Clustering of Nodes in Layered-Tree Topology for Wireless Sensor Networks

Wireless sensor network is composed of a large number of sensor nodes of limited energy resource. The node clustering approach can improve the scalability and lifetime of wireless sensor network. In this paper we propose a novel node clustering protocol based on layered-tree topology for self-organizing distributed wireless sensor networks. It decides optimal number of clusters by employing a new approach for setting threshold value, including the probability of optimum number of cluster-heads and residual energy of the nodes. We also introduce a new scheme for layered-tree construction in each cluster. As a result, the proposed scheme can significantly improve the energy efficiency of the network and increase its lifetime. Computer simulation shows that the proposed scheme effectively reduces and balances the energy consumption of the nodes, and thus significantly extends the network lifetime compared to the existing schemes

TDP1 and TOP1 Modulation in Olaparib-Resistant Cancer Determines the Efficacy of Subsequent Chemotherapy

The aim of this study was to elucidate the carryover effect of olaparib to subsequent chemotherapy and its underlying mechanisms. We generated olaparib-resistant SNU-484, SNU-601, SNU-668, and KATO-III gastric cancer cell lines and confirmed their resistance by cell viability and colony forming assays. Notably, olaparib-resistant cell lines displayed cross-resistance to cisplatin except for KATO-III. Inversely, olaparib-resistant SNU-484, SNU-668, and KATO-III were more sensitive to irinotecan than their parental cells. However, sensitivity to paclitaxel remained unaltered. There were compensatory changes in the ATM/ATR axis and p-Chk1/2 protein expression. ERCC1 was also induced in olaparib-resistant SNU-484, SNU-601, and SNU-668, which showed cross-resistance to cisplatin. Olaparib-resistant cells showed tyrosyl-DNA phosphodiesterase 1 (TDP1) downregulation with higher topoisomerase 1 (TOP1) activity, which is a target of irinotecan. These changes of TOP1 and TDP1 in olaparib-resistant cells was confirmed as the underlying mechanism for increased irinotecan sensitivity through manipulated gene expression of TOP1 and TDP1 by specific plasmid transfection and siRNA. The patient-derived xenograft model established from the patient who acquired resistance to olaparib with BRCA2 mutation showed increased sensitivity in irinotecan. In conclusion, the carryover effects of olaparib to improve antitumor effect of subsequent irinotecan were demonstrated. These effects should be considered when determining the subsequent therapy with olaparib.

A functional regulatory variant of MYH3 influences muscle fiber-type composition and intramuscular fat content in pigs

Muscle development and lipid accumulation in muscle critically affect meat quality of livestock. However, the genetic factors underlying myofiber-type specification and intramuscular fat (IMF) accumulation remain to be elucidated. Using two independent intercrosses between Western commercial breeds and Korean native pigs (KNPs) and a joint linkage-linkage disequilibrium analysis, we identified a 488.1-kb region on porcine chromosome 12 that affects both reddish meat color (a*) and IMF. In this critical region, only the MYH3 gene, encoding myosin heavy chain 3, was found to be preferentially overexpressed in the skeletal muscle of KNPs. Subsequently, MYH3-transgenic mice demonstrated that this gene controls both myofiber-type specification and adipogenesis in skeletal muscle. We discovered a structural variant in the promotor/regulatory region of MYH3 for which Q allele carriers exhibited significantly higher values of a* and IMF than q allele carriers. Furthermore, chromatin immunoprecipitation and cotransfection assays showed that the structural variant in the 5′-flanking region of MYH3 abrogated the binding of the myogenic regulatory factors (MYF5, MYOD, MYOG, and MRF4). The allele distribution of MYH3 among pig populations worldwide indicated that the MYH3 Q allele is of Asian origin and likely predates domestication. In conclusion, we identified a functional regulatory sequence variant in porcine MYH3 that provides novel insights into the genetic basis of the regulation of myofiber type ratios and associated changes in IMF in pigs. The MYH3 variant can play an important role in improving pork quality in current breeding programs.info:eu-repo/semantics/publishedVersio

A Stochastic and Optimized Energy Efficient Clustering Protocol for Wireless Sensor Networks

Wireless sensor network consisting of a large number of small sensors of low-power transceiver is effective for gathering data in a variety of environments. Since the network is built with low-cost sensor nodes of limited battery power, it is a challenging task to design an efficient routing scheme maximizing the network lifetime. In this paper, we propose a new clustering protocol reducing the energy taken for routing, and thus extending the network lifetime. The proposed scheme is based on a newly developed model of optimal number of clusters in the network with which the energy consumption can be minimized. It also includes a method of cluster-head rotation inside each cluster, which avoids the clustering operation during normal operation and evenly distributes the load among the nodes. The performance of the proposed scheme is compared with the clustering-based routing protocols, Low-Energy Adaptive Clustering Hierarchy (LEACH), LEACH-Centralized (LEACH-C), and Adaptive and Energy Efficient Clustering (AEEC) algorithm. Simulation results show that it significantly reduces energy consumption and improves network lifetime. It is thus expected to be effective for large-scale semantic sensor web

Dynamic Load Balancing of Software-Defined Networking Based on Genetic-Ant Colony Optimization

Load Balancing (LB) is one of the most important tasks required to maximize network performance, scalability and robustness. Nowadays, with the emergence of Software-Defined Networking (SDN), LB for SDN has become a very important issue. SDN decouples the control plane from the data forwarding plane to implement centralized control of the whole network. LB assigns the network traffic to the resources in such a way that no one resource is overloaded and therefore the overall performance is maximized. The Ant Colony Optimization (ACO) algorithm has been recognized to be effective for LB of SDN among several existing optimization algorithms. The convergence latency and searching optimal solution are the key criteria of ACO. In this paper, a novel dynamic LB scheme that integrates genetic algorithm (GA) with ACO for further enhancing the performance of SDN is proposed. It capitalizes the merit of fast global search of GA and efficient search of an optimal solution of ACO. Computer simulation results show that the proposed scheme substantially improves the Round Robin and ACO algorithm in terms of the rate of searching optimal path, round trip time, and packet loss rate

Packet Scheduling for Multiple-Switch Software-Defined Networking in Edge Computing Environment

Software-defined networking (SDN) decouples the control plane and data forwarding plane to overcome the limitations of traditional networking infrastructure. Among several communication protocols employed for SDN, OpenFlow is most widely used for the communication between the controller and switch. In this paper two packet scheduling schemes, FCFS-Pushout (FCFS-PO) and FCFS-Pushout-Priority (FCFS-PO-P), are proposed to effectively handle the overload issue of multiple-switch SDN targeting the edge computing environment. Analytical models on their operations are developed, and extensive experiment based on a testbed is carried out to evaluate the schemes. They reveal that both of them are better than the typical FCFS-Block (FCFS-BL) scheduling algorithm in terms of packet wait time. Furthermore, FCFS-PO-P is found to be more effective than FCFS-PO in the edge computing environment