Research Papers - Dept of Computer Systems Engineering

Permanent URI for this collection https://rda.sliit.lk/handle/123456789/1253

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Subject: search.filters.subject.algorithm

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    An algorithm for labeling topological maps to represent point of interest for vision impaired navigation
    (IEEE, 2015-10-13) Jayakody, A; Murray, I; Herrmann, J
    Navigation in indoor environments is highly challenging for both vision impaired and sighted people, particularly in unknown environments visited for the first time. Several solutions have been implemented and proposed to deal with this challenge. Although some of them have shown to be useful in real scenarios, each solution involves a significant deployment effort or describes objects in a manner that is unfamiliar or incomprehensible to an individual with severe blindness. This paper presents a model of adding informational point of interest to the typical indoor topological map; with particular attention to the semantic labels of the different type of indoor places and proposes a simple way to include the tags to build the topological map. Using this POI and the semantic information, the system determines the user's path, locates possible obstacles on that route, and offers navigation information to assist vision impaired navigation.
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    An adaptive routing algorithm for Cognitive Packet Network infrastructure based on neural networks
    (IEEE, 2011-08-16) Madubashitha, D. K. D; Wijesinghe, W. M. S. S; Kamaladiwela, K. A. S. R; Ranaweera, M. G. P; Wijekoon, J; Abeygunawardhana, P. K. W
    This paper examines the possibility of introducing an intelligent routing protocol to the Internet, based on the Cognitive Packet Network (CPN) architecture with respect to the Quality of Service (QoS) delivered to the end users. In the present with increasing populations of countries it is clear that present infrastructure does not hold the sufficient capacity to deliver the expected level of service to the end users. Since there is an eminent need for a solution for improving the QoS in the Internet, this research focuses to provide a new network architecture which would improve the QoS, provide reliable and efficient service which can fulfill the ever growing Internet usage demand. This is achieved through a new network architecture known as CPN which is based on the basis of providing the best and user desired QoS. The main underlying technology behind the CPN will be a neural network. The neural network will be learning the changes in the network and adapt to the situation through the knowledge gathered. The packets will collectively learn about the network thus the load on the routers will be minimized. This mechanism completely replaces the need of a routing table thus making routing far more efficient when comparing to current routing protocols like Open Shortest Path First (OSPF). Final outcome of the research is coming to the conclusion that the future of the Internet is with the neural network based intelligent, dynamically adapting and learning CPN infrastructure instead of current packet switched network.
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    PublicationEmbargo
    An adaptive routing algorithm for Cognitive Packet Network infrastructure based on neural networks
    (IEEE, 2011-08-16) Madubashitha, D. K. D; Wijesinghe, W. M. S. S; Kamaladiwela, K. A. S. R; Ranaweera, M. G. P; Wijekoon, J; Abeygunawardhana, P. K. W
    This paper examines the possibility of introducing an intelligent routing protocol to the Internet, based on the Cognitive Packet Network (CPN) architecture with respect to the Quality of Service (QoS) delivered to the end users. In the present with increasing populations of countries it is clear that present infrastructure does not hold the sufficient capacity to deliver the expected level of service to the end users. Since there is an eminent need for a solution for improving the QoS in the Internet, this research focuses to provide a new network architecture which would improve the QoS, provide reliable and efficient service which can fulfill the ever growing Internet usage demand. This is achieved through a new network architecture known as CPN which is based on the basis of providing the best and user desired QoS. The main underlying technology behind the CPN will be a neural network. The neural network will be learning the changes in the network and adapt to the situation through the knowledge gathered. The packets will collectively learn about the network thus the load on the routers will be minimized. This mechanism completely replaces the need of a routing table thus making routing far more efficient when comparing to current routing protocols like Open Shortest Path First (OSPF). Final outcome of the research is coming to the conclusion that the future of the Internet is with the neural network based intelligent, dynamically adapting and learning CPN infrastructure instead of current packet switched network.