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Every human being has predefined movement in their regular social life. This predefined movement of user is very much useful in cellular network. Using supervise learning methods we can able to find out mobility patterns of mobile users in cellular network, which is useful to divide mobile users in various categories. Based on these categories we can develop algorithms which can help cellular network for reducing location management cost (Location Update cost + Paging Cost). In this paper, Apriori algorithm is used for creating dynamic location area for mobile users using mobility log of mobile users. The performance of the method has been verified for dynamic location area creation by considering different mobility logs of mobile users by taking different minimum support in Apriori algorithm. The simulation has achieved an average of 80% minimum support can be used to create dynamic location area for mobile users and 60%, 40% and 20% minimum support work as an adaptive search for mobile users.

Delay Tolerant Networks (DTNs) where the node connectivity is opportunistic and end-to-end path between any pair of source and destination is not guaranteed most of the time. Hence the messages are transferred from source to destination via intermediate nodes on hop to hop basis using store-carry-forward paradigm. Due to quick advancement in hand held devices such as smart phone and laptop with support of wireless communication interface carried by human being, it is possible in coming days to use DTNs for message dissemination without setting up infrastructure. The routing task becomes challenging in DTNs due to intermittent network connectivity and the connection opportunity arises only when node comes in transmission range of each other. The performance of the routing protocols depend on the selection of appropriate relay node which can deliver the message to final destination in case of source and destination do not meet at all. Many social characteristics are exhibited by the human being like friendship, community, similarity and centrality which can be exploited by the routing protocol in order to take the forwarding decisions. Literature shows that by using these characteristics, the performance of DTN routing protocols have been improved in terms of delivery probability. The existing routing schemes used community detection using aggregated contact duration and contact frequency which does not change over the time period. We propose community detection through Inter Contact Time (ICT) between node pair using power law distribution where the members of community are added and removed dynamically. We also considered single copy of each message in entire network to reduce the network overhead. The proposed routing protocol named Social Based Single Copy Routing (SBSCR) selects the suitable relay node from the community members only based on the social metrics such as similarity and friendship together. ICTs show power law nature in human mobility which is used to detect the community structure at each node. A node maintains its own community and social metrics such as similarity and friendship with other nodes. Whenever node has to select the relay node then it selects from its community with higher value of social metric. The simulations are conducted using ONE simulator on the real traces of campus and conference environments. SBSCR is compared with existing schemes and results show that it outperforms in terms of delivery probability and delivery delay with comparable overhead ratio.

Cotton is a very important crop, as India leads it in terms of production in the world; and also that a vast number of manpower is engaged in farming as well as post-harvest processing and management of different derivatives of it. Weather is crucial for the productivity of the crop. The challenges of climate change; availability of limited land and water for farming; lake of knowledge for good cultivation practices and judicious use of agricultural inputs with farmers are critical hindrances for improving productivity. This requires thorough research on land preparation and use, how to improve fertility of soil, good agronomic practices in lieu of variable climatic conditions, etc. All the talukas of the three districts of North Gujarat where cotton is cultivated have been selected purposively for this study. The effect of soil type, soil pH, soil organic carbon, phosphorous, potassium, precipitation and temperature were selected as independent factors. The yield of cotton crop has positive correlation with the selected parameters. The data sets were applied for analytical process to WEKA. The difference between average of predicted and actual yields of all talukas for high rainfall year 2013 was only 1.55 per cent. The difference between actual and predicted yield for the low temperature year (2015) in different talukas of all talukas was only 0.44 per cent.

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