• Journal of the Korea Society for Simulation
• /
• v.18 no.3
• /
• pp.47-59
• /
• 2009

Due to the application-specific nature of wireless sensor networks, the sensitivity to such a requirement as data reporting latency may vary depending on the type of applications, thus requiring application-specific algorithm and protocol design paradigms which help us to maximize energy conservation and thus the network lifetime. In this paper, we propose a novel delay-adaptive sensor scheduling scheme for energy-saving data gathering which is based on a two phase clustering (TPC). The ultimate goal is to extend the network lifetime by providing sensors with high adaptability to the application-dependent and time-varying delay requirements. The TPC requests sensors to construct two types of links: direct and relay links. The direct links are used for control and forwarding time critical sensed data. On the other hand, the relay links are used only for data forwarding based on the user delay constraints, thus allowing the sensors to opportunistically use the most energy-saving links and forming a multi-hop path. Simulation results demonstrate that cluster-based delay-adaptive data gathering strategy (CD-DGS) saves a significant amount of energy for dense sensor networks by adapting to the user delay constraints.

• The Journal of the Korea Contents Association
• /
• v.9 no.9
• /
• pp.31-40
• /
• 2009

What are important in wireless sensor networks are reliable data transmission, energy efficiency of each node, and the maximization of network life through the distribution of load among the nodes. The present study proposed DSPR, a dynamic unique path routing machanism that considered these requirements in wireless sensor networks. In DSPR, data is transmitted through a dynamic unique path, which has the least cost calculated with the number of hops from each node to the sink, and the average remaining energy. At that time, each node monitors its transmission process and if a node detects route damage it changes the route dynamically, referring to the cost table, and by doing so, it enhances the reliability of the network and distributes energy consumption evenly among the nodes. In addition, when the network topology is changed, only the part related to the change is restructured dynamically instead of restructuring the entire network, and the life of the network is extended by inhibiting unnecessary energy consumption in each node as much as possible. In the results of our experiment, the proposed DSPR increased network life by minimizing energy consumption of the nodes and improved the reliability and energy efficiency of the network.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.15 no.4
• /
• pp.1317-1341
• /
• 2021

Nowadays, the Internet of Things (IoT) is adopted to enable effective and smooth communication among different networks. In some specific application, the Wireless Sensor Networks (WSN) are used in IoT to gather peculiar data without the interaction of human. The WSNs are self-organizing in nature, so it mostly prefer multi-hop data forwarding. Thus to achieve better communication, a cross-layer routing strategy is preferred. In the cross-layer routing strategy, the routing processed through three layers such as transport, data link, and physical layer. Even though effective communication achieved via a cross-layer routing strategy, energy is another constraint in WSN assisted IoT. Cluster-based communication is one of the most used strategies for effectively preserving energy in WSN routing. This paper proposes a Bio-inspired cross-layer routing (BiHCLR) protocol to achieve effective and energy preserving routing in WSN assisted IoT. Initially, the deployed sensor nodes are arranged in the form of a grid as per the grid-based routing strategy. Then to enable energy preservation in BiHCLR, the fuzzy logic approach is executed to select the Cluster Head (CH) for every cell of the grid. Then a hybrid bio-inspired algorithm is used to select the routing path. The hybrid algorithm combines moth search and Salp Swarm optimization techniques. The performance of the proposed BiHCLR is evaluated based on the Quality of Service (QoS) analysis in terms of Packet loss, error bit rate, transmission delay, lifetime of network, buffer occupancy and throughput. Then these performances are validated based on comparison with conventional routing strategies like Fuzzy-rule-based Energy Efficient Clustering and Immune-Inspired Routing (FEEC-IIR), Neuro-Fuzzy- Emperor Penguin Optimization (NF-EPO), Fuzzy Reinforcement Learning-based Data Gathering (FRLDG) and Hierarchical Energy Efficient Data gathering (HEED). Ultimately the performance of the proposed BiHCLR outperforms all other conventional techniques.

• Journal of Korea Society of Industrial Information Systems
• /
• v.14 no.1
• /
• pp.64-72
• /
• 2009

Previous research on sensor networks mainly focused on efficient transmission of data from sensors to fixed sink nodes. Recently there has been active research on mobile sink nodes, but the re-search of an environment where both fixed sink nodes and mobile sinks are present at the same time is rather scarce. This paper proposes a technique for context gathering by mobile devices with the sink functionality added through fixed sinks under a previously built, cluster based multi hop sensor network environment. To this end, clustering of mobile devices were done based on the fixed sinks of a previously built sensor network, and by using appropriate fixed sinks, context gathering was made possible. By mathematical comparison with TTDD routing protocol, which was proposed for mobile sinks, it was conformed that performance increases in energy with the number of mobile sinks, and with the number of movements by mobile devices.