From carbon nanotubes and silicate layers to graphene platelets for polymer nanocomposites

In spite of extensive studies conducted on carbon nanotubes and silicate layers for their polymer-based nanocomposites, the rise of graphene now provides a more promising candidate due to its exceptionally high mechanical performance and electrical and thermal conductivities. The present study developed a facile approach to fabricate epoxy–graphene nanocomposites by thermally expanding a commercial product followed by ultrasonication and solution-compounding with epoxy, and investigated their morphologies, mechanical properties, electrical conductivity and thermal mechanical behaviour. Graphene platelets (GnPs) of 3.5

Collaborative Distributed Scheduling Approaches for Wireless Sensor Network

Energy constraints restrict the lifetime of wireless sensor networks (WSNs) with battery-powered nodes, which poses great challenges for their large scale application. In this paper, we propose a family of collaborative distributed scheduling approaches (CDSAs) based on the Markov process to reduce the energy consumption of a WSN. The family of CDSAs comprises of two approaches: a one-step collaborative distributed approach and a two-step collaborative distributed approach. The approaches enable nodes to learn the behavior information of its environment collaboratively and integrate sleep scheduling with transmission scheduling to reduce the energy consumption. We analyze the adaptability and practicality features of the CDSAs. The simulation results show that the two proposed approaches can effectively reduce nodes' energy consumption. Some other characteristics of the CDSAs like buffer occupation and packet delay are also analyzed in this paper. We evaluate CDSAs extensively on a 15-node WSN testbed. The test results show that the CDSAs conserve the energy effectively and are feasible for real WSNs

Multi-objective function-based node-disjoint multipath routing for mobile ad hoc networks

Funding Information: This work was supported Korea Environmental Industry & Technology Institute (KEITI) grant funded by the Korea government (Ministry of Environment). Project No. RE202101551, the development of IoT-based technology for collecting and managing Big data on environmental hazards and health effects.Peer reviewedPublisher PD

PERFORMANCE ANALYSIS AND OPTIMIZATION OF QUERY-BASED WIRELESS SENSOR NETWORKS

This dissertation is concerned with the modeling, analysis, and optimization of large-scale, query-based wireless sensor networks (WSNs). It addresses issues related to the time sensitivity of information retrieval and dissemination, network lifetime maximization, and optimal clustering of sensor nodes in mobile WSNs. First, a queueing-theoretic framework is proposed to evaluate the performance of such networks whose nodes detect and advertise significant events that are useful for only a limited time; queries generated by sensor nodes are also time-limited. The main performance parameter is the steady state proportion of generated queries that fail to be answered on time. A scalable approximation for this parameter is first derived assuming the transmission range of sensors is unlimited. Subsequently, the proportion of failed queries is approximated using a finite transmission range. The latter approximation is remarkably accurate, even when key model assumptions related to event and query lifetime distributions and network topology are violated. Second, optimization models are proposed to maximize the lifetime of a query-based WSN by selecting the transmission range for all of the sensor nodes, the resource replication level (or time-to-live counter) and the active/sleep schedule of nodes, subject to connectivity and quality-of-service constraints. An improved lower bound is provided for the minimum transmission range needed to ensure no network nodes are isolated with high probability. The optimization models select the optimal operating parameters in each period of a finite planning horizon, and computational results indicate that the maximum lifetime can be significantly extended by adjusting the key operating parameters as sensors fail over time due to energy depletion. Finally, optimization models are proposed to maximize the demand coverage and minimize the costs of locating, and relocating, cluster heads in mobile WSNs. In these models, the locations of mobile sensor nodes evolve randomly so that each sensor must be optimally assigned to a cluster head during each period of a finite planning horizon. Additionally, these models prescribe the optimal times at which to update the sensor locations to improve coverage. Computational experiments illustrate the usefulness of dynamically updating cluster head locations and sensor location information over time

Improving the Energy Efficiency of Mobile Terminals Using Dynamic Multilevel Priority Packet Scheduling in Cooperative Communication

Cooperative communication is an efficient method for reducing the energy consumption of mobile terminal in wireless cellular network. However, it is hard to implement due to the lack of motivations for the Mobile terminals to cooperate. For this scenario as the benchmark case, where the information of the helping mobile terminals such as the channel and battery conditions is completely known by the source node terminal, the problem is formulated as a relay selection problem. Efficient algorithms based on dichotomous search and alternative optimizations are proposed to solve the problem for the cases of split and non-split data at the source MT, respectively. The cooperative communications scheme with pricing mechanism can decrease both the battery outages and communications for the mobile node, and can also increase the average battery level during the mobile terminals operation. In this paper, we state a Dynamic Multilevel Priority (DMP) packet scheduling scheme. In the proposed system, each node, except those which are at the last level of the virtual hierarchy in the zone based topology of Wireless sensor network , have three levels of priority queues. Real-time packets are placed in the highest-priority queue and can preempt data packets in other queues. Non-real-time packets are placed in other two queues based on a certain threshold of their estimated processing time. Leaf nodes will have two queues for real-time and non-real-time data packets since they do not receive data from other nodes and so this reduce end to- end delay. The performance of the proposed Dynamic multilevel priority packet scheduling scheme through simulations for real-time and non-real-time data packet. Simulation results shows that the DMP packet scheduling scheme outperforms conventional schemes interms of average data waiting time and end-to-end delay