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- Hypermedia APIs for the Web of ThingsPublication . Martins, Jaime; Mazayev, Andriy; Correia, NoƩliaThe Web of Things is a new and emerging concept that defines how the Internet of Things can be connected using common Web technologies, by standardizing device interactions on upper-layer protocols. Even for devices that can only communicate using proprietary vendor technologies, upper-layer protocols can generally provide the necessary contact points for a high degree of interoperability. One of the major development issues for this new concept is creating efficient hypermedia-enriched application programming interfaces (APIs) that can map physical Things into virtual ones, exposing their properties and functionality to others. This paper does an in-depth comparison of the following six hypermedia APIs: 1) the JSON Hypertext Application Language from IETF; 2) the Media Types for Hypertext Sensor Markup from IETF; 3) the Constrained RESTful Application Language from IETF'; 4) the Web Thing Model from Evrythng; 5) the Web of Things Specification from W3C; and 6) the Web Thing API from Mozilla.
- Spectrum sharing for LTE and 5G-NR coexistencePublication . Busari, Sherif Adeshina; Correia, NoƩlia; Saghezchi, Firooz B.; Mumtaz, Shahid; Rodriguez, JonathanSpectrum sharing provides a rapid migration pathway toward 5G by enabling the coexistence of 4G LTE and 5G new radio (NR) that share the same spectrum. Due to significant differences in the LTE and 5G-NR air interfaces, several enablers are required to facilitate the spectrum sharing. In this study, we explore the coexistence features and investigate their impacts on network performance. For static and dynamic spectrum sharing scenarios, we assess the impacts of different spectrum sharing ratios, user ratios, MIMO configurations, mixed numerology profiles and traffic patterns on the user throughput and network capacities of spectrum sharing networks, compared with the LTE only and 5G-NR only networks with exclusive spectrum access. The key results show that spectrum sharing leads to a marginal capacity gain over LTE only network and achieves considerably lower capacity than the 5G-NR only network. Also, the results show that mixed numerology profiles between the LTE and 5G-NR lead to capacity losses due to inter-numerology interference. In addition, user and spectrum sharing ratios between LTE and 5G-NR have critical impacts on performance. Reduced spectrum per device as the number of 5G devices increases, higher signaling overhead and higher scheduling complexity are other limiting factors for spectrum sharing networks. The results show limited capacity benefits and reinforce spectrum sharing between LTE and 5G-NR as mainly an evolutionary path to accommodate 5G users in the same LTE spectrum while migrating to the fully-fledged 5G networks. For significant capacity increase, other features such as carrier aggregation, overlay of small cells and higher order MIMO would need to be incorporated into the network.
- Performance evaluation of radio resource schedulers in LTE and 5G NR two-tier HetNetsPublication . Busari, Sherif Adeshina; Correia, NoƩlia; Mumtaz, Shahid; Rodriguez, Jonathan; Saghezchi, Firooz B.Network performance is critically dependent on the employed radio resource scheduler (RRS). The impact becomes even more significant in 5G ultra-dense networks due to the challenges of complicated base station distribution, user association, load balancing and inter-cell interference, among others. Using a combination of three popular schedulers (i.e., round robin (RR), proportional fairness (PF) and best channel quality indicator (BCQI)), we evaluate, in this work, the performance of two-tier heterogeneous networks where the different tiers employ the same or different RRSs. Using user throughput, cell capacity and system fairness as metrics, the results show that, on one hand, the average user throughput-system fairness tradeoff favours the use of the RR-PF combination (where the macrocell tier employs RR while the small cell tier uses PF). On the other hand, the BCQI-BCQI combination produces the highest network capacity, principally from about 5-10% of the total users, thereby sacrificing fair allocation of resources among the users. The results show that there is no globally optimal RRS combination across the metrics. As the mobile network operators have the freedom to deploy schedulers as they deem fit, the RRS combination can be selected to satisfy the performance targets of the respective use cases and deployment scenarios.
- GACN: Self-clustering genetic algorithm for constrained networksPublication . A. Martins, J.; Mazayev, Andriy; Correia, NoƩlia; Schutz, G.; Barradas, A.Extending the lifespan of a wireless sensor network is a complex problem that involves several factors, ranging from device hardware capacity (batteries, processing capabilities, and radio efficiency) to the chosen software stack, which is often unaccounted for by the previous approaches. This letter proposes a genetic algorithm-based clustering optimization method for constrained networks that significantly improves the previous state-of-the-art results, while accounting for the specificities of the Internet engineering task force, Constrained RESTful Environment (CoRE), standards for data transmission and specifically relying on CoRE interfaces, which fit this purpose very well.
- Resource allocation model for sensor clouds under the sensing as a service paradigmPublication . Guerreiro, Joel; Rodrigues, Luis; Correia, NoƩliaThe Sensing as a Service is emerging as a new Internet of Things (IoT) business model for sensors and data sharing in the cloud. Under this paradigm, a resource allocation model for the assignment of both sensors and cloud resources to clients/applications is proposed. This model, contrarily to previous approaches, is adequate for emerging IoT Sensing as a Service business models supporting multi-sensing applications and mashups of Things in the cloud. A heuristic algorithm is also proposed having this model as a basis. Results show that the approach is able to incorporate strategies that lead to the allocation of fewer devices, while selecting the most adequate ones for application needs.
- Mobility planning of LoRa gateways for edge storage of IoT dataPublication . Carvalho, Rodrigo; Correia, NoƩlia; Al-Tam, FaroqLoRaWAN is now a leading technology in IoT developments due to its low power consumption and simple deployment features. Despite being termed a long-distance technology, its coverage is often hampered by the harsh propagation environment. In such cases, a very cost-effective solution is to use mobile gateways for both data collection and delivery at specific places of the edge, avoiding the need for cellular communication modules. This article addresses the optimization problem of deciding how mobile gateways should move, and which edge devices should be visited (and when) for collected data to be fed into the edge distributed storage, while ensuring data usefulness. This optimization problem of gateway mobility with edge storage is formulated mathematically, and a deep reinforcement learning framework is proposed to solve it. Results show that the proposed framework can achieve near optimal results, in particular for large-dense deployments and not very strict time windows. The proposed deep reinforcement learning solution is able to capture underlying patterns, like device coverage and traffic, without prior knowledge of such information.
- Resource design in constrained networks for network lifetime increasePublication . Correia, NoƩlia; Mazayev, Andriy; Schutz, G.; A. Martins, J.; Barradas, A.As constrained "things" become increasingly integrated with the Internet and accessible for interactive communication, energy efficient ways to collect, aggregate, and share data over such constrained networks are needed. In this paper, we propose the use of constrained RESTful environments interfaces to build resource collections having a network lifetime increase in mind. More specifically, based on existing atomic resources, collections are created/designed to become available as new resources, which can be observed. Such resource design should not only match client's interests, but also increase network lifetime as much as possible. For this to happen, energy consumption should be balanced/fair among nodes so that node depletion is delayed. When compared with previous approaches, results show that energy efficiency and network lifetime can be increased while reducing control/registration messages, which are used to set up or change observations.
- Optimization of mixed numerology profiles for 5G wireless communication scenariosPublication . Correia, NoĆ©lia; Al-Tam, Faroq; Rodriguez, JonathanThe management of 5G resources is a demanding task, requiring proper planning of operating numerology indexes and spectrum allocation according to current traffic needs. In addition, any reconfigurations to adapt to the current traffic pattern should be minimized to reduce signaling overhead. In this article, the pre-planning of numerology profiles is proposed to address this problem, and a mathematical optimization model for their planning is developed. The idea is to explore requirements and impairments usually present in a given wireless communication scenario to build numerology profiles and then adopt one of the profiles according to the current users/traffic pattern. The model allows the optimization of mixed numerologies in future 5G systems under any wireless communication scenario, with specific service requirements and impairments, and under any traffic scenario. Results show that, depending on the granularity of the profiles, the proposed optimization model is able to provide satisfaction levels of 60ā100%, whereas a non-optimized approach provides 40ā65%, while minimizing the total number of numerology indexes in operation.
- On load balancing via switch migration in software-defined networkingPublication . Correia, NoĆ©lia; Al-Tam, FaroqSwitch-controller assignment is an essential task in multi-controller software-deļ¬ned networking. Static assignments are not practical because network dynamics are complex and difļ¬cult to predetermine. Since network load varies both in space and time, the mapping of switches to controllers should be adaptive to sudden changes in the network. To that end, switch migration plays an important role in maintaining dynamic switch-controller mapping. Migrating switches from overloaded to underloaded controllers brings ļ¬exibility and adaptability to the network but, at the same time, deciding which switches should be migrated to which controllers, while maintaining a balanced load in the network, is a challenging task. This work presents a heuristic approach with solution shaking to solve the switch migration problem. Shift and swap moves are incorporated within a search scheme. Every move is evaluated by how much beneļ¬titwillgivetoboththeimmigrationandoutmigrationcontrollers.Theexperimentalresultsshowthat theproposedapproachisabletooutweighthestate-of-artapproaches,andimprovetheloadbalancingresults up toā 14% in some scenarios when compared to the most recent approach. In addition, the results show that the proposed work is more robust to controller failure than the state-of-art methods.
- Deep PC-MAC: a deep reinforcement learning pointer-critic media access protocolPublication . Al-Tam, Faroq; Mazayev, Andriy; Correia, NoƩlia; Rodriguez, J.Developing artificial intelligence (AI) solutions for communication problems is one of the hottest topics nowadays. This article presents Deep PC-MAC, a novel deep reinforcement learning (DRL) solution to solve the fair coexistence problem (FCP) between heterogeneous nodes in the unlicensed bands. It is based on a hybrid architecture between pointer networks (Ptr-nets) and advantage actor-critic (A2C), i.e., pointer-critic architecture. The proposed model allows base stations to fairly share unlicensed bands with incumbent nodes. It jointly protects the incumbent nodes from spectrum starvation and improves key-performance indicators (KPIs). Deep PC-MAC is trained from scratch with zero-knowledge about FCP and experimental results demonstrate its efficiency when compared to a baseline method.