Browsing by Author "Wijekoon, J"

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Embargo
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.
Embargo
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.
Embargo
The advanced remote PC management suite
(IEEE, 2011-08-16) Wijekoon, J; Wijesundara, M; Dassanayaka, T; Samarathunga, D; Dissanayaka, R; Perera, D
Developing a system that helps system administrators to perform their administration task more effectively and efficiently is of great importance to reduce downtime, cost and man power requirement. The Advanced Remote PC Management Suite facilitates centralized management of PC infrastructure employing the Intel Active Management Technology (AMT). This technology enables the system administrators to monitor and manage computers via a dedicated channel regardless of whether the computer is powered on. This is known as Out-of-Band (OOB) management. Currently AMT is available in Desktops and Laptops with The 2nd generation Intel Core vPro processors. Using features of AMT, the The Advanced Remote PC Management Suite provides a real-time and intelligent asset management facility in addition to monitoring and administration capabilities. The system also features automated operating system deployment and centralized disk cloning mechanisms. It is also possible to isolate any computer in the network using the system, during incidents such as virus infections. Therefore, this system is able to drastically reduce the number of desk-side-visits by system administrators to setup and troubleshoot PCs in large enterprise networks.
Embargo
AI-Based Child Care Parental Control System
(IEEE, 2022-12-09) Jayasekara, U; Maniyangama, H; Vithana, K; Weerasinghe, T; Wijekoon, J; Panchendrarajan, R
Due to the prevalence of the COVID-19 epidemic around the globe, children were compelled to engage in remote learning through online platforms, hence mobile phone has become one of their predominant devices. Mobile device with Internet access offers a major outlet for education, entertainment, and social connection, but this combination can lead to several significant bad sequences such as online exploitation, harmful addictions, and other negative impacts of online social networking. To address harmful effects, parental controls are becoming more crucial, yet Sri Lankan parents are less aware of this. Consequently, this study proposes a parental control system to monitor their child’s activities. Android, Microsoft Azure, Java, Python, OpenCV, MySQL, and FastAPI are among the most prominent technologies utilized in the proposed application’s development. The suggested approach focuses primarily on the Sri Lankan context and aims to enhance parental digital literacy while safeguarding children from cyber threats. Yielded results showed the proposed mobile application for the identification of toxic words, drugs & alcohol content, game character images, and Instagram Sinhala comments severity as 94%, 95%, 97%, and 55% respectively in controlled experiments.
Embargo
An Automated Solution For Securing Confidential Documents in a BYOD Environment
(IEEE, 2021-12-09) Abisheka, P. A. C; Azra, M. A. F; Poobalan, A. V; Wijekoon, J; Yapa, K; Murthaja, M
BYOD or Bring Your Own Device is a set of policies that allow employees of an organization to use their own devices for official work purposes. BYOD is an immensely popular concept in the present day due to the many advantages it provides. However, the implementation of BYOD policies entail diverse problems and as a result, the confidentiality of documents can be breached. Furthermore, employees without security awareness and training are highly vulnerable to endpoint attacks, network attacks, and zero-day attacks that lead to a breach of confidentiality, integrity, and availability (CIA). In this context, this paper proposes a comprehensive solution; ‘BYODENCE’, for the detection and prevention of unauthorized access to organizational documents. BYODENCE is an efficient BYOD solution which can produce competitive results in terms of accuracy and speed.
Open Access
COVID-19 symptom identification using Deep Learning and hardware emulated systems
(Elsevier, 2023-06-28) Liyanarachchi, R; Wijekoon, J; Premathilaka, M; Vidhanaarachchi, S
The COVID-19 pandemic disrupted regular global activities in every possible way. This pandemic, caused by the transmission of the infectious Coronavirus, is characterized by main symptoms such as fever, fatigue, cough, and loss of smell. A current key focus of the scientific community is to develop automated methods that can effectively identify COVID-19 patients and are also adaptable for foreseen future virus outbreaks. To classify COVID-19 suspects, it is required to use contactless automatic measurements of more than one symptom. This study explores the effectiveness of using Deep Learning combined with a hardware-emulated system to identify COVID-19 patients in Sri Lanka based on two main symptoms: cough and shortness of breath. To achieve this, a Convolutional Neural Network (CNN) based on Transfer Learning was employed to analyze and compare the features of a COVID-19 cough with other types of coughs. Real-time video footage was captured using a FLIR C2 thermal camera and a web camera and subsequently processed using OpenCV image processing algorithms. The objective was to detect the nasal cavities in the video frames and measure the breath cycles per minute, thereby identifying instances of shortness of breath. The proposed method was first tested on crowd-sourced datasets (Coswara, Coughvid, ESC-50, and a dataset from Kaggle) obtained online. It was then applied and verified using a dataset obtained from local hospitals in Sri Lanka. The accuracy of the developed methodologies in diagnosing cough resemblance and recognizing shortness of breath was found to be 94% and 95%, respectively.
Embargo
CoviDefender: Digital Personal Guard For Defending Against COVID19
(IEEE, 2021-09-30) Dayarathna, P; Kumara, I; Ranaweera, D; Nawinna, D; Karunaratne, G; Wijekoon, J
In late 31 December 2019, a cluster of unexplained pneumonia cases was reported in Wuhan, China [1]. A few days later, the causative agent of this mysterious pneumonia was identified as the new COVID-19 virus. Currently, it has been spreading for more than one and a half years and has lost a huge number of lives all over the world. Most people faced this disaster because of their ignorance, carelessness and lack of updates. By the way most people are in lack of knowledge regarding COVID-19 pandemic, symptoms and what should do to survive from that. Those issues are great problems nowadays. “CoviDefender” is set to offer a solution to this worldwide COVID-19 pandemic problem. This is a new technological solution from a mobile application. “CoviDefender” is a Smart Assistant for Defending against COVID-19 Pandemic. This can be described as a solution to the ignorance and carelessness of the people who have been the main cause of the spread of this epidemic.
Embargo
CoviDefender: Digital Personal Guard For Defending Against COVID19
(IEEE, 2021-09-30) Dayarathna, p; Kumara, I; Ranaweera, D; Nawinna, D. P; Karunaratne, G; Wijekoon, J
In late 31 December 2019, a cluster of unexplained pneumonia cases was reported in Wuhan, China [1]. A few days later, the causative agent of this mysterious pneumonia was identified as the new COVID-19 virus. Currently, it has been spreading for more than one and a half years and has lost a huge number of lives all over the world. Most people faced this disaster because of their ignorance, carelessness and lack of updates. By the way most people are in lack of knowledge regarding COVID-19 pandemic, symptoms and what should do to survive from that. Those issues are great problems nowadays. “CoviDefender” is set to offer a solution to this worldwide COVID-19 pandemic problem. This is a new technological solution from a mobile application. “CoviDefender” is a Smart Assistant for Defending against COVID-19 Pandemic. This can be described as a solution to the ignorance and carelessness of the people who have been the main cause of the spread of this epidemic.
Embargo
Distributed algorithm for router-based management of replica server in next-CDN infrastructure
(IEEE, 2013-10-10) Harahap, E; Wijekoon, J; Tennekoon, R; Yamaguchi, F; Ishida, S; Nishi, H
Extending Content Delivery Network (CDN) infrastructure that has features of router-based network management system (RNMS) is highly appealing and challenging. It allows developing a CDN architecture based upon standard design to ease interoperability, scalability, performance, and flexibility both on network monitoring and management controlled from a router. To better understand the system model, necessity, and the advantages of RNMS, this paper proposed an algorithm that distributed in to a special router called Service-oriented Router (SoR). The function of algorithm is to manage the effective and efficient number of replica server runs in the network. In CDN, minimizing the number of activated replica servers should be considered in order to reduce the operation cost of the system. We propose a semantic approached algorithm that has function to optimize the selection of active replica servers which managed from SoR. The algorithm has capability to find the best location of replica servers and performs load balancing among replica servers. Our simulation result indicates that the proposed algorithm can efficiently activate the replica servers according to user's request with 33.9% effective compared to other algorithm within about one millisecond RTT increase.
Embargo
Effective use of network device state information for network path selection
(IEEE, 2017-01-27) Wijekoon, J; Abeygunawardhana, P. K. W
Network path selection defines the methodology of selecting the best routes and forwarding traffic in a network service provider (NSP). NSPs use routing protocols that are optimized for a single arbitrary metric (i.e., administrative weight), which is commonly calculated according to the link state information, to select network paths. Despite the advantages, link-state protocols lack the ability to select network paths by considering the states of network devices such as the effect of routers for network path selection. Apparently, studying possible techniques for selecting network paths based on the state information of network devices, e.g., routers, has become obligatory. This paper hypothesis to calculate a composite path selection metric by employing the state information of network devices; the proposed method selects the network paths based on the cumulative packet traveling time. By simulating proposed method using an ISP topology, the proposed method is examined for the effectiveness of using network device state information for network path selection.
Embargo
Effectiveness of a service-oriented router in future content delivery networks
(IEEE, 2015-07-07) Wijekoon, J; Harahap, E; Takagiwa, K; Tennekoon, R; Nishi, H
Content Delivery Networks (CDNs) constitute a major portion of Internet traffic. To cope with increasing demand for content, CDNs have deployed distributed infrastructures on Internet Service Providers (ISPs') networks. Most CDN systems optimize their traffic flow using Domain Name Systems. However, they do not collaborate with the ISPs, and the lack of collaboration limits performance such as end-user latency. Meanwhile, in future networks, it is anticipated that network routers will be equipped with more processing power and storage modules for providing most effective end-user services. From this viewpoint, a Service-oriented Router (SoR) is introduced to accelerate content-based services. In this paper, the benefits of introducing an SoR to an ISP network for maintaining ISP-CDN collaboration is outlined. Furthermore, a prototype design of the proposed system is presented. Simulations clearly demonstrate the effectiveness of the proposed ISP-CDN collaboration, which yields a 30-50% reduction in end-user latency.
Embargo
Effectiveness of artificial intelligence, decentralized and distributed systems for prediction and secure channelling for Medical Tourism
(IEEE, 2020-11-04) Subasinghe, M; Magalage, D; Amadoru, N; Amarathunga, L; Bhanupriya, N; Wijekoon, J
Good health and wellbeing, a sustainable development goal introduced by the United Nations to be achieved by 2030. Sri Lanka is a country that highly depends on tourism. A healthcare system which consists of high quality and low-cost services and an abundance of tourist attractions makes Sri Lanka to be one of the best medical tourism destinations. Tourism and travel have contributed to the GDP of Sri Lanka by 11.1 billion USD by 2018. Lack of technological advancements within the medical sector has drawn back the ability to smoothly cater medical tourism. The proposed system aims for an advanced technological improvement that would help in further developing and contributing to medical tourism. To this end, this paper introduces an Intelligent System for Secure Channeling platform that aids medical tourism with the help of artificial intelligence and blockchain technologies. System proposes a treatment prediction and suggesting the best doctor for it and a secured network to store and access electronic health records (EHR). The yielded results show that the proposed method successfully performed treatment prediction with 79-88% accuracy.
Open Access
Effectiveness of Service-oriented router for ISP-CDN collaboration
(Information Processing Society of Japan, 2017-01) Wijekoon, J; Harahap, E. H; Tennekoon, R; Nishi, H
This article discusses a novel method to strengthen the collaboration between Internet service providers (ISPs) and content delivery networks (CDNs). CDNs are becoming the primary data delivery method in information communication technology environments because information sharing via networks is becoming the driving force of the future Internet. Moreover, it is anticipated that network routers will be equipped with additional processing power and storage modules for providing efficient end-user services. Consequently, this article studies the effectiveness of introducing a Service-oriented Router (SoR) to strengthen the ISP-CDN collaboration to leverage DNS-based request redirection in CDNs. In contrast, the proposed method yields better performance in user redirection and network resource utilization, suggesting that using SoR may a future business model which addresses adequate ISP-CDN collaboration.
Embargo
Effectiveness of Using Radiology Images and Mask R-CNN for Stomatology
(IEEE, 2022-12-09) Jayasinghe, H; Pallepitiya, N; Chandrasiri, A; Heenkenda, C; Vidhanaarachchi, S; Kugathasan, A; Rathnayaka, K; Wijekoon, J
Dental health-related disorders have proliferated worldwide due to the excessive intake of fast food and sugary foods, which was followed by bad oral hygiene practices. The cost of dental examinations may change based on how critical the condition is, regardless of whether they are not regular. For a person, diagnosing an oral health problem, particularly locating the disease’s underlying cause, can be challenging. To properly diagnose and treat such conditions, advanced dental diagnostic techniques may be necessary. By offering convenience and enhancing their oral health knowledge, the system seeks to serve as a prediction tool that regular people can utilize to detect potential tooth illnesses at an early stage. It is encompassed as a mobile application where a Mask R-CNN model is used in the core that accepts a dental radiograph as the input. The trained model will be able to identify diseases related to the bone and teeth. Based on the performance evaluations, the accuracy of the results that are obtained in tooth type, restoration quality, dental caries, and periodontal disease identification falls in the range of 75%-80%.
Embargo
Effects of the Organizational Knowledge Management Systems on Psychological Well-Being Among Employees in Private Large-Scale IT Organizations in Sri Lanka
(IEEE, 2023-06-12) Aratthanage, K; Wijekoon, J
The goal of this study basically focuses on evaluating the Organizational Knowledge Management Systems (KMS) and their impact on psychological well-being among employees in selected large-scale private IT organizations in Sri Lanka. It evaluates Knowledge Management Systems quality dimensions, KMS adoption of users, and psychological well-being. Knowledge Management is an essential part in IT industry. Gaining domain knowledge from one starting point to sharing knowledge among organizations is a very complex process, therefore, different types of Knowledge Management systems are implemented within IT organizations. There are several quality dimension factors introduced to determine better knowledge management systems. This research evaluates eight quality dimensions against four psychological aspects. In this study, statistical analysis was used to determine the statistically significant levels, correlations and relationships between the independent and dependent variables. Ultimately the results can be used to improve the Human-centered Knowledge Management System's design approach with balanced employee psychological well-being. For further improvements, the results can be used to build interactive knowledge management software-based solutions.
Open Access
Enhanced Content Navigation Using Edge Routers in Content Delivery Network
(Keio University Japan, 2016-08) Wijekoon, J
The Internet can be defined as a network composed of geographically dispersed servers and clients. In principle, clients request content from servers, and the servers respond to the requests by sending the requested content to the clients. The content should be navigated among networks, and certain rules and methods have been developed to achieve optimized navigation. Navigation is definable as the process of finding a destination and reaching that destination using a preferable route. Hence, the main challenges for achieving content navigation on the Internet can be summarized in the following two directions: 1) to determine and select service points and 2) to route users to selected service points. The need for optimized content delivery accelerates the development of the Internet by proposing content delivery networks (CDNs). CDNs use content cache servers within Internet Service Provider (ISP) networks …
Embargo
FROG: A packet hop count based DDoS countermeasure in NDN
(IEEE, 2018-05-25) Nakatsuka, Y; Wijekoon, J; Nishi, H
Named Data Networking (NDN) is a promising inter-networking paradigm that focus on content rather than hosts and their physical locations. In NDN Consumers issue Interests for Contents. Producers generate a content in response to each received interest and such content is routed back to the requesting consumer. When compared to IP, NDN brings advantages such as better throughput and lower latency, because routers are able to cache popular contents and satisfy interests for such contents locally. However, before being considered a viable approach, NDN should offer security services that are ideally better, but at least equivalent to current mechanisms in IP.In this regard, mechanisms to prevent DDoS are of paramount importance. In this work we propose FROG: a simple yet effective Interest Flooding Attack (IFA) detection and mitigation method. FROG runs on routers that are directly connected to NDN consumers and monitors packet hop counts. It then calculates mean and variance using stored hop counts to distinguish attackers from legitimate users. We use the NDN simulator ndnSIM to evaluate FROG's effectiveness. Our results show that FROG improves resilience against DDoS attacks. In particular, during an attack, legitimate users can still receive 75% of requested contents. Without FROG this number decreases to 50%.
Embargo
Gaja-Mithuru: Smart Elephant Monitoring and Tracking System
(IEEE, 2020-11-04) Fernando, P. P. S; Perera, K. Y. L; Dissanayake, P. N; Jayakody, J. A. D. M; Wijekoon, J; Wijesundara, M
In the past few years, a considerable number of villages bordering elephant populated areas of Sri Lanka have been continuously facing the dire effects of the Human-Elephant conflict. With the expanding human settlements in those natural habitats, the sources of food and water for elephants have gradually diminished over time. Therefore, animals are forced to attack crops. The consequent attacks on the villages cause a steady rise in human and elephant casualties. Within such a context, the existing methods of mitigating the human-elephant conflict have proven to be less effective as they often employ intrusive and harmful methods to ward off elephant threats. Thus, this proposal will focus on a monitoring method that is both nonintrusive and nonharmful to both humans and elephants using IoT technologies. To achieve the said objective, a method is proposed mean to detect elephants, monitor their behavior, and identify elephants' future attacks through seismic data related to elephants and GPS data and notify villages in advance. The data were captured using a hardware setup which includes geophones, circuits for amplification and filtering, and GSM modules for data communication. This method achieved a high accuracy in detecting elephant.
Embargo
A Geophone Based Surveillance System Using Neural Networks and IoT
(IEEE, 2020-12-10) Hettigoda, S; Jayaminda, C; Amarathunga, U; Thaha, S; Wijesundara, M; Wijekoon, J
Securing our assets and properties from intruders and thieves has become increasingly challenging as intruders become technology aware. The most common approach to monitor physical assets is CCTV. However, this approach has a number of technical limitations in addition to the cost. The CCTV camera location is visible to the intruder and intruder can also identify possible blind spots in the CCTV coverage area. In this paper, we introduce a novel method to secure physical assets using Geophones, Neural Networks, and IoT Platforms. This can either be used stand alone or to complement existing CCTV systems. In this approach, the system monitors vibrations on ground to detect intruders. We have achieved up to 93.90% overall accuracy for person identification. The system is invisible to intruders and covers a large area with a smaller number of nodes, thereby reducing the cost of ownership.
Embargo
A Geophone Based Surveillance System Using Neural Networks and IoT
(IEEE, 2020-12-10) Hettigoda, S; Jayaminda, C; Amarathunga, U; Thaha, S; Wijesundara, M; Wijekoon, J
Securing our assets and properties from intruders and thieves has become increasingly challenging as intruders become technology aware. The most common approach to monitor physical assets is CCTV. However, this approach has a number of technical limitations in addition to the cost. The CCTV camera location is visible to the intruder and intruder can also identify possible blind spots in the CCTV coverage area. In this paper, we introduce a novel method to secure physical assets using Geophones, Neural Networks, and IoT Platforms. This can either be used stand alone or to complement existing CCTV systems. In this approach, the system monitors vibrations on ground to detect intruders. We have achieved up to 93.90% overall accuracy for person identification. The system is invisible to intruders and covers a large area with a smaller number of nodes, thereby reducing the cost of ownership.