Spiralchord: a space-filling curve based location awareness, cross-layering P2P file sharing system in WMNs

The common characteristics of peer-to-peer （P2P） overlay networks and wireless multi-hop network, such as self-organization, decentralization, hop-by-hop message transmission mode and high degree of dynamicity, lead to research of operating wired P2P applications on wireless multi-hop networks. Wireless mesh network （WMN） as a relative static multi-hop wireless network which is extended from Ad-Hoc networks, has become one of the key technologies for providing increased network coverage of Internet infrastructures. This paper investigates the problem of enabling P2P file sharing in WMNs. A special chord algorithm--spiralchord is proposed to address the major problem in wireless file sharing system how to efficiently find resources currently available. Spiralchord put forward an identifier （ID） assignment technique based on spiral space-filling curve to integrate location-awareness with cross-layering. Location awareness aims at alleviating the mismatch of physical network topology and overlay network topology, and requires close-by IDs in logical ring of neighboring peers, while cross-layering aims at speeding up resource lookup operations, requires faraway IDs of neighboring peers. Spiralchord uses spiral curve to assign peers＇ IDs which meet the contradictory requirements of location-awareness and cross-layering. The simulation results show spiralchord is effective in reducing message overhead, and increasing lookup performance with respect to basic chord.

Location-Aware Personalized Traveler Recommender System(LAPTA)Using Collaborative Filtering KNN

Many tourists who travel to explore different cultures and cities worldwide aim to find the best tourist sites,accommodation,and food according to their interests.This objective makes it harder for tourists to decide and plan where to go and what to do.Aside from hiring a local guide,an option which is beyond most travelers’budgets,the majority of sojourners nowadays use mobile devices to search for or recommend interesting sites on the basis of user reviews.Therefore,this work utilizes the prevalent recommender systems and mobile app technologies to overcome this issue.Accordingly,this study proposes location-aware personalized traveler assistance(LAPTA),a system which integrates user preferences and the global positioning system(GPS)to generate personalized and location-aware recommendations.That integration will enable the enhanced recommendation of the developed scheme relative to those from the traditional recommender systems used in customer ratings.Specifically,LAPTA separates the data obtained from Google locations into name and category tags.After the data separation,the system fetches the keywords from the user’s input according to the user’s past research behavior.The proposed system uses the K-Nearest algorithm to match the name and category tags with the user’s input to generate personalized suggestions.The system also provides suggestions on the basis of nearby popular attractions using the Google point of interest feature to enhance system usability.The experimental results showed that LAPTA could provide more reliable and accurate recommendations compared to the reviewed recommendation applications.

Quantitative estimates of collective geo-tagged human activities in response to typhoon Hato using location-aware big data

Location-aware big data from social media have been widely used to quantitatively characterize natural disasters and disaster-induced losses.It is not clear how human activities collectively respond to a disaster.In this study,we examined the collective human activities in response to Typhoon Hato at multi spatial scales using aggregated location request data.We proposed a Multilevel Abrupt Changes Detection(MACD)methodological framework to detect and characterize the abrupt changes in location requests in response to Typhoon Hato.Results show that,at the grid level,most anomaly grids were located within a radius of 53 km around the typhoon trajectory.At the city level,there are significant spatial difference in terms of the human activity recovery duration(230 h on average).At the subnational level,the absolute magnitude of abrupt location request changes is strongly correlated with the typhoon-induced economic losses and the population affected.