2019 29th Annual Conference of the European Association for Education in Electrical and Information Engineering (EAEEIE), 2019
This paper presents the preliminary results of the THEASIS system which is under development for ... more This paper presents the preliminary results of the THEASIS system which is under development for early detection of wildfires in Greece. Firstly, the proposed system in terms of conceptual design, the early fire detection methodology as well as the main software modules are presented. Laboratory and small-scale experiments made in the University of Patras campus as well as in the Strofylia forest are presented. The concluding remarks are promising towards the development of an efficient system for early detection of wildfires.
Content distribution networks (CDNs) improve scalability and reliability, by replicating content ... more Content distribution networks (CDNs) improve scalability and reliability, by replicating content to the “edge” of the Internet. Apart from the pure networking issues of the CDNs relevant to the establishment of the infrastructure, some very crucial data management issues must be resolved to exploit the full potential of CDNs to reduce the “last mile” latencies. A very important issue is the selection of the content to be prefetched to the CDN servers. All the approaches developed so far, assume the existence of adequate content popularity statistics to drive the prefetch decisions. Such information though, is not always available, or it is extremely volatile, turning such methods problematic. To address this issue, we develop self-adaptive techniques to select the outsourced content in a CDN infrastructure, which requires no apriori knowledge of request statistics. We identify clusters of “correlated” Web pages in a site, called Web site communities, and make these communities the basic outsourcing unit. Through a detailed simulation environment, using both real and synthetic data, we show that the proposed techniques are very robust and effective in reducing the user-perceived latency, performing very close to an unfeasible, off-line policy, which has full knowledge of the content popularity.
2019 29th Annual Conference of the European Association for Education in Electrical and Information Engineering (EAEEIE), 2019
This paper presents the preliminary results of the THEASIS system which is under development for ... more This paper presents the preliminary results of the THEASIS system which is under development for early detection of wildfires in Greece. Firstly, the proposed system in terms of conceptual design, the early fire detection methodology as well as the main software modules are presented. Laboratory and small-scale experiments made in the University of Patras campus as well as in the Strofylia forest are presented. The concluding remarks are promising towards the development of an efficient system for early detection of wildfires.
Content distribution networks (CDNs) improve scalability and reliability, by replicating content ... more Content distribution networks (CDNs) improve scalability and reliability, by replicating content to the “edge” of the Internet. Apart from the pure networking issues of the CDNs relevant to the establishment of the infrastructure, some very crucial data management issues must be resolved to exploit the full potential of CDNs to reduce the “last mile” latencies. A very important issue is the selection of the content to be prefetched to the CDN servers. All the approaches developed so far, assume the existence of adequate content popularity statistics to drive the prefetch decisions. Such information though, is not always available, or it is extremely volatile, turning such methods problematic. To address this issue, we develop self-adaptive techniques to select the outsourced content in a CDN infrastructure, which requires no apriori knowledge of request statistics. We identify clusters of “correlated” Web pages in a site, called Web site communities, and make these communities the basic outsourcing unit. Through a detailed simulation environment, using both real and synthetic data, we show that the proposed techniques are very robust and effective in reducing the user-perceived latency, performing very close to an unfeasible, off-line policy, which has full knowledge of the content popularity.
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Papers by DIMITRIOS KATSAROS