Indika Anuradha Mendis Balapuwaduge

• Balapuwaduge, Indika A.M. & Asres, Mulugeta Weldezgina (2026). Prompt Compliance and Detectability in Text-to-Video Abnormal Incident Simulation for Safety-Critical Computer Vision. I Misra, Sanjay; Kjølerbakken, Kai Morgan & Braarud, Per Øivind (Red.), International Conference on Human Centric Artificial Intelligence (ICHCAI): First International Conference, ICHCAI 2026. IEEE (Institute of Electrical and Electronics Engineers). ISSN 9798331551186. doi: 10.1109/ICHCAI70183.2026.11607542. Fulltekst i vitenarkiv Vis sammendrag

  Open-source text-to-video (T2V) synthesis has been employed for simulating abnormal-incident scenarios for safety-critical applications, where real-world data are often difficult to collect and share because of privacy, operational, and ethical constraints. Before such synthetic videos can be considered for downstream model development, their semantic fidelity and incident recognizability should be assessed in a transparent and reproducible way. In this work, we evaluate open-source T2V models for abnormal incident video generation using two complementary upstream metrics. First, we propose a prompt compliance ratio that measures the proportion of frames that semantically align with the intended prompt over time. Second, we employ a zero-shot incident classification approach to estimate whether synthesized videos preserve recognizable incident categories without task-specific training. We also examine the impact of key video generation parameters, such as inference steps and subjective video quality using controlled prompts. Our method provides indicators of whether synthetic incident videos are sufficiently reliable for safety and security computer vision research workflows. The results indicate that the proposed metrics are effective for assessing both prompt compliance and zero-shot incident recognition in the generated videos. In addition, the study shows that parameter tuning plays an important role in improving separability and overall video quality.

• Ranaweera, Pasika; Balapuwaduge, Indika A.M.; Jurcut, Anca; Zeydan, Engin & Liyanage, Madhusanka (2026). Optimizing Security in Dynamic Service Migration Scenarios of Multi-Access Edge Computing. IEEE Vehicular Technology Conference (VTC). ISSN 1090-3038. VTC2025-Fall. doi: 10.1109/VTC2025-Fall65116.2025.11310623. Fulltekst i vitenarkiv Vis sammendrag

  Security mechanisms and Service Level Guarantees (SLGs) often operate in tension within communication systems, where stronger security protocols introduce overhead, processing delays, and encryption-related latency that can hinder the ability to meet predefined SLGs. This challenge is particularly critical in Multi-Access Edge Computing (MEC), where service migration across edge nodes can significantly impact system performance. Ensuring the security of migrating services while maintaining low-latency communication is vital to preserving service continuity and avoiding disruptions. In this paper, we introduce a novel security framework for MEC-enabled gNodeBs that supports secure and seamless service migration. Central to our framework is an adaptive security optimization model that dynamically adjusts the security level of the migration channel based on real-time bandwidth utilization. This approach maintains the continuity of service without compromising the available bandwidth, thereby upholding the required SLGs while minimizing the impact of security-related overhead.

• Cosmin, Conţu,; Eugen, Borcoci,; Marius-Constantin, Vochin,; Alexandru, Aloman,; Balapuwaduge, Indika A.M. & Li, Frank Yong (2025). Enabling machine learning-assisted resource monitoring for network slice creation and management in OSM: design, implementation, and validation. Telecommunications Systems. ISSN 1018-4864. 88, s. 1–19. doi: 10.1007/s11235-025-01342-7. Fulltekst i vitenarkiv Vis sammendrag

  As a novel concept introduced in 5th generation (5G) mobile networks, network slicing allows configuring a shared physical infrastructure into multiple logical networks that are virtually isolated from each other. Through these logical networks, resource allocation for specific use cases is tailored, facilitating rapid and flexible development of new services and applications. To create and manage network slices, open source management and orchestration (OSM) has emerged as a powerful tool for software developers and network operators. Within the scope of automatic slice generation and management using OSM, however, whether and how machine learning can play a role remain as a hardly addressed research question. In this paper, we explore the feasibility of applying machine learning to OSM for the purpose of improving slice creation and management efficiency. To do so, we introduce an enhancement in the monitoring module of the OSM architecture. More specifically, a machine learning based alarm monitoring sub-module is developed, such that a new field value is automatically generated every time when an alarm is identified. In addition, we create a prediction model for resource utilization prediction so that the most suitable resources can be allocated when a slice is created. Furthermore, we have implemented our solution in a network slicing platform we developed based on OSM and performed proof-of-concept validation through two network slicing scenarios. Through simulation-based validation and testing, we reveal that the proposed method achieves reliable performance and demonstrate the effectiveness of our solution towards automation network slice creation and management in OSM.

• Ghose, Debasish; Chatterjee, Ayan; Balapuwaduge, Indika A.M.; Lin, Yuan & Dash, Soumya P. (2025). Investigating lightweight and interpretable machine learning models for efficient and explainable stress detection. Frontiers in Digital Health. 7. doi: 10.3389/fdgth.2025.1523381. Fulltekst i vitenarkiv Vis sammendrag

  Stress is a common human reaction to demanding circumstances, and prolonged and excessive stress can have detrimental effects on both mental and physical health. Heart rate variability (HRV) is widely used as a measure of stress due to its ability to capture variations in the time intervals between heartbeats. However, achieving high accuracy in stress detection through machine learning (ML), using a reduced set of statistical features extracted from HRV, remains a significant challenge. In this study, we aim to address these challenges by proposing lightweight ML models that can effectively detect stress using minimal HRV features and are computationally efficient enough for IoT deployment. We have developed ML models incorporating efficient feature selection techniques and hyper-parameter tuning. The publicly available SWELL-KW dataset has been utilized for evaluating the performance of our models. Our results demonstrate that lightweight models such as k-NN and Decision Tree can achieve competitive accuracy while ensuring lower computational demands, making them ideal for real-time applications. Promisingly, among the developed models, the k-nearest neighbors (k-NN) algorithm has emerged as the best-performing model, achieving an accuracy score of 99.3% using only three selected features. To confirm real-world deployability, we benchmarked the best model on an 8 GB NVIDIA Jetson Orin Nano edge device, where it retained 99.26% accuracy and completed training in 31 s. Furthermore, our study has incorporated local interpretable model-agnostic explanations to provide comprehensive insights into the predictions made by the k-NN-based architecture.

• Al-Alwash, Husam Mahdi; Borcoci, Eugen; Vochin, Marius-Constantin; Balapuwaduge, Indika A.M. & Li, Frank Yong (2024). Optimization Schedule Schemes for Charging Electric Vehicles: Overview, Challenges, and Solutions. IEEE Access. 12, s. 32801–32818. doi: 10.1109/ACCESS.2024.3371890. Fulltekst i vitenarkiv
• Ghose, Debasish; Pussewalage, Harsha Gardiyawasam; Balapuwaduge, Indika A.M. & Dash, Soumya P. (2024). Secure and Lightweight Communication Protocol for Wake-up Radio Enabled Internet of Things. I Tran, Kim-Phuc; Li, Shujun; Heuchenne, Cédric & Thu-Huong, Truong (Red.), The 7th International Conference on Safety and Security with IoT. Springer. ISSN 9783031530289. s. 3–16. doi: 10.1007/978-3-031-53028-9_1. Fulltekst i vitenarkiv
• Konara, Konara Mudiyanselage Sandun Y.; Kolhe, Mohan Lal; Ulltveit-Moe, Nils & Balapuwaduge, Indika A.M. (2023). Reliability Enhancement of Fast Charging Station under Electric Vehicle Supply Equipment Failures and Repairs. Energies. 16(6). doi: 10.3390/en16062933. Fulltekst i vitenarkiv Vis sammendrag

  This work focuses on the enhancement of the charging reliability of both scheduled (SEVs) and opportunistic (UEVs) electric vehicle (EV) users in an EV fast charging station (FCS). The proposed charging coordination strategies allow UEVs to exploit unused charging resources to optimally utilize the limited charging resources of FCS. However, the optimum utilization of limited charging resources of an FCS while assuring a reliable charging process for plugged-in EVs under random failures of electric vehicle supply equipment (EVSE) is a real challenge for the FCS controller. When the FCS admits UEVs in addition to SEVs, assuring a satisfactory quality of service to both EV user categories is also dispensable. Therefore, we analyze the performance of reservation of off-board mobile chargers (MOBCs) to enhance the charging reliability of EV users while achieving high charging resource utilization. This work proposes resource allocation and charging coordination strategies for an FCS where MOBCs are used to enhance the charging reliability of both SEVs and UEVs. Moreover, the proposed dynamic charging resource coordination strategies are analyzed with a continuous time Markov-chain (CTMC). The presented results from the CTMC model demonstrate that the proposed strategies outperform the EV charging process of the FCS in terms of high resource utilization and reliability while guaranteeing a satisfactory quality of service to EV users.

• Konara, Konara Mudiyanselage Sandun Y.; Kolhe, Mohan Lal; Ulltveit-Moe, Nils & Balapuwaduge, Indika A.M. (2023). Optimal Utilization of Charging Resources of Fast Charging Station with Opportunistic Electric Vehicle Users. Batteries. 9(2). doi: 10.3390/batteries9020140. Fulltekst i vitenarkiv Vis sammendrag

  The key challenge with the rapid proliferation of electric vehicles (EVs) is to optimally manage the available energy charging resources at EV fast-charging stations (FCSs). Furthermore, the rapid deployment of fast-charging stations provides a viable solution to the potential driving range anxiety and charging autonomy. Costly grid reinforcements due to extra load caused by fast charging can be omitted using a dedicated energy storage and/or renewable energy system at the FCS. The energy supply and fixed number of EV supply equipment (EVSE) are considered as the limited charging resources of FCS. Amidst various uncertainties associated with the EV charging process, how to optimally utilize limited charging resources with opportunistic ultra-fast charging EV users (UEVs) is studied in this work. This work proposes resource allocation and charging coordination strategies that facilitate UEVs to dynamically exploit these limited charging resources with defined liabilities when pre-scheduled users (SEVs) do not occupy them to utilize limited charging resources maximally. Moreover, the proposed dynamic charging coordination strategies are analyzed with a Monte Carlo simulation (MCS). The presented numerical results reveal that the major drawbacks of under-utilization of limited charging resources by SEVs can be significantly improved through dynamic charging resource allocation and coordination along with UEVs. With the proposed charging coordination strategies in this study, the maximum charging resource utilization of considered FCS with 10 EVSE has been improved to 90%, which bounds to 78% only with SEVs.

• Tivig, Pantelimon-Teodor; Borcoci, Eugen; VOCHIN, MARIUS-CONSTANTIN; Balapuwaduge, Indika A.M. & Li, Frank Yong (2023). Slicing 5G Core Network Based on the Ryu SDN Controller for Everything as a Service, 2023 26th International Symposium on Wireless Personal Multimedia Communications (WPMC). IEEE (Institute of Electrical and Electronics Engineers). ISSN 9798350308907. s. 58–63. doi: 10.1109/WPMC59531.2023.10338844. Fulltekst i vitenarkiv
• Weerasinghe, Thilina Nuwan; Casares-Giner, Vicente; Balapuwaduge, Indika A.M.; Li, Frank Yong & VOCHIN, MARIUS-CONSTANTIN (2022). A Pseudo-Bayesian Subframe based Framework for Grant-Free Massive Random Access in 5G NR Networks, 2022 International Conference on Computer Communications and Networks (ICCCN). IEEE (Institute of Electrical and Electronics Engineers). ISSN 9781665497268. doi: 10.1109/ICCCN54977.2022.9868918. Fulltekst i vitenarkiv
• Contu, Cosmin; Ciobanu, Andra-Isabela-Elena; Borcoci, Eugen; VOCHIN, MARIUS-CONSTANTIN; Balapuwaduge, Indika A.M. & Topoloi, Silviu [Vis alle 7 forfattere av denne artikkelen] (2022). Deploying Use Case Specific Network Slices Using An OSM Automation Platform, 2022 25th International Symposium on Wireless Personal Multimedia Communications (WPMC). IEEE (Institute of Electrical and Electronics Engineers). ISSN 9781665473187. s. 387–391. doi: 10.1109/WPMC55625.2022.10014883. Fulltekst i vitenarkiv Vis sammendrag

  Network slicing is a novel fifth generation (5G) concept that enables operators to create logical networks (slices), each dedicated to certain specific applications, on top of a common network infrastructure, computation and storage resources. These slices are logically isolated from each other with respect to network performance and security, providing services to vertical industries and various use cases. Accordingly, an orchestrator is needed in order to manage network resources for various slices. Among different orchestrators that have been developed, open source MANO (OSM) appears as a popular platform, providing a software stack for slice developers. In this paper, we present an implementation of deploying network slices based on the OSM automation platform and report preliminary experiments that have been performed. To validate our implementation, a specific media streaming use case has been selected and a slice with three pre-configured network services that contain a media server has been created.

• Weerasinghe, Thilina Nuwan; Giner, Vicente Casares; Balapuwaduge, Indika A.M. & Li, Frank Yong (2021). Priority Enabled Grant-Free Access With Dynamic Slot Allocation for Heterogeneous mMTC Traffic in 5G NR Networks. IEEE Transactions on Communications. ISSN 0090-6778. 69(5). doi: 10.1109/TCOMM.2021.3053990. Fulltekst i vitenarkiv Vis sammendrag

  Although grant-based mechanisms have been a predominant approach for wireless access for years, the additional latency required for initial handshake message exchange and the extra control overhead for packet transmissions have stimulated the emergence of grant-free (GF) transmission. GF access provides a promising mechanism for carrying low and moderate traffic with small data and fits especially well for massive machine type communications (mMTC) applications. Despite a surge of interest in GF access, how to handle heterogeneous mMTC traffic based on GF mechanisms has not been investigated in depth. In this paper, we propose a priority enabled GF access scheme which performs dynamic slot allocation in each 5G new radio subframe to devices with different priority levels on a subframe-by-subframe basis. While high priority traffic has access privilege for slot occupancy, the remaining slots in the same subframe will be allocated to low priority traffic. To evaluate the performance of the proposed scheme, we develop a two-dimensional Markov chain model which integrates these two types of traffic via a pseudo-aggregated process. Furthermore, the model is validated through simulations and the performance of the scheme is evaluated both analytically and by simulations and compared with two other GF access schemes.

• Vithanage, Dinithi; Balapuwaduge, Indika A.M.; Li, Frank Yong & Casares-Giner, Vicente (2021). Cell Association for MTC Devices in 5G Networks: Schemes and Performance Evaluation, 2021 Joint European Conference on Networks and Communications & 6G Summit (EuCNC/6G Summit). IEEE (Institute of Electrical and Electronics Engineers). ISSN 9781665415262. s. 1–6. doi: 10.1109/EuCNC/6GSummit51104.2021.9482587. Fulltekst i vitenarkiv Vis sammendrag

  Fifth generation (5G) networks offer tremendous opportunities for Internet of things applications by facilitating massive machine-type communications (MTC). As many MTC devices are battery powered and intend to stay often in the sleep or power-saving mode, cell (re)association needs to be performed when a device wakes up. On the other hand, 5G networks are usually deployed as heterogeneous networks consisting of both macro and small cells under which a single device may be covered by multiple radio access technologies (RATs) simultaneously. Therefore, it is imperative to design effective cell association schemes for the purpose of efficient connectivity and resource utilization, especially when a device has multiple connectivity options. In this paper, three cell association schemes are proposed by considering a network scenario where multiple cells and different RATs are available for MTC devices. To perform cell association, received signal strength, channel occupancy status of neighboring cells, and directed handoff capability are considered as the criteria for our scheme design. Through analysis and extensive simulations, we demonstrate that superior system performance could be achieved for a given network by employing a suitable scheme that integrates multiple criteria and considers performance tradeoff.

• Søraa, Aasmund; Weerasinghe, Thilina Nuwan; Balapuwaduge, Indika A.M. & Li, Frank Yong (2020). Preamble Transmission Prediction for mMTC Bursty Traffic: A Machine Learning based Approach. I NN, NN (Red.), 2020 IEEE Global Communications Conference (GLOBECOM). IEEE (Institute of Electrical and Electronics Engineers). ISSN 9781728182988. doi: 10.1109/GLOBECOM42002.2020.9322633. Fulltekst i vitenarkiv
• Weerasinghe, Thilina Nuwan; Balapuwaduge, Indika A.M. & Li, Frank Young (2020). Priority-based initial access for URLLC traffic in massive IoT networks: Schemes and performance analysis. Computer Networks. ISSN 1389-1286. 178. doi: 10.1016/j.comnet.2020.107360. Fulltekst i vitenarkiv Vis sammendrag

  At a density of one million devices per square kilometer, the10’s of billions of devices, objects, and machines that form a massive Internet of things (mIoT) require ubiquitous connectivity. Among a massive number of IoT devices, a portion of them require ultra-reliable low latency communication (URLLC) provided via fifth generation (5G) networks, bringing many new challenges due to the stringent service requirements. Albeit a surge of research efforts on URLLC and mIoT, access mechanisms which include both URLLC and massive machine type communications (mMTC) have not yet been investigated in-depth. In this paper, we propose three novel schemes to facilitate priority-based initial access for mIoT/mMTC devices that require URLLC services while also considering the requirements of other mIoT/mMTC devices. Based on a long term evolution-advanced (LTEA) or 5G new radio frame structure, the proposed schemes enable device grouping based on device vicinity or/and their URLLC requirements and allocate dedicated preambles for grouped devices supported by flexible slot allocation for random access. These schemes are able not only to increase the reliability and minimize the delay of URLLC devices but also to improve the performance of all involved mIoT devices. Furthermore, we evaluate the performance of the proposed schemes through mathematical analysis as well as simulations and compare the results with the performance of both the legacy LTE-A based initial access scheme and a grant-free transmission scheme.

• Weerasinghe, Thilina Nuwan; Balapuwaduge, Indika A.M.; Li, Frank Young & Giner, Vicente Casares (2020). MDP-based Resource Allocation for Uplink Grant-free Transmissions in 5G New Radio. IEEE Wireless Communications and Networking Conference. ISSN 1525-3511. doi: 10.1109/WCNC45663.2020.9120656. Fulltekst i vitenarkiv Vis sammendrag

  The diversity of application scenarios in 5G mobile communication networks calls for innovative initial access schemes beyond traditional grant-based approaches. As a novel concept for facilitating small packet transmission and achieving ultra-low latency, grant-free communication is attracting lots of interests in the research community and standardization bodies. However, when a network consists of both grant based and grant-free based end devices, how to allocate slot resources properly between these two categories of devices remains as an unanswered question. In this paper, we propose a Markov decision process based scheme which dynamically allocates grant-free resources based on a specific reliability or priority requirement. The performance of the proposed scheme is evaluated via both analysis and simulations under various traffic arrival conditions.

• Mendis, Handunneththi V. Kalpanie; Balapuwaduge, Indika A.M. & Li, Frank Yong (2019). Dependability-Based Reliability Analysis in URC Networks: Availability in the Space Domain. IEEE/ACM Transactions on Networking. ISSN 1063-6692. 27(5), s. 1915–1930. doi: 10.1109/TNET.2019.2934826. Fulltekst i vitenarkiv Vis sammendrag

  Ultra-reliable low latency communication (URLLC), which refers to achieving almost 100% reliability at a certain (satisfactory) level of services and stringent latency, is one of the key requirements for 5G networks. However, most prior studies on reliable communication did not address space domain analysis. Neither were they pursued from a dependability perspective. This paper addresses the ultra-reliable communication (URC) aspect of URLLC and aims at advocating the concept of URC from a dependability perspective in the space domain. We perform in-depth analysis on URC considering both the spatial characteristics of cell deployment and user distributions, as well as service requirements. We first introduce the concepts of cell availability and system availability in the space domain, then perform connectivity-based availability analysis by considering a Voronoi tessellation where base stations (BSs) are deployed according to a certain distribution. Moreover, we investigate the relationship between signal-to-interference-plus-noise ratio (SINR), user requirement, and achievable cell or system availability by employing both Poisson point process (PPP) and determinantal point process (DPP) BS distributions. For SINR-based availability analysis, coverage contours are identified. Considering further the user distribution in a region of interest, expressions for system availability are derived from users’ perspective. Furthermore, we propose an algorithm which could be used for availability improvement based on the calculated availability level. Numerical results obtained considering diverse network scenarios and cell deployments with multiple cells and multiple topologies illustrate the achievable availability under various circumstances.

• Weerasinghe, Thilina Nuwan; Balapuwaduge, Indika A.M. & Li, Frank Yong (2019). Time-Space Domain Availability Analysis Under Reliability Impairments. IEEE Networking Letters. 1(3), s. 103–106. doi: 10.1109/LNET.2019.2916909. Fulltekst i vitenarkiv Vis sammendrag

  Availability and reliability are two essential metrics for the design, deployment, and operation of future ultra-reliable low latency communication (URLLC) networks. Despite a vast amount of research efforts toward URLLC, very little attention has been made on the ultra-reliable communication (URC) aspect of URLLC from a dependability perspective. As an effort toward achieving anytime and anywhere communication, this letter consolidates a dependability theory-based availability concept for individual users by taking into account reliability impairments that affect URC in both spatial and temporal domains. To this end, we perform per-user availability analysis by considering channel status and user mobility patterns in a Poisson Voronoi network.

• Weerasinghe, Thilina Nuwan; Balapuwaduge, Indika A.M. & Li, Frank Yong (2019). Preamble Reservation Based Access for Grouped mMTC Devices with URLLC Requirements, 2019 IEEE International Conference on Communications (ICC). IEEE (Institute of Electrical and Electronics Engineers). ISSN 9781538680889. doi: 10.1109/ICC.2019.8761430. Fulltekst i vitenarkiv Vis sammendrag

  Ultra-reliable low latency communication (URLLC) and massive machine type communications (mMTC) are two of the three major technological pillars in 5G. For medium access in mMTC scenarios, e.g., smart cities, a major bottleneck for achieving reliable access is channel congestion due to LTE-A based random access. Hence, priority-based access schemes are preferred in order to provide reliable and low latency access for mMTC devices in 5G networks. In this paper, we categorize the devices covered inside a cell into grouped and non-grouped sets and propose a preamble reservation based 2-step access scheme where grouped devices gain network access via a designated group leader using reserved preambles. Through analysis and simulations, we demonstrate that the proposed scheme enables ultra-reliable and low latency access for grouped devices while improving the performance of non-grouped devices through proper configuration of parameters.

• Balapuwaduge, Indika A.M. & Li, Frank Yong (2019). Hidden Markov Model Based Machine Learning for mMTC Device Cell Association in 5G Networks, 2019 IEEE International Conference on Communications (ICC). IEEE (Institute of Electrical and Electronics Engineers). ISSN 9781538680889. doi: 10.1109/ICC.2019.8761913. Fulltekst i vitenarkiv Vis sammendrag

  Massive machine-type communication (mMTC) is expected to play a pivotal role in emerging 5G networks. Considering the dense deployment of small cells and the existence of heterogeneous cells, an MTC device can discover multiple cells for association. Under traditional cell association mechanisms, MTC devices are typically associated with an eNodeB with highest signal strength. However, the selected eNodeB may not be able to handle mMTC requests due to network congestion and overload. Therefore, reliable cell association would provide a smarter solution to facilitate mMTC connections. To enable such a solution, a hidden Markov model (HMM) based machine learning (ML) technique is proposed in this paper to perform optimal cell association.

• Weerasinghe, Thilina Nuwan; Balapuwaduge, Indika A.M. & Li, Frank Yong (2019). Supervised Learning based Arrival Prediction and Dynamic Preamble Allocation for Bursty Traffic. I Lou, Wenjing; Pau, Giovanni & Wolf, Tilman (Red.), Conference on Computer Communications, INFOCOM 2019. IEEE (Institute of Electrical and Electronics Engineers). ISSN 9781728105154. doi: 10.1109/INFOCOMWKSHPS47286.2019.9093789. Fulltekst i vitenarkiv Vis sammendrag

  Achieving ultra-reliable low latency communications (URLLC) in massive machine type communication networks requires novel medium access mechanisms to accommodate a huge number of traffic arrivals. Random access based on LTE-A suffers from collisions and long latency when two or more devices select the same preamble to initiate channel access simultaneously and this problem becomes severe in mMTC networks. In this paper, we propose a machine learning based scheme that allows an eNB to predict the number of arrivals at each random access slot and allocate preambles accordingly. We demonstrate that, by combining arrival prediction with group based dynamic preamble reservation, the grouped devices are able to achieve URLLC under bursty traffic conditions and meanwhile the performance of non-grouped devices is also improved.

• Balapuwaduge, Indika A.M. & Li, Frank Yong (2018). A Joint Time-Space Domain Analysis for Ultra-Reliable Communication in 5G Networks. IEEE International Conference on Communications. ISSN 1550-3607. 2018-May, s. 1–6. doi: 10.1109/ICC.2018.8422742. Fulltekst i vitenarkiv
• Balapuwaduge, Indika A.M.; Li, Frank Yong & Pla, Vicent (2018). Dynamic Spectrum Reservation for CR Networks in the Presence of Channel Failures: Channel Allocation and Reliability Analysis. IEEE Transactions on Wireless Communications. ISSN 1536-1276. 17(2), s. 882–898. doi: 10.1109/TWC.2017.2772240. Fulltekst i vitenarkiv Vis sammendrag

  Providing channel access opportunities for new service requests and guaranteeing continuous connections for ongoing flows until service completion are two challenges for service provisioning in wireless networks. Channel failures, which are typically caused by hardware and software failures or/and by intrinsic instability in radio transmissions, can easily result in network performance degradation. In cognitive radio networks (CRNs), secondary transmissions are inherently vulnerable to connection breaks due to licensed users’ arrivals as well as channel failures. To explore the advantages of channel reservation on performance improvement in error-prone channels, we propose and analyze a dynamic channel reservation (DCR) algorithm and a dynamic spectrum access (DSA) scheme with three access privilege variations. The key idea of the DCR algorithm is to reserve a dynamically adjustable number of channels for the interrupted services to maintain service retainability for ongoing users or to enhance channel availability for new users. Furthermore, the DCR algorithm is embedded in the DSA scheme enabling spectrum access of primary and secondary users with different access privileges based on access flexibility for licensed shared access. The performance of such a CRN in the presence of homogeneous and heterogeneous channel failures is investigated considering different channel failure and repair rates.

• Weerasinghe, Thilina Nuwan; Balapuwaduge, Indika A.M. & Li, Frank Yong (2018). Per-user availability for ultra-reliable communication in 5G: Concept and analysis, 2018 IEEE Wireless Communications and Networking Conference (WCNC). IEEE (Institute of Electrical and Electronics Engineers). ISSN 9781538617342. doi: 10.1109/WCNC.2018.8377200. Fulltekst i vitenarkiv
• Jalali, Elmira; Balapuwaduge, Indika A.M.; Li, Frank Young & Pla, Vicent (2017). A dynamic channel access strategy for underlay cognitive radio networks: Markov modelling and performance evaluation. Transactions on Emerging Telecommunications Technologies. ISSN 1124-318X. 28(1). doi: 10.1002/ett.2928. Fulltekst i vitenarkiv
• Balapuwaduge, Indika A.M.; Li, Frank Young & Pla, Vicent (2017). System Times and Channel Availability for Secondary Transmissions in CRNs: A Dependability Theory based Analysis. IEEE Transactions on Vehicular Technology. ISSN 0018-9545. 66(3), s. 2771–2788. doi: 10.1109/TVT.2016.2585200. Fulltekst i vitenarkiv Vis sammendrag

  Reliability is of fundamental importance for the performance of secondary networks in cognitive radio networks (CRNs). To date, most studies have focused on predicting reliability parameters based on prior statistics of traffic patterns from user behavior. In this paper, we define a few reliability metrics for channel access in multi-channel CRNs which are analogous to the concepts of reliability and availability in the classical dependability theory. Continuous time Markov chains (CTMC) are employed to model channel available and unavailable time intervals based on channel occupancy status. The impact on user access opportunities based on channel availability is investigated by analyzing the steady state channel availability and several system times such as mean channel available time and mean time to first channel unavailability. Moreover, the complementary cumulative distribution function for channel availability is derived by applying the uniformization method and it is evaluated as a measure of guaranteed availability for channel access by secondary users. The preciseness and the correctness of the derived analytical models are validated through discrete-event based simulations. We believe that the reliability metric definitions and the analytical models proposed in this paper have their significance for reliability and availability analysis in CRNs.

• Balapuwaduge, Indika A.M.; Li, Frank Yong & Pla, Vicent (2016). Significance of channel failures on network performance in CRNs with reserved spectrum. I Bregni, Stefano & Fonseca, Nelson (Red.), IEEE International Conference on Communications (ICC 2016). IEEE Sarnoff Symposium. ISSN 9781479966646. doi: 10.1109/ICC.2016.7510891. Fulltekst i vitenarkiv Vis sammendrag

  It is well understood that in wireless networks, channel failures, which are typically caused by equipment or power failures as well as intrinsic features in radio transmissions, such as fading and shadowing, can easily result in network performance degradation. Therefore, fast recovery from channel failures is an important measure that should be incorporated with those networks. Consequently, in a cognitive radio network (CRN), channel failures can cause significant performance degradation in both primary and secondary networks. Instead, retainability, i.e., the capability of providing continuous connection for users must be guaranteed even if a significant network element is disrupted. In this paper, we develop an analytical model to analyze the system performance of CRNs with a focus on random channel failures. In addition to performance analysis under channel failures, a channel reservation scheme is proposed. The scheme can be adopted in dynamic channel access strategies in order to prioritize ongoing sessions over new user requests. Furthermore, optimal channel reservations subject to different performance requirements are also studied.

• Pussewalage, Harsha Gardiyawasam; Ranaweera, Pasika; Oleshchuk, Vladimir & Balapuwaduge, Indika A.M. (2016). Secure Multi-party based Cloud Computing Framework for Statistical Data Analysis of Encrypted Data. I NN, N (Red.), 19th International Conference on Innovations in Clouds, Internet and Networks. IFIP International Federation for Information Processing. ISSN 9783901882814. s. 22–28. Fulltekst i vitenarkiv Vis sammendrag

  Secure multi-party computation (SMC) is a paradigm used to accomplish a common computation among multiple users while keeping the data of each party secret from others. Cloud computing is a next generation computing solution which allows its users to use high speed infrastructure and services provided by cloud service providers (CSP) in a cost effective manner. Therefore, deployment of cloud based architecture for SMCs would aid in improving its performance and efficiency. However, cloud based solutions raises concerns over security of users’ private data, since data is under the control of an external entity when outsourced to cloud platforms. In this paper we have proposed a Secure Multi-party based Cloud Computing Framework which can ensure security, privacy and anonymity of users’ private data. This framework is modeled by considering a scenario which requires outsourcing statistical parameter computation of private sales data of an organization’s sales personnel. The results that we have obtained, provides significant evidence of feasibility of multi-party based cloud computing solutions.

• Balapuwaduge, Indika A.M.; Li, Frank Young; Rajanna, Amogh & Kaveh, Mostafa (2016). Channel Occupancy-Based Dynamic Spectrum Leasing in Multichannel CRNs: Strategies and Performance Evaluation. IEEE Transactions on Communications. ISSN 0090-6778. 64(3), s. 1313–1328. doi: 10.1109/TCOMM.2016.2521723. Fulltekst i vitenarkiv Vis sammendrag

  Spectrum leasing has been proposed as an effective approach for enabling more flexible spectrum utilization in CRNs. In CRNs, a primary network (PN) which consists of multiple primary users (PUs) can lease part of the licensed spectrum to secondary users (SUs) in exchange for operational benefits. The focus of this study is to investigate how and to what extent the PN allows spectrum leasing in CRNs, considering the QoS requirements of the PN and the secondary network (SN). Correspondingly, we propose two dynamic spectrum leasing strategies which can improve the QoS performance of SUs while ensuring sufficient remuneration for PUs. In order to dynamically adjust the portion of leased bandwidth, two forms of leasing algorithms which are based on channel occupancy of the PN and the SN respectively are proposed. Analytical models are developed to characterize system centric performance metrics including capacity, blocking probability and forced termination probability in both networks. Furthermore, a dynamic pricing scheme for spectrum leasing and utility-based resource allocation is introduced. Finally the performance of dynamic leasing is compared quantitatively with that of static leasing and approaches without leasing. Numerical results obtained from both analysis and simulations show that dynamically adjusted spectrum leasing improves network performance.

• Balapuwaduge, Indika A.M.; Rajanna, Amogh; Kaveh, Mostafa & Li, Frank Young (2015). Performance evaluation of three dynamic channel access strategies for spectrum leasing in CRNs, IEEE International Conference on Communications (ICC) 2015. IEEE (Institute of Electrical and Electronics Engineers). ISSN 9781467364324. s. 7570–7575. doi: 10.1109/ICC.2015.7249537. Fulltekst i vitenarkiv Vis sammendrag

  Spectrum leasing in cognitive radio networks (CRNs) allows the primary network (PN) to lease a certain fraction of its licensed bandwidth to the secondary network (SN). The motivation for such a concept is to enhance the performance of SNs while improving channel utilization. Meanwhile, the license owners of the channels can also gain benefits through spectrum leasing in terms of either monetary rewards or cooperative communications. In this paper, we propose three dynamic channel access strategies for spectrum leasing in multi-channel CRNs. A common characteristic of all these strategies is that the priority for channel access over the leased spectrum is given to SNs and the unleased spectrum to PNs respectively. The distinction among these three strategies is at the level of opportunistic or exclusive access to leased and unleased spectra by an SN or a PN. The performance of the proposed strategies is evaluated and compared with each other in terms of several system centric metrics including capacity, blocking probability, forced termination probability and channel utilization efficiency.

• Balapuwaduge, Indika A.M. & Li, Frank Young (2014). System Times and Channel Availability Analyses in Multi-channel Cognitive Radio Networks. I Jamalipour, Abbas & Der-Jiunn, Deng (Red.), ICC 2014 - Proceedings of 2014 IEEE International Conference on Communications. IEEE (Institute of Electrical and Electronics Engineers). ISSN 9781479920037. s. 1320–1325. doi: 10.1109/ICC.2014.6883504. Fulltekst i vitenarkiv Vis sammendrag

  Channel accessibility by a secondary user (SU) in cognitive radio networks (CRNs) depends on the availability of the spectrum based on primary user and other SU activities. A new SU request may be blocked and an ongoing SU service may also be discarded if no sufficient spectrum is available. So far, little work has been done to analyze the reliability and availability aspects of CRNs from the perspective of the dependability theory. In this paper, we introduce the concept of availability for spectrum access in multi-channel CRNs, which is defined as the fraction of time that a CRN can allocate at least the minimum number of required channels for a new SU request. Through a proposed continuous-time discrete-state Markov model, we analyze the performance of CRN channel access schemes in terms of a few reliability-relevant metrics such as mean channel available time and mean time to first channel unavailability. Furthermore numerical results are also presented in this paper and the correctness of the derived theoretical models are verified through simulations.

• Lei, Jiao; Balapuwaduge, Indika A.M.; Li, Frank Young & Pla, Vicent (2014). On the performance of channel assembling and fragmentation in cognitive radio networks. IEEE Transactions on Wireless Communications. ISSN 1536-1276. 13(10), s. 5661–5675. doi: 10.1109/TWC.2014.2322057. Fulltekst i vitenarkiv Vis sammendrag

  Flexible channel allocation may be applied to multichannel cognitive radio networks (CRNs) through either channel assembling (CA) or channel fragmentation (CF). While CA allows one secondary user (SU) occupy multiple channels when primary users (PUs) are absent, CF provides finer granularity for channel occupancy by allocating a portion of one channel to an SU flow. In this paper, we investigate the impact of CF together with CA for SU flows by proposing a channel access strategy which activates both CF and CA and correspondingly evaluating its performance. In addition, we also consider a novel scenario where CA is enabled for PU flows. The performance evaluation is conducted based on continuous time Markov chain (CTMC) modeling and simulations. Through mathematical analyses and simulation results, we demonstrate that higher system capacity can be achieved indeed by jointly employing both CA and CF, in comparison with the CA-only strategies. However, this benefit is obtained only under certain conditions which are pointed out in this paper. Furthermore, the theoretical capacity upper bound for SU flows with both CF and CA enabled is derived when PU activities are relatively static compared with SU flows.

• Balapuwaduge, Indika A.M.; Lei, Jiao; Pla, Vicent & Li, Frank Young (2014). Channel Assembling with Priority-based Queues in Cognitive Radio Networks: Strategies and Performance Evaluation. IEEE Transactions on Wireless Communications. ISSN 1536-1276. 13(2), s. 630–645. doi: 10.1109/TWC.2013.120713.121948. Fulltekst i vitenarkiv Vis sammendrag

  With the implementation of channel assembling (CA) techniques, higher data rate can be achieved for secondary users in multi-channel cognitive radio networks. Recent studies which are based on loss systems show that maximal capacity can be achieved using dynamic CA strategies. However the channel allocation schemes suffer from high blocking and forced termination when primary users become active. In this paper, we propose to introduce queues for secondary users so that those flows that would otherwise be blocked or forcibly terminated could be buffered and possibly served later. More specifically, in a multi-channel network with heterogeneous traffic, two queues are separately allocated to real-time and elastic users and channel access opportunities are distributed between these two queues in a way that real-time services receive higher priority. Two queuing schemes are introduced based on the delay tolerance of interrupted elastic services. Furthermore, continuous time Markov chain models are developed to evaluate the performance of the proposed CA strategy with queues, and the correctness as well as the preciseness of the derived theoretical models are verified through extensive simulations. Numerical results demonstrate that the integration of queues can further increase the capacity of the secondary network and spectrum utilization while decreasing blocking probability and forced termination probability.

• Balapuwaduge, Indika A.M.; Lei, Jiao & Li, Frank Yong (2012). A Markov chain model for performance analysis of VBR voice using multiple thresholds. I Bogucka, Hanna (Red.), European Wireless, 2012. EW. 18th European Wireless Conference. VDE Verlag GmbH. ISSN 9783800734269. Fulltekst i vitenarkiv Vis sammendrag

  Statistical multiplexing is a popular technique used in digital communications in order to increase utilization efficiency of system resources. Variable bit rate (VBR) voice coding is an example of such multiplexing technique and has been widely used in digital telephony. While fixed rate codec allows only a limited number of simultaneous connections, VBR encoding allows the codec to alter its bit rate dynamically, depending on the instantaneous traffic demand and resource utilization status. In this paper, we propose a scheme to increase the number of simultaneous VBR connections for a system with limited number of channels. When there are more calls, the bit rates of the ongoing connections are decreased and new connections are accommodated by the saved bandwidth. Multiple threshold levels are adopted to increase the number of high data rate connections. The system performance of the proposed scheme is analyzed through Markov chain modelling and the developed analytical model is also validated by simulations. Numerical results demonstrate that the concept of multiple thresholds leads to better performance of the system, represented by a higher percentage of high rate calls.

• Balapuwaduge, Indika A.M.; Lei, Jiao & Li, Frank Yong (2012). Complexity Analysis of Spectrum Access Strategies with Channel Aggregation in CR Networks, 2012 IEEE Global Telecommunications Conference -GLOBECOM 2012. IEEE (Institute of Electrical and Electronics Engineers). ISSN 9781467309219. s. 1313–1319. doi: 10.1109/glocom.2012.6503292. Fulltekst i vitenarkiv

Se alle arbeider i NVA

• Jayasekara, Buddhi; Balapuwaduge, Indika A.M. & Li, Frank Yong (2023). Dynamic Sensitivity Control for Mitigating Hidden and Exposed Terminals in WiFi 7 Networks. Fulltekst i vitenarkiv Vis sammendrag

  The ratification of the IEEE 802.11be WiFi 7 standard amendment has been driven by the need to achieve ultra-high throughput and stringent low-latency for emerging applications. To accomplish this goal, 802.11be relies on various novel techniques. However, the same as in many earlier WiFi standards, two significant challenges known as the hidden terminal problem and the exposed terminal problem still remain, leading to degraded network performance. In order to mitigate the effects of these terminal problems, a promising technique called dynamic sensitivity control (DSC) has been introduced since 802.11ax WiFi 6 networks. This paper proposes an effective algorithm for applying DSC in WiFi 7 networks, aiming to enhance the performance of IEEE 802.11be and 802.11ax stations by reducing collision probabilities resulted from hidden terminals. Through extensive evaluation and analysis, our algorithm showcases its potential in optimizing network performance for future 802.11be deployment. The findings contribute to the seamless integration of WiFi standards in the evolution of wireless communication landscape towards next generation systems.

• Balapuwaduge, Indika A.M. & Li, Frank Yong (2018). Cellular Networks: An Evolution from 1G to 4G, Encyclopedia of Wireless Networks. Springer. ISSN 9783319329031. doi: 10.1007/978-3-319-32903-1_214-1. Fulltekst i vitenarkiv
• Balapuwaduge, Indika A.M. & Li, Frank Yong (2016). Channel Access and Reliability Performance in Cognitive Radio Networks:Modeling and Performance Analysis. Universitetet i Agder. ISSN 9788271178321. Fulltekst i vitenarkiv Vis sammendrag

  According to the facts and figures published by the international telecommunication union (ITU) regarding information and communication technology (ICT) industry, it is estimated that over 3.2 billion people have access to the Internet in 2015 [1]. Since 2000, this number has been octupled. Meanwhile, by the end of 2015, there were more than 7 billion mobile cellular subscriptions in the world, corresponding to a penetration rate of 97%. As the most dynamic segment in ICT, mobile communication is providing Internet services and consequently the mobile broadband penetration rate has reached 47% globally. Accordingly, capacity, throughput, reliability, service quality and resource availability of wireless services become essential factors for future mobile and wireless communications. Essentially, all these wireless technologies, standards, services and allocation policies rely on one common natural resource, i.e., radio spectrum. Radio spectrum spans over the electromagnetic frequencies between 3 kHz and 300 GHz. Existing radio spectrum access techniques are based on the fixed allocation of radio resources. These methods with fixed assigned bandwidth for exclusive usage of licensed users are often not efficient since most of the spectrum bands are under-utilized, either/both in the space domain or/and in the time domain. In reality, it is observed that many spectrum bands are largely un-occupied in many places [2], [3]. For instance, the spectrum bands which are exclusively allocated for TV broadcasting services in USA remain un-occupied from midnight to early morning according to the real-life measurement performed in [4]. In addition to the wastage of radio resources, spectrum under-utilization constraints spectrum availability for other intended users. Furthermore, legacy fixed spectrum allocation techniques are not capable of adapting to the changes and interactions in the system, leading to degraded network performance. Unlike in the static spectrum allocation, a fraction of the radio spectrum is allocated for open access as license-free bands, e.g., the industrial, scientific and medical (ISM) bands (902-928, 2400-2483.5, 5725-5850 MHz). In 1985, the federal communications commission (FCC) permitted to use the ISM bands for private and unlicensed occupancy, however, under certain restrictions on transmission power [5]. Consequently, standards like IEEE 802.11 for wireless local area networks (WLANs) and IEEE 802.15 for wireless personal area networks (WPAN) have grown rapidly with open access spectrum policies in the 2.4 GHz and 5 GHz ISM bands. With the co-existence of both similar and dissimilar radio technologies, 802.11 networks face challenges for providing satisfactory quality of service (QoS). This and the above mentioned spectrum under-utilization issues motivate the spectrum regulatory bodies to rethink about more flexible spectrum access for licenseexempt users or more efficient radio spectrum management. Cognitive radio (CR) is probably the most promising technology for achieving efficient spectrum utilization in future wireless networks.

Se alle arbeider i NVA