Abstract-We will show that ocean-reflected signals from the global positioning system (GPS) navigation satellite constellation can be detected from a low-earth orbiting satellite and that these signals show rough correlation with independent measurements of the sea winds. We will present waveforms of ocean-reflected GPS signals that have been detected using the experiment onboard the United Kingdom's Disaster Monitoring Constellation satellite and describe the processing methods used to obtain their delay and Doppler power distributions. The GPS bistatic radar experiment has made several raw data collections, and reflected GPS signals have been found on all attempts. The down linked data from an experiment has undergone extensive processing, and ocean-scattered signals have been mapped across a wide range of delay and Doppler space revealing characteristics which are known to be related to geophysical parameters such as surface roughness and wind speed. Here we will discuss the effects of integration time, reflection incidence angle and examine several delay-Doppler signal maps. The signals detected have been found to be in general agreement with an existing model (based on geometric optics) and with limited independent measurements of sea winds; a brief comparison is presented here. These results demonstrate that the concept of using bistatically reflected global navigation satellite systems signals from low earth orbit is a viable means of ocean remote sensing.

In unstructured peer‐to‐peer (P2P) networks, two autonomous peer nodes can be connected if users in those nodes are interested in each other's data. Owing to the similarity between P2P networks and social networks, where peer nodes can be regarded as people and connections can be regarded as relationships, social strategies are useful for improving the performance of resource discovery by self‐organizing autonomous peers on unstructured P2P networks. In this paper, we present an efficient social‐like peer‐to‐peer (ESLP) method for resource discovery by mimicking different human behaviours in social networks. ESLP has been simulated in a dynamic environment with a growing number of peer nodes. From the simulation results and analysis, ESLP achieved better performance than current methods. Copyright © 2008 John Wiley & Sons, Ltd.

This paper presents small world architecture for P2P networks (SWAN) for content discovery in multi-group P2P systems. A semi-structured P2P algorithm of SWAN is utilized to create and find long-range shortcuts toward remote peer groups. In SWAN, not every peer node needs to be connected to remote groups, but every peer node can easily find which peer nodes have external connections to a specific peer group. From our analysis and simulation, SWAN has the advantages of both structured and unstructured P2P networks and can achieve good performance in both stable and dynamic environments.Keywords: Peer-to-peer; Small world; Information search IntroductionMost early Internet applications are distributed using client/server architecture that has a series of drawbacks, such as performance bottlenecks and low fault tolerance. On the contrary, peer-to-peer (P2P) architecture does not rely on centralized servers to provide access to services and offers an appealing alternative to the client/server model, especially for large-scale distributed applications. This paper presents small world architecture for P2P networks (SWAN) for resource discovery and discovery in multi-group P2P systems. A semi-structured P2P algorithm of SWAN is used to create and discover long-range shortcuts between different peer groups, which can satisfy the following requirements of design:(1) Not every peer node needs to connect to other peer groups;(2) Each peer node needs to know or can easily find which peer nodes have external connections to which peer groups; 3 (3) External links to other peer groups need to be distributed within the peer group and cannot be centralized in one or a few peer nodes.The rest of paper is organized as follows: Section 2 discusses related work. Section 3 presents the SWAN algorithms. The small-world properties of SWAN are analysed in Section 4. The performance evaluation and simulations are given in Section 5 and Section 6, respectively. We conclude the work in Section 7. Related Work Resource Discovery in Peer-to-Peer NetworksExisting P2P solutions for resource discovery can be generally classified into two categories: structured and unstructured P2P systems. Distributed hash tables (DHTs) have become the dominant methodology for resource discovery in structured P2Pnetworks [5]. The observed problem of most DHTs is that the cost of maintaining a consistent distributed index is too high in dynamic environments [6]. Some structured P2P protocols (e.g. Kademlia [7]) are beginning to seek ways to save the cost of maintaining a consistent index. In contrast, unstructured P2P systems (e.g. Gnutella) do not control data placement and are more resilient in dynamic environments, but current unstructured P2P search techniques tend to either require high search overhead or generate massive network traffic.In contrast, SWAN uses a semi-structured P2P search method combining the techniques of both structured and unstructured search methods. SWAN does not strictly rely on DHTs. It can find the requested data inside and ...

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