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Service-oriented architecture is becoming a major software framework for complex application and it can be dynamically and flexibly composed by integrating existing component web services provided by different providers with standard protocols. The rapid introduction of new web services into a dynamic business environment can adversely affect the service quality and user satisfaction. Therefore, how to leverage, aggregate and make use of individual component's quality of service (QoS) information to derive the optimal QoS of the composite service which meets the needs of users is still an ongoing hot research problem. This study aims at reviewing the advance of the current state-of-the-art in technologies and inspiring the possible new ideas for web service selection and composition, especially with nature-inspired computing approaches. Firstly, the background knowledge of web services is presented. Secondly, various nature-inspired web selection and composition approaches are systematically reviewed and analysed for QoS-aware web services. Finally, challenges, remarks and discussions about QoS-aware web service composition are presented.

This study investigates the integration of Internet of things (IoT) and passive optical network (PON) technologies with an emphasis on their synergy, architectural design, deployment strategies, real-world applications, and related concerns. The paper provides a detailed analysis of how PON could enhance the scalability, performance, and reliability of IoT ecosystems, paving the way for advancements such as smart agriculture, smart cities, and industrial automation. A strong, high-capacity communication infrastructure is required due to the exponential rise in connected devices brought about by the IoT explosive growth. Because of their high bandwidth, low latency, and energy efficiency, passive optical networks, or PONs, have become a promising backbone for facilitating extensive IoTdeployments.

With the rapid development of human society, the urbanization of the world’s population is also progressing rapidly. Urbanization has brought many challenges and problems to the development of cities. For example, the urban population is under excessive pressure, various natural resources and energy are increasingly scarce, and environmental pollution is increasing, etc. However, the original urban model has to be changed to enable people to live in greener and more sustainable cities, thus providing them with a more convenient and comfortable living environment. The new urban framework, the smart city, provides excellent opportunities to meet these challenges, while solving urban problems at the same time. At this stage, many countries are actively responding to calls for smart city development plans. This paper investigates the current stage of the smart city. First, it introduces the background of smart city development and gives a brief definition of the concept of the smart city. Second, it describes the framework of a smart city in accordance with the given definition. Finally, various intelligent algorithms to make cities smarter, along with specific examples, are discussed and analyzed.

Vehicular ad-hoc network (VANET), identified as a mobile ad hoc network MANETs with several added constraints. Basically, in VANETs, the network is established on the fly based on the availability of vehicles on roads and supporting infrastructures along the roads, such as base stations. Vehicles and road-side infrastructures are required to provide communication facilities, particularly when enough vehicles are not available on the roads for effective communication. VANETs are crucial for providing a wide range of safety and non-safety applications to road users. However, the specific fundamental problem in VANET is the challenge of creating effective communication between two fast-moving vehicles. Therefore, message routing is an issue for many safety and non-safety of VANETs applications. The challenge in designing a robust but reliable message dissemination technique is primarily due to the stringent QoS requirements of the VANETs safety applications. This paper investigated various methods and conducted literature on an idea to develop a model for efficient and reliable message dissemination routing techniques in VANET.

Mobile Service selection is an important but challenging problem in service and mobile computing. Quality of service (QoS) predication is a critical step in service selection in 5G network environments. The traditional methods, such as collaborative filtering (CF), suffer from a series of defects, such as failing to handle data sparsity. In mobile network environments, the abnormal QoS data are likely to result in inferior prediction accuracy. Unfortunately, these problems have not attracted enough attention, especially in a mixed mobile network environment with different network configurations, generations, or types. An ensemble learning method for predicting missing QoS in 5G network environments is proposed in this paper. There are two key principles: one is the newly proposed similarity computation method for identifying similar neighbors; the other is the extended ensemble learning model for discovering and filtering fake neighbors from the preliminary neighbors set. Moreover, three prediction models are also proposed, two individual models and one combination model. They are used for utilizing the user similar neighbors and servicing similar neighbors, respectively. Experimental results conducted in two real-world datasets show our approaches can produce superior prediction accuracy.

Adoption of Software-Defined Networks(SDN) as a new networking paradigm, promises solutions for Quality of Service(QoS) management issues raised at the service providers level due to the massive increase in connected devices (e.g., Servers, Mobile devices, M2M, Things, etc.), traffic in between, and the diverse user and service demands (e.g., delay, bandwidth, etc.). Although its advantage in network control flexibility compared to traditional networking, SDN still requires a design of robust and fast QoS guaranteeing routing algorithms due to its central control computation overhead. In this article, we present a new QoS-aware routing algorithm designed to work on top of SDN and serves delay-sensitive services that require certain delay requirements with low computation time. Such problems are usually modeled as Delay Constrained Least Cost (DCLC) problem which is a well-known NP-hard problem. We adopted the Lagrangian relaxation-based approach that incorporates the delay constraint into the objective cost function to solve the DCLC problem. Differently than existing Lagrangian relaxation-based algorithms, we designed our algorithm to reduce the solution search space by exploiting the problem lower-bound cost and delay paths. Moreover, we defined three different constraint tightness factors inferred from the problem current state to avoid extra non-useful Dijkstra calls. To improve the solution quality, we propose a novel approach that use state information obtained from previous optimization iterations to obtain a small-size network subgraph. Then it search the obtained subgraph for a better solution that the Lagrangian relaxation-based approach may miss. We performed an extensive python-based simulation to evaluate the performance of MODLARAC and compared it with two Lagrangian relaxation-based heuristic algorithms proposed in the literature to solve the DCLC problem, LARAC, and BiLAD algorithms. The obtained results showed improvement up to a 15% reduction in internal Dijkstra calls count with about a 2% increase in the total path cost compared to those obtained by the optimal solution.

5G networks support emerging high-speed and low-latency applications, such as remote healthcare and connected cars. Such applications require a consistent quality of service (QoS) to be supported by the underlying optical networks. A combination of spatio-temporal graph neural networks (STGNNs) and twin-delayed deep deterministic policy gradient (TD3), with modifications, is proposed here to solve the problem of QoS optimization through metrics, such as delay, throughput, and jitter. The STGNNs extract the dynamic topology-related features from the network. Modified TD3 helps in learning an adaptive routing policy for optimization of QoS metrics. The proposed model, labelled as spatio-temporal optical network recurrent model with TD3 (STORM-TD3) is validated through simulation. Compared to DDPG, the existing approach, it reduces the end-to-end delay by 9 %, jitter by 1.65 %, maintaining the same level of throughput, and is recommended for deployment in 5G optical networks for QoS optimization.

Service-based systems that are dynamically composed at runtime to provide complex, adaptive functionality are currently one of the main development paradigms in software engineering. However, the Quality of Service (QoS) delivered by these systems remains an important concern, and needs to be managed in an equally adaptive and predictable way. To address this need, we introduce a novel, tool-supported framework for the development of adaptive service-based systems called QoSMOS (QoS Management and Optimization of Service-based systems). QoSMOS can be used to develop service-based systems that achieve their QoS requirements through dynamically adapting to changes in the system state, environment, and workload. QoSMOS service-based systems translate high-level QoS requirements specified by their administrators into probabilistic temporal logic formulae, which are then formally and automatically analyzed to identify and enforce optimal system configurations. The QoSMOS self-adaptation mechanism can handle reliability and performance-related QoS requirements, and can be integrated into newly developed solutions or legacy systems. The effectiveness and scalability of the approach are validated using simulations and a set of experiments based on an implementation of an adaptive service-based system for remote medical assistance.

In this paper, 5G slicing networks are proposed to be deployed to address the issues associated with current communication networks in power grid systems and to enable smart grid applications. 5G slice architecture and the corresponding schemes including radio resource reservation, QoS scheduling strategy, VLAN, VPN and 5QI are applied for the access network, the transport network and the core network in the system, based on which a real 5G slicing network is implemented for smart grid applications. It is shown by field trial that the performance requirement regarding service isolation, bandwidth, delay and reliability required by various smart grid applications can be satisfied using the proposed schemes in the real system.

Addressing the recent trend of the massive demand for resources and ubiquitous use for all citizens has led to the conceptualization of technologies such as the Internet of Things (IoT) and smart cities. Ubiquitous IoT connectivity can be achieved to serve both urban and underserved remote areas such as rural communities by deploying 5G mobile networks with Low Power Wide Area Network (LPWAN). The current architectures will not offer flexible connectivity to many IoT applications due to high service demand, data exchange, emerging technologies, and security challenges. Hence, this paper explores various architectures that consider a hybrid 5G-LPWAN-IoT and Smart Cities. This includes security challenges as well as endogenous security and solutions in 5G and LPWAN-IoT. The slicing of virtual networks using software-defined network (SDN)/network function virtualization (NFV) based on the different quality of service (QoS) to satisfy different services and quality of experience (QoE) is presented. Also, a strategy that considers the implementation of 5G jointly with Weightless-N (TVWS) technologies to reduce the cell edge interference is considered. Discussions on the need for ubiquity connectivity leveraging 5G and LPWAN-IoT are presented. In addition, future research directions are presented, including a unified 5G network and LPWAN-IoT architecture that will holistically support integration with emerging technologies and endogenous security for improved/secured smart cities and remote areas IoT applications. Finally, the use of LPWAN jointly with low earth orbit (LEO) satellites for ubiquitous IoT connectivity is advocated in this paper.