The growing commercial interest in indoor locationbased services (ILBS) has spurred recent development of many indoor positioning techniques. Due to the absence of GPS (global positioning system) signal, many other signals have been proposed for indoor usage. Among them, Wi-Fi (802.11) emerges as a promising one due to the pervasive deployment of wireless LANs (WLANs). In particular, Wi-Fi fingerprinting has been attracting much attention recently because it does not require line-ofsight measurement of access points (APs) and achieves high applicability in complex indoor environment.This survey overviews recent advances on two major areas of Wi-Fi fingerprint localization: advanced localization techniques and efficient system deployment. Regarding advanced techniques to localize users, we present how to make use of temporal or spatial signal patterns, user collaboration, and motion sensors.Regarding efficient system deployment, we discuss recent advances on reducing offline labor-intensive survey, adapting to fingerprint changes, calibrating heterogeneous devices for signal collection, and achieving energy efficiency for smartphones. We study and compare the approaches through our deployment experiences, and discuss some future directions.

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Abstract-In traditional mobile streaming networks such as 3G cellular networks, all users pull streams from a server. Such pull model leads to high streaming cost and problem in system scalability. In this paper, we propose and investigate a fully distributed, scalable, and cost-effective protocol to distribute multimedia content to mobiles in a peer-to-peer manner. Our protocol, termed Collaborative Streaming among Mobiles (COSMOS), makes use of broadcasting and data sharing to achieve high performance (in terms of delay, cost fairness, stream continuity, etc.). In COSMOS, only a few peers pull video descriptions from base stations. Using a free broadcast channel (such as Wi-Fi and Bluetooth), they share the streams to nearby neighbors. As a result, COSMOS greatly reduces the streaming cost and cellular bandwidth requirement. Furthermore, as video streams are supplied by multiple peers, COSMOS is robust to peer failure. Since broadcasting is used to distribute video data, COSMOS is highly scalable to large number of users. In COSMOS, peers autonomously determine whether to broadcast packets or not in order to efficiently use of the channel bandwidth. By taking turns to pull descriptions, peers can effectively share, and hence substantially reduce, streaming cost. As broadcast scope is small and peers can often obtain a number of streams from its neighbors, COSMOS achieves low delay and excellent stream continuity.

The delivery of quality video service often requires high bandwidth with low delay or cost in network transmission. Current routing protocols such as those used in the Internet are mainly based on the single-path approach (e.g., the shortest-path routing). This approach cannot meet the end-to-end bandwidth requirement when the video is streamed over bandwidth-limited networks. In order to overcome this limitation, we propose multipath routing, where the video takes multiple paths to reach its destination(s), thereby increasing the aggregate throughput. We consider both unicast (point-to-point) and multicast scenarios. For unicast, we present an efficient multipath heuristic (of complexity (3)), which achieves high bandwidth with low delay. Given a set of path lengths, we then present and prove a simple data scheduling algorithm as implemented at the server, which achieves the theoretical minimum end-to-end delay. For a network with unitcapacity links, the algorithm, when combined with disjoint-path routing, offers an exact and efficient solution to meet a bandwidth requirement with minimum delay. For multicast, we study the construction of multiple trees for layered video to satisfy the user bandwidth requirements. We propose two efficient heuristics on how such trees can be constructed so as to minimize the cost of their aggregation subject to a delay constraint.