5,480 research outputs found
Energy Efficient Rectangular Indexing for Mobile Peer-to-Peer Environment
Now a days in wireless environment there are many challenges. One of them which is need to be addressed in mobile Peer-to-Peer environment is getting the information of interest quickly and efficiently. Wherein whenever the node tries to get the desired data it has to wait too long or have to contact to unnecessary nodes which are not having their data of interest. This causes the node to waste the limited power resources and incurs more cost in terms of energy wastage. Here we proposed an energy efficient rectangular indexing called PMBR (Peer-to-Peer Minimum Bounding Rectangle) which allows the user to get the information of interest in energy efficient manner. We proposed algorithms namely PMBR_DSS, PMBR_HB and PMBR_CP and processed Nearest Neighbor & Range type queries. The experimental results carried out shows that the proposed algorithm PMBR_CP provides the efficient, quick and assured access to information of interest by saving the scarce power resources
Regional Data Archiving and Management for Northeast Illinois
This project studies the feasibility and implementation options for establishing a regional data archiving system to help monitor
and manage traffic operations and planning for the northeastern Illinois region. It aims to provide a clear guidance to the
regional transportation agencies, from both technical and business perspectives, about building such a comprehensive
transportation information system. Several implementation alternatives are identified and analyzed. This research is carried
out in three phases.
In the first phase, existing documents related to ITS deployments in the broader Chicago area are summarized, and a
thorough review is conducted of similar systems across the country. Various stakeholders are interviewed to collect
information on all data elements that they store, including the format, system, and granularity. Their perception of a data
archive system, such as potential benefits and costs, is also surveyed. In the second phase, a conceptual design of the
database is developed. This conceptual design includes system architecture, functional modules, user interfaces, and
examples of usage. In the last phase, the possible business models for the archive system to sustain itself are reviewed. We
estimate initial capital and recurring operational/maintenance costs for the system based on realistic information on the
hardware, software, labor, and resource requirements. We also identify possible revenue opportunities.
A few implementation options for the archive system are summarized in this report; namely:
1. System hosted by a partnering agency
2. System contracted to a university
3. System contracted to a national laboratory
4. System outsourced to a service provider
The costs, advantages and disadvantages for each of these recommended options are also provided.ICT-R27-22published or submitted for publicationis peer reviewe
Sequencing geographical data for efficient query processing on air in mobile computing.
Three cost models are derived to measure Data Broadcast Wait (DBW), Data Access Time in the multiplexing scheme (ATDataMul) where both data and indices are broadcast in the same channel, and Data Access Time in the separate channel scheme (ATDataSep) where data and indices are broadcast in two separate channels. Hypergraph representations are used to represent the spatial relationships of both point data and graph data. The broadcast data placement problem is then converted to the graph layout problem. A framework for classifying ordering heuristics for different types of geographical data is presented. A low-polynomial cost approximation graph layout method is used to solve the DBW minimization problem. Based on the proven monotonic relationship between ATData Sep and DBW, the same approximation method is also used for AT DataSep optimization. A novel method is developed to optimize ATDataMul. Experiments using both synthetic and real data are conducted to evaluate the performance of the ordering heuristics and optimization methods. The results show that R-Tree traversal ordering heuristic in conjunction with the optimization methods is effective for sequencing point data for spatial range query processing, while graph partition tree traversal ordering heuristic in conjunction with the optimization methods is suitable for sequencing graph data for network path query processing over air.Geographical data broadcasting is suitable for many large scale dissemination-based applications due to its independence of number of users, and thus it can serve as an important part of intelligent information infrastructures for modern cities. In broadcast systems, query response time is greatly affected by the order in which data items are being broadcast. However, existing broadcast ordering techniques are not suitable for geographical data because of the multi-dimension and rich semantics of geographical data. This research develops cost models and methods for placing geographical data items in a broadcast channel based on their spatial semantics to reduce response time and energy consumption for processing spatial queries on point data and graph data
Query Processing In Location-based Services
With the advances in wireless communication technology and advanced positioning systems, a variety of Location-Based Services (LBS) become available to the public. Mobile users can issue location-based queries to probe their surrounding environments. One important type of query in LBS is moving monitoring queries over mobile objects. Due to the high frequency in location updates and the expensive cost of continuous query processing, server computation capacity and wireless communication bandwidth are the two limiting factors for large-scale deployment of moving object database systems. To address both of the scalability factors, distributed computing has been considered. These schemes enable moving objects to participate as a peer in query processing to substantially reduce the demand on server computation, and wireless communications associated with location updates. In the first part of this dissertation, we propose a distributed framework to process moving monitoring queries over moving objects in a spatial network environment. In the second part of this dissertation, in order to reduce the communication cost, we leverage both on-demand data access and periodic broadcast to design a new hybrid distributed solution for moving monitoring queries in an open space environment. Location-based services make our daily life more convenient. However, to receive the services, one has to reveal his/her location and query information when issuing locationbased queries. This could lead to privacy breach if these personal information are possessed by some untrusted parties. In the third part of this dissertation, we introduce a new privacy protection measure called query l-diversity, and provide two cloaking algorithms to achieve both location kanonymity and query l-diversity to better protect user privacy. In the fourth part of this dissertation, we design a hybrid three-tier architecture to help reduce privacy exposure. In the fifth part of this dissertation, we propose to use Road Network Embedding technique to process privacy protected queries
Dynamic Geospatial Spectrum Modelling: Taxonomy, Options and Consequences
Much of the research in Dynamic Spectrum Access (DSA) has focused on opportunistic access in the temporal domain. While this has been quite useful in establishing the technical feasibility of DSA systems, it has missed large sections of the overall DSA problem space. In this paper, we argue that the spatio-temporal operating context of specific environments matters to the selection of the appropriate technology for learning context information. We identify twelve potential operating environments and compare four context awareness approaches (on-board sensing, databases, sensor networks, and cooperative sharing) for these environments. Since our point of view is overall system cost and efficiency, this analysis has utility for those regulators whose objectives are reducing system costs and enhancing system efficiency. We conclude that regulators should pay attention to the operating environment of DSA systems when determining which approaches to context learning to encourage
Tracking Human Mobility using WiFi signals
We study six months of human mobility data, including WiFi and GPS traces
recorded with high temporal resolution, and find that time series of WiFi scans
contain a strong latent location signal. In fact, due to inherent stability and
low entropy of human mobility, it is possible to assign location to WiFi access
points based on a very small number of GPS samples and then use these access
points as location beacons. Using just one GPS observation per day per person
allows us to estimate the location of, and subsequently use, WiFi access points
to account for 80\% of mobility across a population. These results reveal a
great opportunity for using ubiquitous WiFi routers for high-resolution outdoor
positioning, but also significant privacy implications of such side-channel
location tracking
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