A peer-to-peer collaboration framework for multi-sensor data fusion

Lee, Panho; Jayasumana, Anura P.; Bandara, H. M. N. Dilum; Lim, Sanghun; Chandrasekar, V.

doi:10.1016/j.jnca.2011.12.005

Cited by 11 publications

(7 citation statements)

References 25 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Unstructured P2P systems are based on random overlays where resources are advertised, discovered, and/or selected by sending messages through flooding or random walks. Flooding can be used to advertise RSs and/or to select resources on the fly using multi-attribute queries [3]. Either way, all the nodes/queries can get to know about all the resources in the system, which enables the most suitable set of resources to collaborate.…”

Section: Unstructured-overlay-based Solutionsmentioning

confidence: 99%

“…We consider four representative applications to illustrate the salient features and characteristics of collaborative P2P systems. First is Collaborative Adaptive Sensing of the Atmosphere (CASA) [1,3], an emerging DCAS system based on a dense network of weather radars that collaborate in real time to detect hazardous atmospheric conditions such as tornados and severe storms. CASA also employs many small sensors such as pressure sensors and rain gauges to further enhance the detectability and prediction accuracy of weather events.…”

Section: Introductionmentioning

confidence: 99%

“…CASA also employs many small sensors such as pressure sensors and rain gauges to further enhance the detectability and prediction accuracy of weather events. Collaborative P2P data fusion provides an attractive implementation choice for CASA real-time radar data fusion [3], wherein data are constantly being generated, processed, and pushed and pulled among groups of heterogeneous radars, sensors, storage, and processing nodes. The group of radars, sensors, processing, and storage elements involved in tracking a particular weather event may continue to change as the weather event migrates in both time and space.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Collaborative applications over peer-to-peer systems–challenges and solutions

Bandara

Jayasumana

2012

Peer-to-Peer Netw. Appl.

Self Cite

View full text Add to dashboard Cite

Emerging collaborative Peer-to-Peer (P2P) systems require discovery and utilization of diverse, multiattribute, distributed, and dynamic groups of resources to achieve greater tasks beyond conventional file and processor cycle sharing. Collaborations involving application specific resources and dynamic quality of service goals are stressing current P2P architectures. Salient features and desirable characteristics of collaborative P2P systems are highlighted. Resource advertising, selecting, matching, and binding, the critical phases in these systems, and their associated challenges are reviewed using examples from distributed collaborative adaptive sensing systems, cloud computing, and mobile social networks. State-of-the-art resource discovery/aggregation solutions are compared with respect to their architecture, lookup overhead, load balancing, etc., to determine their ability to meet the goals and challenges of each critical phase. Incentives, trust, privacy, and security issues are also discussed, as they will ultimately determine the success of a collaborative P2P system. Open issues and research opportunities that are essential to achieve the true potential of collaborative P2P systems are discussed. The final publication is available at www.springerlink.com computing [6], based on underutilized computing resources in homes or businesses for example, targets issues such as centralized data, privacy, proprietary applications, and cascading failures in modern clouds. Certain applications also benefit from a mixture of dedicated and voluntary cloud resources [7][8]. A collaborative P2P system is the core of such a multi-site or community-cloud system that interconnects dedicated/voluntary resources while dealing with rapid scalability and resource fluctuations. We refer to such systems as P2P clouds. Third application, Global Environment for Network Innovations (GENI) [9], is a collaborative and exploratory platform for discoveries and innovation. GENI allows users to aggregate diverse resources (e.g., processing, networks, sensors, actuators, and software) from multiple administrative domains for a common task. A collaborative P2P system is a natural fit for GENI because of its distributed, dynamic, heterogeneous, and collaborative nature. Fourth, the value of social networks can be enhanced by allowing users to share diverse resources available in their mobile devices [2]. For example, a person with a basic mobile phone could connect to a friend's smart phone with GPS capability to locate a nearby ATM. In another example, a group sharing their holiday experiences in a coffee shop could use one member's projection phone to show pictures from others' mobiles/tablets or stream videos from their home servers. Moreover, in large social gatherings such as carnivals, sports events, or political rallies, users' mobile devices can be used to share hot deals, comments, videos, or vote for a certain resolution without relying on a network infrastructure. Such applications are already emerging under the domain of opport...

show abstract

Section: Unstructured-overlay-based Solutionsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Collaborative applications over peer-to-peer systems–challenges and solutions

Bandara

Jayasumana

2012

Peer-to-Peer Netw. Appl.

Self Cite

View full text Add to dashboard Cite

show abstract

“…DCAS systems rely on a multitude of heterogeneous and distributed sensors, ranging from mote-based, resource-limited, low-power, and task-specific wireless sensor nodes to resourcerich, high-power, and multipurpose sensors such as radars. Data generated by these sensors are processed using distributed groups of computational, storage, and bandwidth resources [2]. A key defining characteristic of DCAS systems is data pull where end-user information needs determine how and what group(s) of system resources are utilized to generate and process the required data [3].…”

Section: Introductionmentioning

confidence: 99%

“…A key defining characteristic of DCAS systems is data pull where end-user information needs determine how and what group(s) of system resources are utilized to generate and process the required data [3]. Collaborative Adaptive Sensing of the Atmosphere (CASA) [1][2][3]] is a DCAS system based on a dense network of low-cost weather radars that collaborate in real time to detect and track hazardous, localized weather phenomena such as tornados and severe storms.…”

Section: Introductionmentioning

confidence: 99%

Radar networking in Collaborative Adaptive Sensing of Atmosphere: State of the art and research challenges

Bandara

Jayasuman

Zink

2012

2012 IEEE Globecom Workshops

View full text Add to dashboard Cite

Collaborative Adaptive Sensing of the Atmosphere (CASA), in which a network of small weather radars collaborates in real time, has emerged as the preferred alternative for accurately detecting and tracking hazardous weather phenomena such as tornados. We address data transport and multi-sensor data fusion solutions proposed in context of CASA, focusing on their ability to support streaming and data pull modes of radar data access. How CASA can leverage emerging technologies, such as Named Data Networking (NDN), virtualization, and cloud computing to meet the performance, quality of service, and resource utilization requirements in a scalable manner are addressed. Open issues and research challenges for realizing the true potential of large-scale CASA networks are considered.

show abstract

An efficient and distributed file search in unstructured peer-to-peer networks

Shojafar

Abawajy

Delkhah

et al. 2013

Peer-to-Peer Netw. Appl.

View full text Add to dashboard Cite

Peer-to-peer (P2P) networks are gaining increased attention from both the scientific community and the larger Internet user community. Data retrieval algorithms lie at the center of P2P networks, and this paper addresses the problem of efficiently searching for files in unstructured P2P systems. We propose an Improved Adaptive Probabilistic Search (IAPS) algorithm that is fully distributed and bandwidth efficient. IAPS uses ant-colony optimization and takes file types into consideration in order to search for file container nodes with a high probability of success. We have performed extensive simulations to study the performance of IAPS, and we compare it with the Random Walk and Adaptive Probabilistic Search algorithms. Our experimental results show that IAPS achieves high success rates, high response rates, and significant message reduction

show abstract

A peer-to-peer collaboration framework for multi-sensor data fusion

Cited by 11 publications

References 25 publications

Collaborative applications over peer-to-peer systems–challenges and solutions

Collaborative applications over peer-to-peer systems–challenges and solutions

Radar networking in Collaborative Adaptive Sensing of Atmosphere: State of the art and research challenges

An efficient and distributed file search in unstructured peer-to-peer networks

Contact Info

Product

Resources

About