For monitoring burst events in a kind of reactive wireless sensor networks (WSNs), a multipath routing protocol (MRP) based on dynamic clustering and ant colony optimization (ACO) is proposed.. Such an approach can maximize the network lifetime and reduce the energy consumption. An important attribute of WSNs is its limited power supply, and therefore in MRP, some metrics (such as energy consumption of communication among nodes, residual energy, path length) are considered as very important criteria while designing routing. Firstly, a cluster head (CH) is selected among nodes located in the event area according to some parameters, such as residual energy. Secondly, an improved ACO algorithm is applied in search for multiple paths between the CH and sink node. Finally, the CH dynamically chooses a route to transmit data with a probability that depends on many path metrics, such as energy consumption. The simulation results show that MRP can prolong the network lifetime, as well as balance energy consumption among nodes and reduce the average energy consumption effectively.

For monitoring burst events in a kind of reactive wireless sensor networks (WSNs), a multipath routing protocol (MRP) based on dynamic clustering and ant colony optimization (ACO) is proposed. Such an approach can maximize the network lifetime and reduce the energy consumption. An important attribute of WSNs is their limited power supply, and therefore some metrics (such as energy consumption of communication among nodes, residual energy, path length) were considered as very important criteria while designing routing in the MRP. Firstly, a cluster head (CH) is selected among nodes located in the event area according to some parameters, such as residual energy. Secondly, an improved ACO algorithm is applied in the search for multiple paths between the CH and sink node. Finally, the CH dynamically chooses a route to transmit data with a probability that depends on many path metrics, such as energy consumption. The simulation results show that MRP can prolong the network lifetime, as well as balance of energy consumption among nodes and reduce the average energy consumption effectively.

An investigation of the potential neuroprotective natural product constituents of the rhizomes of Typhonium giganteum led to the isolation of two new cerebrosides, typhonosides E (1) and F (2), along with 11 known analogues (3-13). The structures of compounds 1 and 2 were elucidated by spectroscopic data interpretation. The activity of these compounds against glutamate-induced cell apoptosis was investigated in PC12 cells. All compounds exhibited such activity, which was related to the length of the fatty acyl chain. Among them, longan cerebroside II (11), with the longest fatty acyl chain, showed the most potent protective effect in PC12 cells from glutamate injury, with an EC value of 2.5 μM. Moreover, at the molecular level, longan cerebroside II (11) downregulated the expression of caspase-9, caspase-3, and Bax, upregulated the expression of Bcl-2, and decreased the level of cytosolic cytochrome c in a concentration-dependent manner.

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These nodes have limited energy supply in wireless sensor networks. Thus energy consumption is the main concern while developing routing algorithm in wireless sensor networks. In this paper, we propose a multipath routing algorithm based on Rumor Routing, called EBMRR (Energy-Balance Multipath Rumor Routing), which is probabilistic approach that attempts to find multipath according to residual energy and energy usage at neighbors, and to evenly distribute the energy consumption over a large part of network by alternatively using one of the multiple paths to transmit data. We compare our proposed algorithm with the energy-efficient routing algorithm and traditional multi-path routing. Simulation results show that our proposed algorithm has higher energy efficiency and longer network lifetime.

Abstract:Cloud computing has competitive advantages-such as on-demand self-service, rapid computing, cost reduction, and almost unlimited storage-that have attracted extensive attention from both academia and industry in recent years. Some review works have been reported to summarize extant studies related to cloud computing, but few analyze these studies based on the citations. Co-citation analysis can provide scholars a strong support to identify the intellectual bases and leading edges of a specific field. In addition, advanced algorithms, which can directly affect the availability, efficiency, and security of cloud computing, are the key to conducting computing across various clouds. Motivated by these observations, we conduct a specific visualization review of the studies related to cloud computing algorithms using one mainstream co-citation analysis tool-CiteSpace. The visualization results detect the most influential studies, journals, countries, institutions, and authors on cloud computing algorithms and reveal the intellectual bases and focuses of cloud computing algorithms in the literature, providing guidance for interested researchers to make further studies on cloud computing algorithms.