Research Papers - Dept of Software Engineering

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Author: search.filters.author.Ratnayake, PHas files: Yes

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    PublicationEmbargo
    Smart Caring System for Ornamental Fish
    (IEEE, 2022-12-09) Fernando, S; Jayaweera, N; Pitawala, S; Kaushalya, R; Ratnayake, P; Siriwardana, S
    Ornamental Fish Industry continues to be one of the fastest growing sectors worldwide. Healthy fish production at aquariums requires intensive care and ensures a stable and an optimum production environment inside the fish tanks, which is a challenging task. Unfortunately, due to the limitations in fish industry, productivity of well-developed, healthy fish has drastically depreciated. Limited skills and knowledge of aquarists have been a challenging task which has led to inaccurate predictions on certain factors such as quantification and length of estimation, amounts and types of fish food and servicing the filters at proper time intervals. Existing aquariums depend on the experience and availability of the aquarists, which can be a challenging process in real life. Developing a system to regulate these major concerns is a prominent solution. This research is done to propose an automated method, with the help of several fish aquariums and existing research papers, to encounter the mentioned major concerns which affects the aquarists and other stakeholders.
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    PublicationOpen Access
    Disassortative Mixing and Systemic Rational Behaviour: How System Rationality Is Influenced by Topology and Placement in Networked Systems
    (MDPI, 2022-09-12) Kasthurirathna, D; Ratnayake, P; Piraveenan, M
    Interdependent decisionmaking of individuals in social systems can be modelled by games played on complex networks. Players in such systems have bounded rationality, which influences the computation of equilibrium solutions. It has been shown that the ‘system rationality’, which indicates the overall rationality of a network of players, may play a key role in the emergence of scale-free or core-periphery topologies in real-world networks. In this work, we identify optimal topologies and mixing patterns of players which can maximise system rationality. Based on simulation results, we show that irrespective of the placement of nodes with higher rationality, it is the disassortative mixing of node rationality that helps to maximize system rationality in a population. In other words, the findings of this work indicate that the overall rationality of a population may improve when more players with non-similar individual rationality levels interact with each other. We identify particular topologies such as the core-periphery topology, which facilitates the optimisation of system rationality. The findings presented in this work may have useful interpretations and applications in socio-economic systems for maximizing the utility of interactions in a population of strategic players.
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    PublicationOpen Access
    Disassortative mixing of boundedly-rational players in socio-ecological systems
    (researchgate.net, 2022-03-25) Ratnayake, P; Kasthurirathna, D; Piraveenan, M
    Bounded rationality refers to the non-optimal rationality of players in non-cooperative games. In a networked game, the bounded rationality of players may be heterogeneous and spatially distributed. It has been shown that the ‘system rationality’, which indicates the overall rationality of a network of players, may play a key role in the emergence of scale-free or core-periphery topologies in real-world networks. On the other hand, scalar-assortativity is a metric used to quantify the assortative mixing of nodes with respect to a given scalar attribute. In this work, we observe the effect of node rationality-based scalar-assortativity, on the system rationality of a network. Based on simulation results, we show that irrespective of the placement of nodes with higher rationality, it is the disassortative mixing of node rationality that helps to maximize system rationality in a population. The findings may have useful interpretations and applications in socio-economic systems in maximizing the utility of interactions in a population of strategic players
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    PublicationOpen Access
    Quantifying the Robustness of Complex Networks with Heterogeneous Nodes
    (Multidisciplinary Digital Publishing Institute, 2021-01) Ratnayake, P; Weragoda, S; Wansapura, J; Kasthurirathna, D; Piraveenan, M
    The robustness of a complex network measures its ability to withstand random or targeted attacks. Most network robustness measures operate under the assumption that the nodes in a network are homogeneous and abstract. However, most real-world networks consist of nodes that are heterogeneous in nature. In this work, we propose a robustness measure called fitnessincorporated average network efficiency, that attempts to capture the heterogeneity of nodes using the ‘fitness’ of nodes in measuring the robustness of a network. Further, we adopt the same measure to compare the robustness of networks with heterogeneous nodes under varying topologies, such as the scale-free topology or the Erd˝os–Rényi random topology. We apply the proposed robustness measure using a wireless sensor network simulator to show that it can be effectively used to measure the robustness of a network using a topological approach. We also apply the proposed robustness measure to two real-world networks; namely the CO2 exchange network and an air traffic network. We conclude that with the proposed measure, not only the topological structure, but also the fitness function and the fitness distribution among nodes, should be considered in evaluating the robustness of a complex network.