The development of 6th-generation (6G) mobile networks brings advancements in wireless communications, including lower latency, higher data rates, and improved spectral efficiency, as well as enhanced facilitation for the use of Artificial Intelligence (AI) technologies, integrated communications, sensing, and renewable energy sources. To harness this potential, a scalable framework integrating edge and cloud computing is needed to provide a robust computing continuum for various IoT applications and services. This paper analyses the strengths and weaknesses of existing and emerging distributed computing frameworks—ranging from traditional centralized IoT architectures, through fog, edge, and local-edge architectures, to the full three-tier edge–cloud continuum—in terms of IoT service orchestration and diverse application requirements. We emphasize the latest evolutionary step, three-tier edge-cloud continuum, which aims to resolve the most significant limitations of the previous frameworks, recognized in the literature. It enables efficient IoT service orchestration by utilizing distributed resources and computation closer to end users, while taking full advantage of the centralized resources at data centers. We evaluate the maturity of these frameworks, considering factors such as scalability, resource efficiency, adaptability to changes, resource availability, security and privacy, as well as robustness and resilience. Overall, this study aims to serve as a roadmap for researchers, network architects, and industry stakeholders to make informed decisions on implementing the computing continuum in 6G networks.

Artificial intelligence (AI) is increasingly transforming the healthcare sector by enabling advanced automated decision-making. However, implementing Machine Learning (ML) systems in medical imaging applications presents significant challenges, such as ensuring consistent results across different environments, maintaining comprehensive records of experimental processes, and establishing reliable methods for model comparison and evaluation. These issues become more evident as medical AI shifts towards a hybrid Cloud-Edge Continuum (CEC), adding complexity to workload orchestration and performance monitoring across diverse infrastructures. To address these challenges, this work introduces a modular Edge Micro Data Centre (EMDC) architecture that supports a scalable experiment tracking framework designed for AI model deployments in healthcare. The approach extends MLflow with a domain-specific module for medical image segmentation, incorporating several clinically relevant performance metrics. The EMDC architecture enables distributed processing and performance monitoring within a hybrid CEC environment. By aligning MLOps principles with CEC infrastructure, the proposed system facilitates reliable and scalable AI integration into the healthcare sector.

The rapid proliferation of the Internet of Things (IoT) and edge computing devices calls for solutions that deliver low latency, energy efficiency, and robust security-often challenging goals to balance simultaneously. This paper introduces a novel nanoservice-based framework that dynamically adapts to changing demands while achieving sustainable and secure edge operations. By breaking down functionalities into specialized and narrowly scoped nanoservices that are requested only as needed and eliminated when idle, the approach significantly reduces latency and energy usage compared to conventional, more static methods. Moreover, integrating a Zero-Trust Architecture (ZTA) ensures that every component-computational or security-related-is continuously verified and restricted through strict access controls and micro-segmentation. This framework's adaptability extends uniformly to all nanoservices, including those providing security features, thereby maintaining strong protective measures even as workloads and network conditions evolve. Experimental evaluations on IoT devices under varying workloads demonstrate that the proposed approach significantly reduces energy consumption and latency while maintaining security and scalability. These results underscore the potential for an integrated, flexible model that simultaneously addresses energy efficiency, performance, and security-an essential trifecta in future edge computing environments.

In the age of the Internet of Things (IoT) and the expanding computing continuum, it’s crucial to manage and share resources at the edges of networks. This position paper presents a new concept known as ’semantic slicing’. This approach harnesses the power of artificial intelligence (AI), wireless networks, edge computing, and sensing technologies to enable novel applications, optimize resource allocation, and streamline data processing and decision-making across complex systems spanning the computing continuum. Semantic slicing applies a deep understanding of the data and specific application requirements to intelligently allocate resources and distribute processing tasks in the computing continuum. This strategy allows for the creation of systems that are not only more efficient and responsive, but also better equipped to adapt to a variety of applications and services.

The novel concept of factory-as-a-service (FaaS) allows the agility of adapting the manufacturing process by identifying the industry’s supply chain and user requirements. To cater to FaaS, flexibility in networking and cloud services is a must. 5G network slice broker (NSB) is a third-party mediator that caters to networking resource demand from clients to the service providers. Thus, this article introduces a secure blockchain-based NSB to facilitate FaaS. The proposed secure NSB (SNSB) provides secure, cognitive, and distributed network services for resource allocation and security service level agreement (SSLA) formation with coordination of slice managers and SSLA managers. In SNSB, we introduce a federated slice selection algorithm with Stackelberg game model and reinforcement learning algorithm to compute the real time and the optimal unit price and demand level. We provide an extensive implementation and performance evaluation of SNSB using the slice manager and a custom SSLA manager.

Secure and intelligent environments are crucial for fostering future IoT applications such as digital healthcare and Industry 4.0. Such smart environments must enable needed digital services to the respective users ubiquitously and fulfill critical requirements such as ensuring security, privacy, and low latency. This paper summarizes the dissertation work [1] through three major contributions, i) a lightweight biometrics-based user authentication mechanism in the smart and gadget-less healthcare environment, ii) a conceptual three-tier mechanism for secure nodes bootstrapping and secure users access for digital services, and iii) a Blockchain and Edge computing based network architecture for IIoT use case to fulfill the needed requirements such as low-latency, trust management, and security among others. The performance evaluation of the proposed framework is carried out, and the obtained results highlight valuable insight of this work for enabling a secure future hyperconnected environment for various applications.

The deployment of edge computing infrastructure requires a careful placement of the edge servers, with an aim to improve application latencies and reduce data transfer load in opportunistic Internet of Things systems. In the edge server placement, it is important to consider computing capacity, available deployment budget, and hardware requirements for the edge servers and the underlying backbone network topology. In this paper, we thoroughly survey the existing literature in edge server placement, identify gaps and present an extensive set of parameters to be considered. We then develop a novel algorithm, called PACK, for server placement as a capacitated location–allocation problem. PACK minimizes the distances between servers and their associated access points, while taking into account capacity constraints for load balancing and enabling workload sharing between servers. Moreover, PACK considers practical issues such as prioritized locations and reliability. We evaluate the algorithm in two distinct scenarios: one with high capacity servers for edge computing in general, and one with low capacity servers for Fog computing. Evaluations are performed with a data set collected in a real-world network, consisting of both dense and sparse deployments of access points across a city area. The resulting algorithm and related tools are publicly available as open source software.

Blockchain is so far well-known for its potential applications in financial and banking sectors. However, blockchain as a decentralized and distributed technology can be utilized as a powerful tool for immense daily life applications. Healthcare is one of the prominent applications area among others where blockchain is supposed to make a strong impact. It is generating wide range of opportunities and possibilities in current healthcare systems. Therefore, this paper is all about exploring the potential applications of blockchain technology in current healthcare systems and highlights the most important requirements to fulfill the need of such systems such as trustless and transparent healthcare systems. In addition, this work also presents the challenges and obstacles needed to resolve before the successful adoption of blockchain technology in healthcare systems. Furthermore, we introduce the smart contract for blockchain based healthcare systems which is key for defining the pre-defined agreements among various involved stakeholders.

Energy efficiency is a powerful measure for promoting sustainability in technological evolution and ensuring feasible battery life of mobile end-user devices. Peer-to-peer technology provides decentralized and self-organizing, but also energy-inefficient technology for distributing content between devices in networks that scale up almost infinitely. The dissertation [1] summarized in this paper makes four contributions towards enabling energy-aware peer-to-peer networking in mobile environments: 1) an empirical study for understanding the energy consumption characteristics of radio interfaces and typical composition of traffic in peer-to-peer networks, 2) a model for estimating the energy consumption of a mobile device with different traffic profiles, 3) a model for energy-aware load monitoring of mobile peer nodes, and 4) a mobile agent based virtual peers concept for energy-aware sharing of peer responsibilities between peer nodes in a subnet. The results give valuable insight into implementing energy-efficient peer-to-peer systems in mobile environments.

In this demo we present an energy efficient motion detection mechanism for a high-resolution wireless (battery powered) surveillance camera node. We use Raspberry Pi (RPi) as a camera sensor node to demonstrate two scenarios. In the first scenario, the RPi performs motion detection using Pyro-electric InfraRed (PIR) sensor, while in the latter we use an external low-power node to keep the RPi in low power mode and at the same time detect motion using PIR sensor. The main contributions of this demo are the power management implementation, a surveillance application and the evaluation of power consumption between the two scenarios.

With the introduction of novel standardized web technologies such as WebGL, 3D virtual environments (VEs) are making their way into the web. Concurrently, resource rich mobile devices, such as smartphones and tablets, have become the primary access medium for the web. This paper introduces a method called RADE that enables resource-aware P2P-assisted 3D asset delivery in a web browser using WebRTC. Use of P2P technology in 3D asset delivery can (1) decrease the load on 3D asset servers; (2) decrease the application response times; and (3) reduce the operational costs of VE service providers. The performance and resource fairness of RADE was evaluated in real-life wireless networks using a prototype implementation. Based on the results, RADE can significantly reduce the server load and the 3D asset delivery times especially when 3D asset servers are under heavy load. For instance, with a scarce server bandwidth of 2Mbps, use of RADE resulted in 55% shorter 3D asset delivery times on average. Although RADE has been developed for 3D asset delivery, it is applicable for many types of web applications, including video delivery.

In this paper, we propose a novel architecture, called ADHT, that allows the participation of wireless and constrained-capacity M2M devices in a P2P overlay without compromising their battery life. The approach makes P2P-based networking feasible in scenarios where dedicated super-peer nodes are not available or not feasible to use, e.g. when all the participating nodes in a subnet are constrained devices. The concept is based on sharing the peer responsibilities among the nodes within the same subnet using mobile agent-based virtual peers. The mobile agent-based approach enables on-the-fly configurations to further reduce energy consumption in the subnet nodes during runtime. The presented mobile agent composition is both programming language- and platform-independent. Therefore it inherently enables heterogeneous platforms, from the low-power resource-constrained embedded networked devices to the cloud platforms, to operate as the P2P peer. We analyze the power consumption characteristics of the mobile agent-based approach by comparing it with alternative architectures with a numerical analysis.

The Internet of Things presents the user with a novel means of communicating with the Web world through ubiquitous object-enabled networks. Cloud Computing enables a convenient, on demand and scalable network access to a shared pool of configurable computing resources. This paper mainly focuses on a common approach to integrate the Internet of Things (IoT) and Cloud Computing under the name of CloudThings architecture. We review the state of the art for integrating Cloud Computing and the Internet of Things. We examine an IoT-enabled smart home scenario to analyze the IoT application requirements. We also propose the CloudThings architecture, a Cloud-based Internet of Things platform which accommodates CloudThings IaaS, PaaS, and SaaS for accelerating IoT application, development, and management. Moreover, we present our progress in developing the CloudThings architecture, followed by a conclusion.

One challenging problem in Machine-to-Machine (M2M) applications is to efficiently discover the resources provided by a huge number of heterogeneous devices. This paper proposes distributed resource discovery architecture (DRD) for M2M applications. The DRD supports heterogeneous devices in resource description registration and discovery of resource value. It achieves interoperability among heterogeneous devices in disparate networks and enables resource access from the Internet. In the DRD, a resource registration component is designed for storing resource descriptions, a resource discovery component is designed to retrieve resource values on behalf of clients after getting address information by looking up resource descriptions. The DRD utilizes a peer-to-peer overlay to distribute workload and avoid single point of failure. A real-world prototype is implemented and verified with a simple demo. Preliminary evaluation on response time of resource discovery is provided.

We demonstrate interoperable mobile agents for language- and platform-independent wireless sensor network programming, with low-power resource-constrained embedded devices as static nodes and Android-based smartphones as mobile nodes, over disparate networks: 6LoWPAN and Wi-Fi. Representational state transfer architectural principles are applied in agent composition, control and migration and exposing the system resources to the Web: the devices, agents, sensor data, tasks and data processing results. The adaptable agent composition includes the task code in any programming language, the agent migrates according to a resource list and the state, i.e. the intermediate task result, represents the agent as a system resource. Mobile agents are then utilized in two tasks: first to collect light sensor data cooperatively in location, saving the mobile node battery whenever possible, and secondly the magnetometer sensor data with the scanned Wi-Fi access points' signal strength is used to detect groups of mobile nodes moving in the same direction in real-time.

We demonstrate interoperable mobile agents to integrate Internet of Things and wireless sensor networks with resource-constrained low-power embedded networked devices. We introduce adaptable composition for the mobile agent, complying with the Representational State Transfer principles, which are then used for agent migration, controlling the agent and exposing the data, system resources, tasks and services, to the Web. We gather requirements for the system and heterogeneous networked devices and present an application programming interface to enable mobile agents in these systems. The agents are demonstrated in a real-world prototype with smartphones and embedded networked devices, where we utilize a proxy component to expose system resources to the Web for human-machine interactions. Spanning over disparate networks and protocols, the proxy translates messages including the agent composition, between HTTP and Constrained Application Protocol. Lastly, we suggest an evaluation method for the agent communication and migration costs, considering the different types of system resources and utilization.

Machine-to-Machine (M2M) communications emerge to achieve ubiquitous communications among all the networked devices. One challenging problem in M2M applications is to discover the resources provided by the devices efficiently. This challenge arises from two perspectives: (1) a large number of heterogeneous devices co-exist and most of them are constrained devices (e.g., limited processing capability), (2) different communication protocols are utilized to get access to different types of resources provided by the devices (e.g., humidity information provided by a sensor). This paper proposes distributed resource directory architecture for M2M applications, referred to as DRD4M. The DRD4M supports heterogeneous devices using HTTP and CoAP protocols for resource registration and lookup. This enables the interoperability among heterogeneous devices and resource access to constrained devices from disparate network including the Internet. The DRD4M introduces two components: a resource registration component for registering resources and a resource lookup component with caching functionality for handling resource lookup with filtering. A peer-to-peer (P2P) overlay is introduced in DRD4M to connect resource peers to avoid single point of failure. A real-world prototype is implemented and is verified with a demo application. Preliminary performance evaluation in terms of response time of resource lookup is provided.

In this paper, we propose an advanced model, called e-Aware, for estimating how application layer protocol properties affect the energy consumption of mobile devices, operating in 3G (WCDMA) and WLAN (802.11) networks. The main motivation for the model is to facilitate designing energy-efficient networking solutions, by reducing the need for time-consuming measurements with real-life networks and devices. The model makes a distinction between signaling and media transfers due to their different energy consumption characteristics, and takes into account the fundamentals of radio interface properties, such as different energy states and timers controlling them. The model is fine-tuned using device-specific coefficients that are defined according to real-world measurements with actual devices. We have implemented the model and simulated it in Matlab environment. The correct functionality is verified by comparing the results with real-life measurements in identical networking scenarios.

The popularity of community-centric applications has rapidly grown during the recent years. In this paper, we evaluate the robustness of a P2P community management system, where communities are established as autonomous DHT overlays that are advertised in a global DHT overlay. The evaluation is based on the experimental measurements conducted using a DHT-based protocol with two DHT algorithms called Kademlia and Chord. The robustness of the P2P community management system was evaluated with different levels of churn and node activity, in terms of nodes' look-up success ratio, network traffic load and average hop count. The P2P community management system was also compared against a flat DHT structure where all the community related activities are performed in a single DHT overlay. The evaluation results suggest that the P2P community management system performs very well in an environment with high level of churn, the performance improvement being especially significant with Chord.

Distributed Hash Tables (DHTs) have been deployed in a wide variety of peer-to-peer (P2P) networks. While the traditional use of P2P technology is focused around content sharing, the current trend is in applying the P2P technology for new application areas, such as interpersonal communications. Despite active research and standardization efforts, such as the development of Peer-to-Peer Session Initiation Protocol (P2PSIP), there has been little effort to evaluate the suitability of different DHTs for interpersonal communications. As there are significant differences between the requirements of various application types, the task of selecting an appropriate DHT algorithm for a particular application type is not trivial. Therefore an evaluation is needed. In this paper, we compare the performance and efficiency of two popular DHT algorithms, Kademlia and Chord, in P2PSIP environment. We are particularly interested in their messaging overhead and routing performance in different sizes of overlay networks. The results reveal that in identical application scenarios, Kademlia outperforms Chord by shorter lookup path lengths, whereas Chord scales better to larger networks in the terms of messaging cost.

We analyze the performance of a DHT-based P2P overlay network in resource access and overlay maintenance activities. We use a cross-platform implementation of the protocol called P2PP. Mobile systems are the main target platform of our protocol implementation; due to practical reasons, we conduct large-scale evaluations using a server array. The performance metric is the request accomplishment success ratio in the overlay network. The evaluations are conducted in the presence of churn i.e. the peers' continuous activity of joining and leaving the overlay, which is crucial for realistic simulations. The online and offline time-periods of churning peers follow an exponential distribution. In addition to churn, we use overlay size and resource lookup activity as variable parameters. Measurements of request success ratio can be used to approximate the performance of a P2P overlay network and the load inflicted on it, when its number of peers and activity level are known.

Peer-to-Peer (P2P) technologies have many advantages over traditional client/server technologies, including cost- effectiveness, scalability and robustness, due to their decentralized network structure. However, the performance has traditionally been an issue in P2P systems. Especially the higher lookup latencies, when compared with the traditional client/server systems, have been the bottleneck in many P2P systems. In this paper, we propose a truncated pyramid P2P architecture together with an enhanced model, Vertical Tunneling Model (VTM) for improving the lookup performance. The proposed architecture is built on Peer-to-Peer SIP (P2PSIP) network. VTM builds up vertical tunnels between the upper and lower sub-overlays to speed up the service lookup and decrease the session setup delay. Based on the performance analysis and results, it is shown that VTM has better performance compared with the existing systems in average lookup hops, which is about 1/3 of that of the existing systems, the predominance is more evident as the network scale increases.

We evaluate the battery life of mobile devices that act as full-fledged peer nodes in a Kademlia DHT based P2P overlay network. The motivation is to find out how long a mobile peer is able to function in a UMTS or WLAN access network, and how the different parameter settings affect this battery life; this is interesting as mobile access to P2P networks is expected to become common in the near future. The majority of the peers in an overlay are simulated on a server array, while the power measurements are conducted on actual mobile devices. The variable overlay parameters are the number of peers, resource lookup activity, and the level of churn. The chosen values of parameters represent a relatively high amount of activity. In UMTS the measured battery life is approximately 3 hours and in WLAN it is 5 to 10 (most often around 8) hours. We also provide power measurements on sending and receiving UDP packets in UMTS and WLAN, for approximating the power consumption of network protocols without protocol-specific measurements.

We present the effects of different churn models on the performance of structured peer-to-peer (P2P) networks in this paper. Specifically, Exponential distribution (ED), Pareto distribution (PD), and Weibull distribution (WD) are evaluated to provide a comparative analysis. Kademlia-based Peer-to-Peer Protocol (P2PP) is utilized as the underlying signaling protocol. Through simulations, we conclude that the simulated different churn models do not have a significant effect on the performance of the simulated structured P2P network. Quantitatively, ED and PD result in better performance compared to WD from the viewpoints of lookup success rate, mean network traffic load, and mean number of messages.

The need for efficient and scalable data management has increased in the contemporary distributed mobile and fixed networks. Sharing growing amounts of multimedia data stored in autonomous, heterogeneous and distributed equipment such as mobile devices, personal computers, enterprise servers etc. is a trend, especially considering peer-to-peer networking scenarios. In this paper we describe a simple yet extendable analytical model to enable comparison of various aspects of the existing and emerging distributed data management systems. We introduce an abstract model for analyzing service enabler efficiency indicating operational costs for system external and internal parameters. Model is applied to benchmark distributed data management techniques to support optimal design choices, especially considering the design guidelines for data management in mobile P2P environments.

This paper evaluates the feasibility of mobile nodes as peers in a structured peer-to-peer overlay network. Our performance analysis is based on the Peer-to-Peer Protocol (P2PP), which is a peer protocol candidate for the Peer-to-Peer Session Initiation Protocol (P2PSIP). We use both, live-network measurements and simulations, to evaluate two performance metrics: resource lookup success rate and mobile battery duration. While lookup success rate measures P2PP performance in general, battery duration is crucial for mobile use of P2PP. Restricted battery life limits the feasibility of mobile peers. We reveal the tradeoff between lookup success rate and battery duration. Based on the findings it is possible to find more suitable protocol parameters for mobile peers. The battery duration measurements, made with UDP in UMTS and WLAN access networks, are also applicable in the wireless usage of other application-layer protocols.

The seamless and flexible interconnection of the existing and emerging protocols and networks is essential to the success of the new generation mobile applications and services. For exploiting the functional diversity, we have developed a middleware for mobile devices called the Plug-and-Play Application Platform (PnPAP). We have previously studied the Session Initiation Protocol (SIP) as an interconnecting protocol for the PnPAP nodes. In this paper, we analyze the usage of a new variant of SIP called Peer-to-Peer SIP (P2P SIP) for this purpose. Our interconnection architecture utilizes layered (hierarchical) P2P SIP to establish a self-organizing, failure tolerant overlay signaling network between PnPAP nodes. Signaling latency and scalability of the layered P2P SIP signaling is compared in a simulation environment with both the traditional client-server SIP and fully distributed P2P SIP. Simulation results illustrate the benefits of the layered P2P SIP solution where only the supernodes participate to the DHT management, enabling light-weight peer node implementation for mobile nodes.

This paper presents a novel mobile application interaction concept using application supernetworking. With efficient use of middleware, the use of resources can be optimized through so called Supersessions, which is an important factor especially in mobile devices. By implementing application co-operation, the user's awareness of available services can be increased while decreasing the amount of needed user input. Measurement results based on our plug-and-play application platform prototype with application supernetworking show the feasibility of the approach

There are several non-interoperable peer-to-peer (P2P) protocols available today with different functionalities. In order to exploit this functional diversity on mobile devices, we have developed a plug-and-play application platform (PnPAP). PnPAP provides autonomous, dynamic selection between multiple P2P protocols while ensuring the best available network connectivity. In this paper, we introduce methods for utilizing session initiation protocol (SIP) in inter-PnPAP communications. This communication may include downloads of distributed P2P resources such as polymorphic protocol libraries or dynamic state-machine control modules. These components are then used to optimize connectivity management between heterogeneous wireless access networks. In addition, context information may be exchanged between mobile nodes in order to facilitate extended service availability, operability and quality. We analyze the feasibility of merged P2P and All-IP (including SIP) architecture through the novel use of a specialized SIP server and the leveraging of the emerging instant messaging capabilities of SIP. Preliminary measurement results from the prototype implementation on a Symbian platform and test-bed, with overhead and latency analysis, illustrate the feasibility of this approach.

This paper proposes an intelligent mobile middleware utilizing group-based content push with dynamic session startup and plug-and-play features. Solution enhances the distribution of mobile content, such as game applications or multimedia files, within a peer group community. It exploits the social relationships of the user community to enable instant application downloading, installation, and licensing upon incoming connection attempt initiated by another peer group member. In the core of the middleware functionality are dynamic application identification and immediate session startup. This paper presents a use case scenario for a content push procedure. Functional and technical analysis of the novel middleware component are provided. Observations from experimental signaling system setup are mapped with estimates of end-to-end delay budget.

While peer-to-peer (P2P) has emerged as a new hot communication concept among the Internet users, mobile usage of P2P applications is still taking its first steps. This article first elaborates the evolutionary process that P2P architectures are going through. Challenges and requirements for mobile P2P are then identified, followed by a definition of a novel Plug-and-Play Application Platform (PnPAP). This platform enables dynamic selections between diverse P2P and session management protocols while preserving the best available network connectivity through Holistic Connectivity (HCon) management. On-the-fly reconfiguration and run-time parameter optimization can be done with a lightweight interpretable state machine. The concept enables flexible and seamless communications for mobile devices in P2P networks.