Wolters Kluwer Health may email you for journal alerts and information, but is committed to maint... more Wolters Kluwer Health may email you for journal alerts and information, but is committed to maintaining your privacy and will not share your personal information without your express consent. For more information, please refer to our Privacy Policy. ... Skip Navigation Links Home > January ...
Significant improvements in Information and Communication (ICT) infrastructure over the last deca... more Significant improvements in Information and Communication (ICT) infrastructure over the last decade put Sri Lanka among the top developing nations for ICT-led economic and social growth. While ICT has also contributed to increased research outcomes through better access to world-class knowledge, research resources, and other researchers, overall growth and significance of research findings are not in par with most of the top developing nations. In this research, through surveys and interviews, we explore the current state of computing resources available for research, as well as the needs and challenges faced by researchers. We identified a number of challenges, including shortage of computational and storage resources, cost of software licenses, limited awareness of alternative tools, inadequate programing skills among graduate students, unavailability of research computing support staff, unreliable infrastructure, and organizational constraints. We further discuss potential soluti...
With the rapid evolution of technological, economic, and regulatory landscapes, contemporary Bloc... more With the rapid evolution of technological, economic, and regulatory landscapes, contemporary Blockchian platforms are all but certain to undergo major changes. Therefore, applications that rely on them will eventually need to migrate the Blockchain to remain competitive and secure, as well as to enhance the performance, cost efficiency, privacy, and regulatory compliance. However, the differences in data and smart contract representations, mode of hosting, transaction fees, and the need to preserve consistency, immutability, and data provenance introduce unique challenges over database migration. We first present a set of Blockchain migration scenarios and data fidelity levels using an illustrative example. We then derive a set of migration patterns to address those scenarios and above data management challenges. Finally, we demonstrate how the effort, cost, and risk of Blockchain migration can be minimized by choosing a suitable data fidelity level and proactive system design. Prac...
The division of police patrol districts affects patrol performance, such as average response time... more The division of police patrol districts affects patrol performance, such as average response time and workload variation. However, the possible sample space is large and the corresponding graph-partitioning problem is NP-complete. Moreover, the resulting patrol beats must be contiguous and compact. We propose a heuristic based, clustering method to divide a given police district into optimal patrol beats based on crime and census data. Use of past crime data, their severity, and census data results in more compact shapes with lower crime response time and equitable workload. Moreover, it enables defining patrol beats for different seasons and time shifts. Furthermore, we considered the actual road distance than the traditional Euclidean distance in responding to crimes. We demonstrated the utility of the proposed method using a real-world crime and census dataset. For the given dataset, maximum response time for Calls For Service (CFS) was 35.2 seconds, which is the time taken to tr...
Emerging collaborative Peer-to-Peer (P2P) applications rely on resource discovery solutions to ag... more Emerging collaborative Peer-to-Peer (P2P) applications rely on resource discovery solutions to aggregate groups of heterogeneous, multi-attribute, and dynamic resources that are distributed. In the absence of data and understanding of real-life resource and query characteristics, design and evaluation of existing solutions have relied on many simplifying assumptions. We first present a summary of resource and query characteristics from PlanetLab. These characteristics are then used to evaluate fundamental design choices for multi-attribute resource discovery based on the cost of advertising/querying resources, index size, and load balancing. Simulation-based analysis indicates that the cost of advertising dynamic attributes is significant and in-creases with the number of attributes. Compared to uniform queries, real-world queries are relatively easier to resolve using unstructured, superpeer, and single-attribute dominated query based structured P2P solutions. However, they cause s...
Improving the fuel efficiency of vehicles is imperative to reduce costs and protect the environme... more Improving the fuel efficiency of vehicles is imperative to reduce costs and protect the environment. While the efficient engine and vehicle designs, as well as intelligent route planning, are well-known solutions to enhance the fuel efficiency, research has also demonstrated that the adoption of fuel-efficient driving behaviors could lead to further savings. In this work, we propose a novel framework to promote fuel-efficient driving behaviors through real-time automatic monitoring and driver feedback. In this framework, a random-forest based classification model developed using historical data to identifies fuel-inefficient driving behaviors. The classifier considers driver-dependent parameters such as speed and acceleration/deceleration pattern, as well as environmental parameters such as traffic, road topography, and weather to evaluate the fuel efficiency of one-minute driving events. When an inefficient driving action is detected, a fuzzy logic inference system is used to deter...
With the rapid evolution of technological, economic, and regulatory landscapes, contemporary bloc... more With the rapid evolution of technological, economic, and regulatory landscapes, contemporary blockchain platforms are all but certain to undergo major changes. Therefore, the applications that rely on them will eventually need to migrate from one blockchain instance to another to remain competitive and secure, as well as to enhance the business process, performance, cost efficiency, privacy, and regulatory compliance. However, the differences in data and smart contract representations, modes of hosting, transaction fees, as well as the need to preserve consistency, immutability, and data provenance introduce unique challenges over database migration. We first present a set of blockchain migration scenarios and data fidelity levels using an illustrative example. We then present a set of migration patterns to address those scenarios and the above data management challenges. Finally, we demonstrate how the effort, cost, and risk of migration could be minimized by choosing a suitable se...
One of the major challenges in Wireless Sensor Networks (WSNs) is saving energy to prolonging sen... more One of the major challenges in Wireless Sensor Networks (WSNs) is saving energy to prolonging sensor motes' lifetime, as battery capacities are limited and often difficult to replace or re-charge. In dense sensor a mote deployment, which is often the case, energy consumption could be reduced by activating only a subset of the sensors at a time based on the spatial and temporal correlations among the sensors. However, identifying such subsets is nontrivial as the associated set-cover problem is NP-complete. Therefore, we propose a heuristic-based algorithm called the Correlated Set Calculation Algorithm (CSCA) to determine the subset of motes to be activated at a given time. CSCA considers both the spatial correlation among sensors and multiple sensor types in determining the subset of sensor motes to activate. Therefore, CSCA could enhance the coverage of the area of interest while minimizing the overall energy expenditure and maximizing the lifetime of the WSN. Experimental and...
: The primary goal is to develop a novel, efficient, integrated, subsurface monitoring system, ca... more : The primary goal is to develop a novel, efficient, integrated, subsurface monitoring system, capable of capturing transient chemical plumes in real-time to assess the source and predict future plume behavior. This proof-of-concept research aimed at demonstrating the use of an intelligent Wireless Sensor Network (WSN) to monitor contaminant plume movement in naturally heterogeneous subsurface formations to advance the sensor networking based monitoring for decision making and design. Also of specific interest in the demonstration using synthetic data and date from test aquifers, was how we can adapt computational transport models to utilize data from the WSN and how well this improves model predictions to be used in intelligent remediation. Experimental research was conducted in 2-D and 3-D test aquifers. The data generated in these synthetic aquifer instrumented with sensors and motes was used to validate developed software, inversion methods and modeling tools. A study, which foc...
2020 5th International Conference on Information Technology Research (ICITR)
With the increasing appetite for publicly available personal data for various analytics and decis... more With the increasing appetite for publicly available personal data for various analytics and decision making, due care must be taken to preserve the privacy of data subjects before any disclosure of data. Though many data anonymization techniques are available, there is no holistic understanding of their risk of re-identification and the conditions under which they could be applied. Therefore, it is imperative to study the risk of re-identification of anonymization techniques across different types of datasets. In this paper, we assess the re identification risk of four popular anonymization techniques against four different datasets. We use population uniqueness to evaluate the risk of re-identification. As per the analysis, k anonymity shows the lowest re-identification risk for unbiased samples of the population datasets. Moreover, our findings also emphasize that the risk assessment methodology should depend on the chosen dataset. Furthermore, for the datasets with higher linkability, the risk of re-identification measured using the uniqueness is much lower than the real risk of re-identification.
2017 IEEE International Conference on Industrial and Information Systems (ICIIS)
Distracted drivers are causing a staggering number of accidents. Drivers deviate from their typic... more Distracted drivers are causing a staggering number of accidents. Drivers deviate from their typical driving pattern due to reasons such as stress, distraction, drowsiness, and drunkenness. We present a vehicular data acquisition and analytics system for real-time driver behavior monitoring, anomaly detection, and alerting. On Board Diagnostic (OBD) unit available in most of the modern vehicles is used to collect the driver and vehicle related parameters. OBD-to-Bluetooth dongle is used to extract the data via a mobile app. Mobile app then transfers the data to a backend consisting of a Complex Event Processor (CEP). Then the proposed system first performs a historical analysis of completed trips to identify a driver's behavior using a Markov model and k-Means clustering algorithms. Moreover, Adaboost algorithm is used for safe driver-behavior monitoring. Based on these the CEP engine identifies multiple parameters to generate and classify a driver's driving style. Once a deviation from the typical driving pattern is detected the user is alerted. Experimental results show the proposed system can achieve more than 90% accuracy under various driving simulations.
In a blockchain-based system, data and the consensus-based process of recording and updating them... more In a blockchain-based system, data and the consensus-based process of recording and updating them over distributed nodes are central to enabling the trustless multi-party transactions. Thus, properly understanding what and how the data are stored and manipulated ultimately determines the degree of utility, performance, and cost of a blockchain-based application. While blockchains enhance the quality of the data by providing a transparent, immutable, and consistent data store, the technology also brings new challenges from a data management perspective. In this paper, we analyse blockchains from the viewpoint of a developer to highlight important concepts and considerations when incorporating a blockchain into a larger software system as a data store. The work aims to increase the level of understanding of blockchain technology as a data store and to promote a methodical approach in applying it to large software systems. First, we identify the common architectural layers of a typical software system with data stores and conceptualise each layer in blockchain terms. Second, we examine the placement and flow of data in blockchain-based applications. Third, we explore data administration aspects for blockchains, especially as a distributed data store. Fourth, we discuss the analytics of blockchain data and trustable data analytics enabled by blockchain. Lastly, we examine the data governance issues in blockchains in terms of privacy and quality assurance.
International Journal of Computing & Network Technology
Distributed, multi-attribute Resource Discovery (RD) is a fundamental requirement in collaborativ... more Distributed, multi-attribute Resource Discovery (RD) is a fundamental requirement in collaborative Peer-to-Peer (P2P), grid, and cloud computing. We present an efficient and load balanced, P2P-based multi-attribute RD solution that consists of five heuristics, which can be executed independently and distributedly. First heuristic maintains a minimum number of nodes in a ringlike overlay while pruning nodes that do not significantly contribute to the range query resolution. Removing nonproductive nodes reduces the cost (e.g., hops and latency) of advertising resources and resolving queries. Second and third heuristics dynamically balance the key and query load distribution by transferring some of the keys to its predecessor/successor and by adding new predecessors/successors to handle transferred keys when existing nodes are insufficient, respectively. Last two heuristics form cliques of nodes (that are placed orthogonal to the overlay ring) to dynamically balance the highly skewed key and query loads. By applying these heuristics in the presented order, a RD solution that better responds to real-world resource and query characteristics is developed. Its efficacy is demonstrated using a simulation-based analysis under a variety of single and multi-attribute resource and query distributions derived from real workloads.
Wolters Kluwer Health may email you for journal alerts and information, but is committed to maint... more Wolters Kluwer Health may email you for journal alerts and information, but is committed to maintaining your privacy and will not share your personal information without your express consent. For more information, please refer to our Privacy Policy. ... Skip Navigation Links Home > January ...
Significant improvements in Information and Communication (ICT) infrastructure over the last deca... more Significant improvements in Information and Communication (ICT) infrastructure over the last decade put Sri Lanka among the top developing nations for ICT-led economic and social growth. While ICT has also contributed to increased research outcomes through better access to world-class knowledge, research resources, and other researchers, overall growth and significance of research findings are not in par with most of the top developing nations. In this research, through surveys and interviews, we explore the current state of computing resources available for research, as well as the needs and challenges faced by researchers. We identified a number of challenges, including shortage of computational and storage resources, cost of software licenses, limited awareness of alternative tools, inadequate programing skills among graduate students, unavailability of research computing support staff, unreliable infrastructure, and organizational constraints. We further discuss potential soluti...
With the rapid evolution of technological, economic, and regulatory landscapes, contemporary Bloc... more With the rapid evolution of technological, economic, and regulatory landscapes, contemporary Blockchian platforms are all but certain to undergo major changes. Therefore, applications that rely on them will eventually need to migrate the Blockchain to remain competitive and secure, as well as to enhance the performance, cost efficiency, privacy, and regulatory compliance. However, the differences in data and smart contract representations, mode of hosting, transaction fees, and the need to preserve consistency, immutability, and data provenance introduce unique challenges over database migration. We first present a set of Blockchain migration scenarios and data fidelity levels using an illustrative example. We then derive a set of migration patterns to address those scenarios and above data management challenges. Finally, we demonstrate how the effort, cost, and risk of Blockchain migration can be minimized by choosing a suitable data fidelity level and proactive system design. Prac...
The division of police patrol districts affects patrol performance, such as average response time... more The division of police patrol districts affects patrol performance, such as average response time and workload variation. However, the possible sample space is large and the corresponding graph-partitioning problem is NP-complete. Moreover, the resulting patrol beats must be contiguous and compact. We propose a heuristic based, clustering method to divide a given police district into optimal patrol beats based on crime and census data. Use of past crime data, their severity, and census data results in more compact shapes with lower crime response time and equitable workload. Moreover, it enables defining patrol beats for different seasons and time shifts. Furthermore, we considered the actual road distance than the traditional Euclidean distance in responding to crimes. We demonstrated the utility of the proposed method using a real-world crime and census dataset. For the given dataset, maximum response time for Calls For Service (CFS) was 35.2 seconds, which is the time taken to tr...
Emerging collaborative Peer-to-Peer (P2P) applications rely on resource discovery solutions to ag... more Emerging collaborative Peer-to-Peer (P2P) applications rely on resource discovery solutions to aggregate groups of heterogeneous, multi-attribute, and dynamic resources that are distributed. In the absence of data and understanding of real-life resource and query characteristics, design and evaluation of existing solutions have relied on many simplifying assumptions. We first present a summary of resource and query characteristics from PlanetLab. These characteristics are then used to evaluate fundamental design choices for multi-attribute resource discovery based on the cost of advertising/querying resources, index size, and load balancing. Simulation-based analysis indicates that the cost of advertising dynamic attributes is significant and in-creases with the number of attributes. Compared to uniform queries, real-world queries are relatively easier to resolve using unstructured, superpeer, and single-attribute dominated query based structured P2P solutions. However, they cause s...
Improving the fuel efficiency of vehicles is imperative to reduce costs and protect the environme... more Improving the fuel efficiency of vehicles is imperative to reduce costs and protect the environment. While the efficient engine and vehicle designs, as well as intelligent route planning, are well-known solutions to enhance the fuel efficiency, research has also demonstrated that the adoption of fuel-efficient driving behaviors could lead to further savings. In this work, we propose a novel framework to promote fuel-efficient driving behaviors through real-time automatic monitoring and driver feedback. In this framework, a random-forest based classification model developed using historical data to identifies fuel-inefficient driving behaviors. The classifier considers driver-dependent parameters such as speed and acceleration/deceleration pattern, as well as environmental parameters such as traffic, road topography, and weather to evaluate the fuel efficiency of one-minute driving events. When an inefficient driving action is detected, a fuzzy logic inference system is used to deter...
With the rapid evolution of technological, economic, and regulatory landscapes, contemporary bloc... more With the rapid evolution of technological, economic, and regulatory landscapes, contemporary blockchain platforms are all but certain to undergo major changes. Therefore, the applications that rely on them will eventually need to migrate from one blockchain instance to another to remain competitive and secure, as well as to enhance the business process, performance, cost efficiency, privacy, and regulatory compliance. However, the differences in data and smart contract representations, modes of hosting, transaction fees, as well as the need to preserve consistency, immutability, and data provenance introduce unique challenges over database migration. We first present a set of blockchain migration scenarios and data fidelity levels using an illustrative example. We then present a set of migration patterns to address those scenarios and the above data management challenges. Finally, we demonstrate how the effort, cost, and risk of migration could be minimized by choosing a suitable se...
One of the major challenges in Wireless Sensor Networks (WSNs) is saving energy to prolonging sen... more One of the major challenges in Wireless Sensor Networks (WSNs) is saving energy to prolonging sensor motes' lifetime, as battery capacities are limited and often difficult to replace or re-charge. In dense sensor a mote deployment, which is often the case, energy consumption could be reduced by activating only a subset of the sensors at a time based on the spatial and temporal correlations among the sensors. However, identifying such subsets is nontrivial as the associated set-cover problem is NP-complete. Therefore, we propose a heuristic-based algorithm called the Correlated Set Calculation Algorithm (CSCA) to determine the subset of motes to be activated at a given time. CSCA considers both the spatial correlation among sensors and multiple sensor types in determining the subset of sensor motes to activate. Therefore, CSCA could enhance the coverage of the area of interest while minimizing the overall energy expenditure and maximizing the lifetime of the WSN. Experimental and...
: The primary goal is to develop a novel, efficient, integrated, subsurface monitoring system, ca... more : The primary goal is to develop a novel, efficient, integrated, subsurface monitoring system, capable of capturing transient chemical plumes in real-time to assess the source and predict future plume behavior. This proof-of-concept research aimed at demonstrating the use of an intelligent Wireless Sensor Network (WSN) to monitor contaminant plume movement in naturally heterogeneous subsurface formations to advance the sensor networking based monitoring for decision making and design. Also of specific interest in the demonstration using synthetic data and date from test aquifers, was how we can adapt computational transport models to utilize data from the WSN and how well this improves model predictions to be used in intelligent remediation. Experimental research was conducted in 2-D and 3-D test aquifers. The data generated in these synthetic aquifer instrumented with sensors and motes was used to validate developed software, inversion methods and modeling tools. A study, which foc...
2020 5th International Conference on Information Technology Research (ICITR)
With the increasing appetite for publicly available personal data for various analytics and decis... more With the increasing appetite for publicly available personal data for various analytics and decision making, due care must be taken to preserve the privacy of data subjects before any disclosure of data. Though many data anonymization techniques are available, there is no holistic understanding of their risk of re-identification and the conditions under which they could be applied. Therefore, it is imperative to study the risk of re-identification of anonymization techniques across different types of datasets. In this paper, we assess the re identification risk of four popular anonymization techniques against four different datasets. We use population uniqueness to evaluate the risk of re-identification. As per the analysis, k anonymity shows the lowest re-identification risk for unbiased samples of the population datasets. Moreover, our findings also emphasize that the risk assessment methodology should depend on the chosen dataset. Furthermore, for the datasets with higher linkability, the risk of re-identification measured using the uniqueness is much lower than the real risk of re-identification.
2017 IEEE International Conference on Industrial and Information Systems (ICIIS)
Distracted drivers are causing a staggering number of accidents. Drivers deviate from their typic... more Distracted drivers are causing a staggering number of accidents. Drivers deviate from their typical driving pattern due to reasons such as stress, distraction, drowsiness, and drunkenness. We present a vehicular data acquisition and analytics system for real-time driver behavior monitoring, anomaly detection, and alerting. On Board Diagnostic (OBD) unit available in most of the modern vehicles is used to collect the driver and vehicle related parameters. OBD-to-Bluetooth dongle is used to extract the data via a mobile app. Mobile app then transfers the data to a backend consisting of a Complex Event Processor (CEP). Then the proposed system first performs a historical analysis of completed trips to identify a driver's behavior using a Markov model and k-Means clustering algorithms. Moreover, Adaboost algorithm is used for safe driver-behavior monitoring. Based on these the CEP engine identifies multiple parameters to generate and classify a driver's driving style. Once a deviation from the typical driving pattern is detected the user is alerted. Experimental results show the proposed system can achieve more than 90% accuracy under various driving simulations.
In a blockchain-based system, data and the consensus-based process of recording and updating them... more In a blockchain-based system, data and the consensus-based process of recording and updating them over distributed nodes are central to enabling the trustless multi-party transactions. Thus, properly understanding what and how the data are stored and manipulated ultimately determines the degree of utility, performance, and cost of a blockchain-based application. While blockchains enhance the quality of the data by providing a transparent, immutable, and consistent data store, the technology also brings new challenges from a data management perspective. In this paper, we analyse blockchains from the viewpoint of a developer to highlight important concepts and considerations when incorporating a blockchain into a larger software system as a data store. The work aims to increase the level of understanding of blockchain technology as a data store and to promote a methodical approach in applying it to large software systems. First, we identify the common architectural layers of a typical software system with data stores and conceptualise each layer in blockchain terms. Second, we examine the placement and flow of data in blockchain-based applications. Third, we explore data administration aspects for blockchains, especially as a distributed data store. Fourth, we discuss the analytics of blockchain data and trustable data analytics enabled by blockchain. Lastly, we examine the data governance issues in blockchains in terms of privacy and quality assurance.
International Journal of Computing & Network Technology
Distributed, multi-attribute Resource Discovery (RD) is a fundamental requirement in collaborativ... more Distributed, multi-attribute Resource Discovery (RD) is a fundamental requirement in collaborative Peer-to-Peer (P2P), grid, and cloud computing. We present an efficient and load balanced, P2P-based multi-attribute RD solution that consists of five heuristics, which can be executed independently and distributedly. First heuristic maintains a minimum number of nodes in a ringlike overlay while pruning nodes that do not significantly contribute to the range query resolution. Removing nonproductive nodes reduces the cost (e.g., hops and latency) of advertising resources and resolving queries. Second and third heuristics dynamically balance the key and query load distribution by transferring some of the keys to its predecessor/successor and by adding new predecessors/successors to handle transferred keys when existing nodes are insufficient, respectively. Last two heuristics form cliques of nodes (that are placed orthogonal to the overlay ring) to dynamically balance the highly skewed key and query loads. By applying these heuristics in the presented order, a RD solution that better responds to real-world resource and query characteristics is developed. Its efficacy is demonstrated using a simulation-based analysis under a variety of single and multi-attribute resource and query distributions derived from real workloads.
Uploads
Papers by Dilum Bandara