Several sensor nodes in the wireless network collect the data rigorously which aids in many of the applications. The network with high and the consistent data load is the only requirement of the wireless sensor networks. Due to the limited sources of the network and the high data loads, networks may be affected by congestion. Congestion is a highly objectionable issue which leads to information loss and the deprived performance of the wireless sensor networks. In this paper, an adaptive cuckoo search based optimal rate adjustment (ACSRO) for the congestion avoidance and control is proposed. The rate adjustment regulates the share rate of the node to mitigate the congestion. The performance of the proposed rate optimization approach is evaluated using the evaluation metrics such as throughput, delay, normalized packet loss, normalized queue size, and congestion level. The results of the proposed rate optimization show that the congestion is compacted and the performance of the WSN is improved. Ó 2016 Faculty of Engineering, Alexandria University. Production and hosting by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

No abstract

No abstract

In our everyday lives we require information to accomplish daily tasks. Database is one of the most important sources of information. Database systems have been widely used in data storage and retrieval. However, to extract information from databases, we need to have some knowledge of database languages like SQL. But SQL has predefined structures and format, so it is hard for the non-expert users to formulate the desired query. To override this complexity, we have turned to natural language to retrieve information from database, which can be an ideal channel between a non-technical user and the application. But the application cannot understand natural language so an interface is required. This interface is capable of converting the user’s natural language query to an equivalent database language query. In this paper, we address the system architecture for translating a Hindi sentence in the form of an audio to an equivalent SQL query. The users don’t need to learn any formal query language; hence it’s easy to use for common people.

No abstract