustering schemes have been proposed to increase energy efficiency in wireless sensor networks. Clustering schemes consist of a hierarchical structure in the sensor network to aggregate and transmit data. However, existing clustering schemes are not suitable for use in wireless multimedia sensor networks because they consume a large quantity of energy and have extremely short lifetime. To address this problem, we propose the Energy-Aware Cooperative Communication (EACC) method which is a novel cooperative clustering method that systematically adapts to various types of multimedia data including images and video. An evaluation of its performance shows that the proposed method is up to 2.5 times more energy-efficient than the existing clustering schemes.

Energy Efficient Clustering Scheme for Mobile Wireless Sensor Network

In this paper, we introduce an EMSP(Efficient Mobility Support Protocol) for mobile sensor network with mobility-aware. We propose virtual cluster and node split scheme considering movements of mobile nodes. The existing M-LEACH protocol suffers from communication cost spent on JOIN request information during invitation phase. To address this issue, the large boundary of the cluster in LUR-tree can reduce superfluous update cost. In addition to the expansion of the cluster, the proposed approach exploits node split algorithms used in R-tree in order to uniformly form a cluster. The simulated results show that energy-consumption has less up to about 40% than LEACH-C and 8% than M-LEACH protocol. Finally, we show that the proposed scheme outperforms those of other in terms of lifetime of sensor fields and scalability in wireless sensor network.

New TCP congestion control algorithm based on bandwidth measurement for seamless vertical handoffs in heterogeneous mobile networks

With the widespread use of wireless Internet and wireless LANs, different wireless technologies, such as 3G cellular networks and WLAN, will cooperate to support more users and applications with higher data rates over wider areas. When a mobile node moves between hybrid networks, a need arises for seamless vertical handoffs between different wireless networks in order to provide high performance data transmission. When an application with a TCP connection in a mobile node performs a vertical handoff, TCP performance is degraded due to packet loss even while the previous TCP state information is maintained during handoff, as 3G and WLAN have different available bandwidths. In this paper, a new congestion control algorithm is proposed for a vertical handoff that improves TCP performance by measuring the rough end-to-end available bandwidth and calculating the slow-start threshold. By ns-2 simulation it is shown that, compared to previous algorithms, the proposed algorithm enhances TCP performance during vertical handoffs.