Abstract-Smartphones can unfold the full potential of crowdsourcing, allowing users to transparently contribute to complex and novel problem solving. We present the intrinsic characteristics of smartphones, a taxonomy that classi es the emerging eld of mobile crowdsourcing and three in-house applications that optimize location-based search and similarity services over data generated by a crowd: (i) SmartTrace + enables similarity matching between a given pattern and the trajectories of smartphone users, keeping the target trajectories private; (ii) Crowdcast enables location-based interaction by ef ciently calculating the k nearest neighbors for each user at all times; (iii) SmartP2P optimizes energy, time and recall of search in a mobile social community for objects generated by a crowd. We show how these applications can be deployed on SmartLab, a novel cloud of 40+ Android devices deployed at University of Cyprus, providing an open testbed that facilitates research and development of applications on smartphones at a massive scale.

One important problem in peer-to-peer (P2P) networks is searching and retrieving the correct information. However, existing searching mechanisms in pure peer-to-peer networks are inefficient due to the decentralized nature of such networks. We propose two mechanisms for information retrieval in pure peer-to-peer networks. The first, the modified Breadth-First-Search (BFS) mechanism, is an extension of the current Gnuttela protocol, allows searching with keywords, and is designed to minimize the number of messages that are needed to search the network. The second, the Intelligent Search mechanism, uses the past behavior of the P2P network to further improve the scalability of the search procedure. In this algorithm, each peer autonomously decides which of its peers are most likely to answer a given query. The algorithm is entirely distributed, and therefore scales well with the size of the network. We implemented our mechanisms as middleware platforms. To show the advantages of our mechanisms we present experimental results using the middleware implementation.

No abstract

One important problem in peer-to-peer (P2P) networks is searching and retrieving the correct information. However, existing searching mechanisms in pure peer-to-peer networks are inefficient due to the decentralized nature of such networks. We propose two mechanisms for information retrieval in pure peer-to-peer networks. The first, the modified Breadth-First-Search (BFS) mechanism, is an extension of the current Gnuttela protocol, allows searching with keywords, and is designed to minimize the number of messages that are needed to search the network. The second, the Intelligent Search mechanism, uses the past behavior of the P2P network to further improve the scalability of the search procedure. In this algorithm, each peer autonomously decides which of its peers are most likely to answer a given query. The algorithm is entirely distributed, and therefore scales well with the size of the network. We implemented our mechanisms as middleware platforms. To show the advantages of our mechanisms we present experimental results using the middleware implementation.

No abstract