| 1. |
- Hallberg, Josef, et al.
(författare)
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Enriched media-experience of sport events
- 2004
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Ingår i: Proceedings. - Los Alamitos, Calif : IEEE Communications Society. - 0769522580 ; , s. 2-9
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Konferensbidrag (refereegranskat)abstract
- This paper describes a system where Internet-enabled sensor technology was integrated into a context-aware platform to give viewers of sport events an enriched media experience. The system was developed as a proof of concept and was evaluated during real-life use at the Vasaloppet cross-country ski event. Using Bluetooth wireless ad-hoc networking and GPRS technology, sensor data was transmitted from contestants to the context-aware platform Alipes, which in turn presented the sport event viewer with a personalized, context-aware view. In this paper we discuss the system architecture and integration of components. The system was evaluated both from technical and user perspectives, where the evaluation results confirm our approach to be technically feasible and that the system provide an enriched media-experience for the majority of viewers.
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| 2. |
- Jayaraman, Prem, et al.
(författare)
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Dynamic situation modeling and reasoning under uncertainty
- 2009
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Ingår i: AUPC '09. - New York : ACM Digital Library. - 9781605586441 ; , s. 113-122
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Konferensbidrag (refereegranskat)abstract
- Reasoning under uncertainty is a key challenge in context aware pervasive systems. In this paper we propose R-CS a situation based context reasoning model that employs ranking technique to rank and order context attributes. Using the proposed ranking technique and available context information, we compute dynamic situation spaces (a collection of contextual attributes that best represent a real world situation) We also propose and incorporate multilevel hierarchical contextual regions into R-CS that enables situation reasoning to be based on one or more dependent context attributes. We present a theoretical approach to compute importance and relevance of newly discovered context attributes which are not defined within the situation space definition by employing the approach of investigating similar neighboring situation spaces. R-CS builds on context spaces theory, a context model based on situation reasoning. We have implemented the proposed algorithms/approaches into R-CS and have validated them by evaluating against context spaces reasoning model.
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| 3. |
- Jayaraman, Prem Prakash, et al.
(författare)
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Cost-efficient data collection approach using K-nearest neighbors in a 3D sensor network
- 2010
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Ingår i: 11th IEEE International Conference on Mobile Data Management, MDM 2010. - Piscataway, NJ : IEEE Communications Society. - 9781424470754 ; , s. 183-188
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Konferensbidrag (refereegranskat)abstract
- Sensor networks represent an important component of distributed infrastructure supplying raw data to various applications from military to healthcare. A key challenge is costefficient collection of distributed data streaming from those sensor networks. In this paper we propose the use of mobile data collectors that employ K-NN queries as a cost-efficient approach to collect data within the sensor network. We investigate a 3D sensor network and propose a cost-efficient 3D-KNN algorithm that uses minimal energy and communication overheads to compute k-nearest neighbors. The 3D-KNN algorithm uses a 3 dimensional plane rotation algorithm that maps sensor nodes on a 3D plane to a reference plane identified by the mobile data collector. We propose a cost-efficient KNN boundary estimation algorithm that computes KNN boundary based on network density. We also propose a neighbor prediction algorithm that uses distance, signal to noise ratio and mobile data collector's trajectory information to identify sensor nodes along the mobile data collector's path. We simulate the proposed 3D-KNN algorithm using GlomoSim and validate its cost efficiency by evaluating its energy efficiency and query latency. Lessons and results of extensive simulation conclude the paper
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| 4. |
- Jayaraman, Prem Prakash, et al.
(författare)
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Cost efficient data collection of sensory originated data using context-aware mobile devices
- 2008
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Ingår i: 2008 Ninth International Conference on Mobile Data Management workshops. - Piscataway, NJ : IEEE Communications Society. - 9781424444847 ; , s. 190-197
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Konferensbidrag (refereegranskat)abstract
- Sensory originated data collection and processing has always been a big challenge in wireless sensor networks (WSN). WSN represent a distributed producer of large amount of valuable data required by varied number of applications. In this paper we propose the use of context aware data mules (CADAMULE) as a solution for smart data collection within sensor networks. We present an extension to Context Spaces modelling theory by incorporating context discovery at runtime. This facilitates our system to discover new context attributes by looking into previous situations and events when pre-defined context is not sufficient for the reasoning process. We use this model as a base to provide contextual information to the mobile data mule whose spare capacity for communication and processing can be used to collect and process sensor data. The focus of the paper is to propose and evaluate a cost-efficient data collection technique which uses a cost formula computed from the context information obtained by the system. We validate our system by a simulation in which we try to reason out and identify the best and also the most cost efficient data mule. The context aware data mule negotiates with the sensor node collecting and delivering the data to the sink
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| 5. |
- Jayaraman, Prem Prakash, et al.
(författare)
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Coverage area computation on the run for efficient sensor data collection
- 2008
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Ingår i: New technologies, mobility and security. - Piscataway, NJ : IEEE Communications Society. - 9781424435470
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Konferensbidrag (refereegranskat)abstract
- Wireless sensor networks have emerged as a key area of research in recent years. With the dominance of ubiquitous and pervasive era of computing, these networks present a rich infrastructure for valuable information. In this paper we focus on efficient data collection in sensor networks by proposing an algorithm to compute a coverage (collection) area using smart mobile objects. The algorithm proposed computes a collection area dynamically covering nodes around the mobile objects current location. It uses a weighed graph technique to identify nodes from which data can be collected efficiently by the mobile object discarding the rest. The proposed algorithm computes the collection area using Voronoi Diagrams and Delaunay triangle. We validate the proposed algorithm by simulating the algorithm over a Bluetooth based sensor network. We also evaluate the algorithms efficiency to compute the coverage area by changing the mobile objects context parameters.
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| 6. |
- Jayaraman, Prem Prakash, et al.
(författare)
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Intelligent mobile data mules for cost-efficient sensor data collection
- 2010
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Ingår i: International Journal of Next-Generation Computing. - 2229-4678 .- 0976-5034. ; 1:1
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Tidskriftsartikel (refereegranskat)abstract
- Sensor networks represent an important component of distributed pervasive infrastructure. A key challenge facing sensor networks is cost-effcient collection of data streaming from these distributed data sites. In this paper, we present a mobile data mule-based sensor data collection approach employing K-Nearest Neighbours queries. We propose a novel 3D-KNN algorithm that dynamically computes nearest sensors spread within a 3D environment around the data mule. The 3D-KNN algorithm incorporates a novel boundary estimation and neighbour selection algorithm to compute the nearest neighbour set. Further, we propose a neighbour prediction algorithm that computes sensor locations within the vicinity of the data mules' trajectory. We simulate the proposed 3D-KNN algorithm using GlomoSim validating its cost-effciency by extensive evaluations. Results of our simulations conclude the paper.
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| 7. |
- Jayaraman, Prem Prakash, et al.
(författare)
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Intelligent processing of K-nearest neighbors queries using mobile data collectors in a location aware 3D wireless sensor network
- 2010
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Ingår i: Trends in applied intelligent systems. - Berlin : Encyclopedia of Global Archaeology/Springer Verlag. - 9783642130335 ; , s. 260-270
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Konferensbidrag (refereegranskat)abstract
- The increased acceptance of sensor networks into everyday pervasive environments has lead to the creation of abundant distributed resource constrained data sources. In this paper, we propose an intelligent mobile data collector-based K-Nearest Neighbor query processing algorithm namely 3D-KNN. The K-Nearest Neighbor query is an important class of query processing approach in sensor networks. The proposed algorithm is employed over a sensor network that is situated within a 3 dimensional space. We propose a novel boundary estimation algorithm which computes an energy efficient sensor boundary that encloses at least k nearest nodes. We then propose a 3D plane rotation algorithm that maps selected sensor nodes on different planes onto a reference plane and a novel k nearest neighbor selection algorithm based on node distance and signal-to-noise ratio parameters. We have implemented the 3D-KNN algorithm in GlomoSim and validate the proposed algorithm's cost efficiency by extensive performance evaluation over well defined system criteria
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| 8. |
- Jayaraman, Prem Prakash, et al.
(författare)
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On-the-fly situation composition within smart spaces
- 2009
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Ingår i: Smart Spaces and Next Generation Wired/Wireless Networking. - Berlin : Encyclopedia of Global Archaeology/Springer Verlag. - 9783642041884 ; , s. 52-65
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Konferensbidrag (refereegranskat)abstract
- Advances in pervasive computing systems have made smart computing spaces a reality. These smart spaces are sources of large amount of data required for context aware pervasive applications to function autonomously. In this paper we present a situation aware reasoning system that composes situations at runtime based on available information from the smart spaces. Our proposed system R-CS uses situation composition on-the-fly to compute temporal situations that best represent the real world situation (contextual information). Our proposed situation composition algorithm is dependent on underlying sensor data (hardware and software). These sensory data are prone to errors like inaccuracy, old data, data ambiguity etc. R-CS proposes algorithms that incorporate sensor data errors estimation techniques into our proposed dynamic situation composition based reasoning system. R-CS is built as an extension to Context Spaces, a fixed situation set based reasoning system. We implement R-CS dynamic situation composition algorithms over context spaces and validate our proposed R-CS model against context spaces' fixed situation reasoning model.
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| 9. |
- Jayaraman, Prem Prakash, et al.
(författare)
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Sensor data collection using heterogeneous mobile devices
- 2007
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Ingår i: 2007 IEEE International Conference on Pervasive Services. - Piscataway, NJ : IEEE Communications Society. - 1424413257 ; , s. 161-164
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Konferensbidrag (refereegranskat)abstract
- Data collection has always been a major challenge in sensor networks and various techniques have been proposed to enable efficient data collection. One such methodology is the use of mobile elements within the existing infrastructure to enable data collection. The paper proposes the use of existing mobile elements like mobile phones which have enough spare capacity to act as data carriers within a sensor network to carry sensor data. With advent of technology, mobile devices have become so powerful that they can work in a pervasive environment and make decisions based on context information like presence, location etc. Our proposal is an intelligent heterogeneous network in which the sensor nodes act as the data accumulators and the context-aware mobile phones act as data carriers of the sensed data. A framework that enables the mobile node and sensor node communication over Bluetooth is proposed and a p implementation is presented.
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| 10. |
- Jayaraman, Prem Prakash, et al.
(författare)
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Smart sensing and sensor data collection on the move for modelling intelligent environments
- 2008
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Ingår i: Next Generation Teletraffic and Wired/Wireless Advanced Networking. - Berlin : Encyclopedia of Global Archaeology/Springer Verlag. - 9783540854999 ; , s. 306-317
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Konferensbidrag (refereegranskat)abstract
- With advent of pervasive computing and considerable acceptance of sensor networks, smart sensing techniques and data collection have been topics of interest. This paper presents a smart sensing and data collection technique from sensor networks using context aware high powered mobile objects within the environment. The paper proposes CAM-R a context aware robot that can move within smart environments sensing new sensor sources and collecting sensory originated data efficiently. Based on these sensed data sources, we propose an extension to context spaces model that builds a virtual model of the intelligent environment. This intelligent environment model built using extended context spaces can be used by number of context aware applications to efficiently query and retrieve data from the sensor network using CAM-R based data collection approach. We also present a prototype implementation of CAM-R built using off-the-shelf hardware and a context based cost function used to compute data collection decisions. We validate our system by implementing the virtual modelling of the intelligent environment based on simulated input obtained from CAM-R and sensors. We also evaluate CAM-Rby simulating and comparing the energy spent by the sensor nodes during data collection process using our proposed approach and traditional fixed sink based approach.
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