Liu, Ling

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Now showing 1 - 10 of 40
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    GeoCast: An Efficient Overlay System for Multicast Applications
    (Georgia Institute of Technology, 2009) Liu, Ling ; Pu, Calton ; Wang, Yuehua ; Zhang, Gong
    In this paper, we present GeoCast, a geographical location aware overlay network framework designed for providing efficient group communication services. GeoCast can be seen as an extension to the CAN network in the term of topology management and routing protocol. Geocast design has three important properties that attractive to group communication applications. First, it uses geographical mapping of nodes to regions to take advantage of the similarity between physical and network proximity. Second, a shortcut enabled geo-distance routing protocol is employed in GeoCast, which is more resilient than Chord-like or Pastry-like overlay networks due to the availability of multiple independent routing paths. Third and most importantly, a novel routing table management scheme is designed to allow the applications based on that have ability to manage their maintenance overhead in terms of network resource constrains.
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    Mobile Identity Management: Concepts, Issues, and Techniques
    (Georgia Institute of Technology, 2009) Li, Yun ; Liu, Ling
    This paper takes a systematic approach to examining the basic concepts, the research issues and the state of art technologies in mobile identity management. We examine the concept of mobile identity and argue that mobile identity should be defined by combining mobile device identity and mobile user identity in a location-aware computing environment. Thus mobile identity management deals with the management of user identity and mobile device identity, as well as the management of the linking of human, devices, and locations in different mobile contexts. Based on this understanding, we review the state of art research on techniques for mobile user identity support, techniques for mobile device identity support, techniques for linking of a human and her mobile devices, and techniques and issues of linking a mobile device and its location. The survey ends with a summary and an outlook of the future research and technology development trends.
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    A Patient-centric, Attribute-based, Source-verifiable Framework for Health Record Sharing
    (Georgia Institute of Technology, 2009) Mohan, Apurva ; Bauer, David ; Blough, Douglas M. ; Ahamad, Mustaque ; Bamba, Bhuvan ; Krishnan, Ramkumar ; Liu, Ling ; Mashima, Daisuke ; Palanisamy, Balaji
    The storage of health records in electronic format, and the wide-spread sharing of these records among different health care providers, have enormous potential benefits to the U.S. healthcare system. These benefits include both improving the quality of health care delivered to patients and reducing the costs of delivering that care. However, maintaining the security of electronic health record systems and the privacy of the information they contain is paramount to ensure that patients have confidence in the use of such systems. In this paper, we propose a framework for electronic health record sharing that is patient centric, i.e. it provides patients with substantial control over how their information is shared and with whom; provides for verifiability of original sources of health information and the integrity of the data; and permits fine-grained decisions about when data can be shared based on the use of attribute-based techniques for authorization and access control. We present the architecture of the framework, describe a prototype system we have built based on it, and demonstrate its use within a scenario involving emergency responders' access to health record information.
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    ITR/SI: Guarding the next internet frontier: countering denial of information
    (Georgia Institute of Technology, 2008-12-19) Ahamad, Mustaque ; Omiecinski, Edward ; Pu, Calton ; Mark, Leo ; Liu, Ling
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    A peer to peer approach to large scale information monitoring
    (Georgia Institute of Technology, 2008-10-31) Liu, Ling
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    A Energy Efficient Approach to Processing Spatial Alarms on Mobile Clients
    (Georgia Institute of Technology, 2008) Murugappan, Anand ; Liu, Ling
    Many on a daily basis use time based alarms. Spatial alarms extend the very same idea to location-based triggers, which are fired whenever a mobile user enters the spatial region of the location alarms. Spatial alarms provide critical capabilities for many mobile location based applications ranging from personal assistants, inventory tracking to industrial safety warning systems. In this paper we present an energy efficient framework for processing spatial alarms on mobile clients, while maintaining low computation and storage costs. Our approach to spatial alarms provides two systematic methods for minimizing energy consumption on mobile clients. First, we introduce the concept of safe distance to reduce the number of unnecessary mobile client wakeups for spatial alarm evaluation. This mechanism not only reduces the amount of unnecessary processing of the spatial alarms but also significantly minimizes the energy consumption on mobile clients, compared to periodic wakeups, while preserving the accuracy and timeliness of the spatial alarms. Second, we develop a suite of techniques for minimizing the number of location triggers to be checked for spatial alarm evaluation upon each wakeup. This further reduces the computation cost and energy expenditure on mobile clients. We evaluate the scalability and energy-efficiency of our approach using a road network simulator. Our client based framework for spatial alarms offers significant improvements on both system performance and battery lifetime of mobile clients, while maintaining high quality of spatial alarm services, especially compared to the conventional approach of periodic wakeup and checking all alarms upon wakeup.
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    Safe Region Techniques for Fast Spatial Alarm Evaluation
    (Georgia Institute of Technology, 2008) Bamba, Bhuvan ; Liu, Ling ; Iyengar, Arun ; Yu, Philip S.
    Spatial alarms are personalized location-based triggers installed by mobile users to serve as a reminder of a location of interest to be encountered in their future trips. Unlike continuous spatial queries, spatial alarms do not require immediate processing and periodic reevaluation upon installation. Thus, a critical challenge for efficient processing of spatial alarms is to determine when to evaluate each spatial alarm, while ensuring the demanding requirements of high accuracy and system scalability. In this paper, we compare alternative approaches for evaluation of spatial alarms: periodic evaluation, safe period-based processing and safe region-based processing. We argue that the safe region-based approach provides highly efficient processing of spatial alarms at the server. Furthermore, it reduces wireless communication costs and energy consumption on the client side by reducing the number of location updates to be transmitted to the server without sacrificing accuracy of spatial alarm evaluation. We develop safe region computation techniques based on different heuristics, namely, Maximum Perimeter Rectangular Safe Region (MPSR), Largest Component Rectangles Safe Region (LCSR) and Bitmap Encoded Safe Region (BSR) approach, and present an in-depth study on trade-offs involved in the selection of an appropriate safe region computation strategy. Our experimental evaluation shows that the best optimization strategy requires an approach which adapts to changing system load conditions and resource constraints, as none of the safe region computation techniques outperforms the others on all relevant evaluation metrics. Experimental evaluation also validates our conjecture that safe region-based processing offers close to optimal performance in terms of CPU load on the server and wireless communication costs at the mobile clients.
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    Efficient and Secure Search of Enterprise File Systems
    (Georgia Institute of Technology, 2007) Singh, Aameek ; Srivatsa, Mudhakar ; Liu, Ling
    With fast paced growth of enterprise data, quickly locating relevant content has become a critical IT capability. Research has shown that nearly 85% of enterprise data lies in flat filesystems [12] that allow multiple users and user groups with different access privileges to underlying data. Any search tool for such large scale systems needs to be efficient and yet cognizant of the access control semantics imposed by the underlying filesystem. Current multiuser enterprise search techniques use two disjoint search and access-control components by creating a single system-wide index and simply filtering search results for access control. This approach is ineffective as the index and query statistics subtly leak private information. The other available approach of using separate indices for each user is undesirable as it not only increases disk consumption due to shared files, but also increases the overheads of updating the indices whenever a file changes. We propose a distributed approach that couples search and access-control into a unified framework and provides secure multiuser search. Our scheme (logically) divides data into independent access-privileges based chunks, called access-control barrels (ACB). ACBs not only manage security but also improve overall efficiency as they can be indexed and searched in parallel by distributing them to multiple enterprise machines. We describe the architecture of ACBs based search framework and propose two optimization technique that ensure the scalability of our approach. We also discuss other useful features of our approach – seamless integration with desktop search and an extenstion to provide secure search in untrusted storage service provider environments. We validate our approach with a detailed evaluation using industry benchmarks and real datasets. Our initial experiments show secure search with 38% improved indexing efficiency and low overheads for ACB processing.
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    CubeCache: Efficient and Scalable Processing of OLAP Aggregation Queries in a Peer-to-Peer Network
    (Georgia Institute of Technology, 2007) Seshadri, Sangeetha ; Cooper, Brian F. ; Liu, Ling
    Peer to Peer (P2P) data sharing systems are emerging as a promising infrastructure for collaborative data sharing among multiple geographically distributed data centers within a large enterprise. This paper presents CubeCache, a peer-to-peer system for efficiently serving OLAP queries and data cube aggregations in a distributed data warehouse system. CubeCache combines multiple client caches into a single query processing and caching system. Compared to existing peer-to-peer systems the CubeCache solution has a number of unique features. First, we add a query processing layer to perform innetwork data aggregation over peer caches. Second, we introduce the concept of Query-Trails: a cache listing recent data requestors. Query-Trails make it easier to find caches that are likely to have data needed for a query. Third, we design a benefit measure that incorporates the 'rarity' of a chunk into the notion of benefit, allowing controlled replication of chunks in a system plagued by frequent node departures or failures. We report the results of analysis and an experimental study using simulations and an implemented prototype that shows the CubeCache solution reduces the server load, improves query throughput and reduces query latency for OLAP tasks.
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    PRIVACYGRID: Supporting Anonymous Location Queries in Mobile Environments
    (Georgia Institute of Technology, 2007) Bamba, Bhuvan ; Liu, Ling
    We present PRIVACYGRID − a framework for supporting anonymous location-based queries in mobile information delivery systems. The PRIVACYGRID framework offers three unique capabilities. First, we provide a location privacy preference profile model, called location P3P, which allows mobile users to explicitly define their preferred location privacy requirements in terms of both location hiding measures (e.g., location k-anonymity and location l-diversity) and location service quality measures (e.g., maximum spatial resolution and maximum temporal resolution). Second, we develop three fast and effective location cloaking algorithms for providing location k-anonymity and location l-diversity in a mobile environment. The Quad Grid cloaking algorithm is fast but has lower anonymization success rate. The dynamic bottom-up or top-down grid cloaking algorithms provide much higher anonymization success rate and yet are efficient in terms of both time complexity and maintenance cost. Finally, we discuss a hybrid approach that combines the topdown and bottom-up search of location cloaking regions to further lower the average anonymization time. In addition, we argue for incorporating temporal cloaking into the location cloaking process to further increase the success rate of location anonymization. We also discuss the PRIVACYGRID mechanisms for anonymous support of range queries. Our experimental evaluation shows that the PRIVACYGRID approach can provide optimal location anonymity as defined by per user location P3P without introducing significant performance penalties.