The management of cellular networks and services has evolved due to the rapidly changing demands and complexity of service modeling and management. This paper uses intent-based networking (IBN) as a solution and couples it with contextual information from knowledge graphs (KGs) of network and service components to achieve the objective of service orchestration in cellular networks. Fusing IBN with KGs facilitates an intelligent, flexible, and resilient service orchestration process.We propose an intent completion approach using knowledge graph learning and a mapping model capable of inferring and validating the service intents in the network. Subsequently, these service intents are deployed using available network resources in a simulated fifth generation (5G) non-standalone (NSA) network. The compliance of the deployed intents is monitored, and mutual optimization against their required service key performance indicators is performed using Simultaneous Perturbation Stochastic Approximation (SPSA) and Multiple Gradient Descent Algorithm (MGDA). The numerical results show that the knowledge graph with Gaussian embedding (KG2E) model outperforms other distance-based embedding models for the proposed service KG. Different combinations of strict latency (SL) and non-strict latency (NSL) intents are deployed, and compliance is evaluated for increasing numbers of deployed intents against baseline deployment scenarios. The results show a higher level of compliance for SL intents to target latencies in comparison to NSL intents for the proposed intent deployment and optimization algorithm.

This paper presents a novel approach to network management by integrating intent-based networking (IBN) with knowledge graphs (KGs); thus, creating a more intuitive and efficient pipeline for service orchestration. By mapping high-level business intents onto network configurations using KGs, the system dynamically adapts to network changes and service demands, ensuring optimal performance and resource allocation. This integration facilitates a deeper understanding of network states and dependencies, enabling predictive adjustments and real-time troubleshooting. We utilize knowledge graph embedding (KGE) to acquire context information from the network and service providers. The trained KGE model maps intents to services via service prediction and intent validation processes in the proposed intent processing pipeline. We evaluate the trained model for its efficiency in the service mapping and intent validation tasks using simulated environments and extensive experiments. The service prediction and intent verification accuracy ≥80% is achieved for the trained KGE model on a custom service orchestration intent knowledge graph (IKG) based on TMForum’s intent common model.

In recent years, blockchain technologies have expanded from the finance field to other areas that rely on trust-based solutions. The healthcare industry represents one such area, as digital transformation disrupts relationships between patients, healthcare professionals, and healthcare institutes. Patients and healthcare institutes lack a proficient tool to verify the credentials of medical professionals in a digital environment. Furthermore, healthcare professionals lack a tool where they are in control over their credentials. The first contribution of this paper is a proposal of a solution that leverages the private permissioned Hyperledger Fabric blockchain and smart contracts to provide a source of transparent trust for relationships within the healthcare industry. Second, we pave the ground for GDPR compliance by storing only the hash values on the blockchain. Third, we solve the problem of patient authentication by utilizing cryptographic techniques. Finally, we prove the usability of the proposed solution by implementing a user interface and creating a live deployment.

Intent-driven networks are an essential stepping stone in the evolution of network and service management towards a truly autonomous paradigm. User centric intents provide an abstracted means of impacting the design, provisioning, deployment and assurance of network infrastructure and services with the help of service level agreements and minimum network capability exposure. The concept of Intent Based Networking (IBN) poses several challenges in terms of the contextual definition of intents, role of different stakeholders, and a generalized architecture. In this review, we provide a comprehensive analysis of the state-of-the-art in IBN including the intent description models, intent lifecycle management, significance of IBN and a generalized architectural framework along with challenges and prospects for IBN in future cellular networks. An analytical study is performed on the data collected from relevant studies primarily focusing on the inter-working of IBN with softwarized networking based on NFV/SDN infrastructures. Critical functions required in the IBN management and service model design are explored with different abstract modeling techniques and a converged architectural framework is proposed. The key findings include: (1) benefits and role of IBN in autonomous networking, (2) improvements needed to integrate intents as fundamental policies for service modeling and network management, (3) need for appropriate representation models for intents in domain agnostic abstract manner, and (4) need to include learning as a fundamental function in autonomous networks. These observations provide the basis for in-depth investigation and standardization efforts for IBN as a fundamental network management paradigm in beyond 5G cellular networks.

One of the most challenging services fifth-generation (5G) mobile network is designed to support, is the critical services in-need of very low latency, and/or high reliability. It is now clear that such critical services will also be at the core of beyond 5G (B5G) networks. While 5G radio design accommodates such supports by introducing more flexibility in timing, how efficiently those services could be scheduled over a shared network with other broadband services remains as a challenge. In this paper, we use network slicing as an enabler for network sharing and propose an optimization framework to schedule resources to critical services via puncturing technique with minimal impact on the regular broadband services. We then thoroughly examine the performance of the framework in terms of throughput and reliability through simulation.

Intent-based networking (IBN) provides a promising approach for managing networks and orchestrating services in beyond 5th Generation (B5G) deployments using modern service-based architectures. Public safety (PS) services form the basis of keeping society functional, owing to the responsiveness and avail-ability throughout the network. The provisioning of these services requires efficient and agile network management techniques with low-overhead and embedded intelligence. IBN incorporates the service subscribers in a model-driven approach to provision different user-centric services. However, it requires domain-specific and contextual processing of intents for abstracted management of network functions. This work proposes an intent definition for PS services in B5G networks, as well as a processing and orchestration architecture for a push-to-talk (PTT) use case. The simulation results show that PTT services adhere to the key performance indicators of access time and mouth-to-ear latency bounded by approximately 250 and 150 milliseconds, respectively, with an additional overhead experienced during the intent processing in the range of 20-40 milliseconds. This validates the premise of IBN in providing flexible and scalable management and service orchestration solution for PS next generation networks.

Developing specialized cloud‐based and open‐source testbeds is a practical approach to investigate network slicing functionalities in the fifth‐generation (5G) mobile networks. This paper provides a comprehensive review of most of the existing cost‐efficient and small‐scale testbeds that partially or fully deploy network slicing. First, we present relevant software packages for the three main functional blocks of the ETSI NFV MANO framework and for emulating the access and core network domains. Second, we define primary and secondary design criteria for deploying network slicing testbeds. These design criteria are later used for comparison between the testbeds. Third, we present the state‐of‐the‐art testbeds, including their design objectives, key technologies, network slicing deployment, and experiments. Next, we evaluate the testbeds according to the defined design criteria and present an in‐depth summary table. This assessment concludes with the superiority of some of them over the rest and the most dominant software packages satisfying the ETSI NFV MANO framework. Finally, challenges, potential solutions, and future works of network slicing testbeds are discussed.

Network slicing aims to shape 5G as a flexible, scalable, and demand-oriented network. Research communities deploy small-scale and cost-efficient testbeds in order to evaluate network slicing functionalities. We introduce a novel testbed, called 5GIIK, that provides implementation, management, and orchestration of network slices across all network domains and different access technologies. Our methodology identifies design criteria that are a superset of the features present in other state-of-the-art testbeds and determines appropriate open-source tools for implementing them. 5GIIK is one of the most comprehensive testbeds because it provides additional features and capabilities such as slice provision dynamicity, real-time monitoring of VMs and VNF-onboarding to different VIMs. We illustrate the potentials of the proposed testbed and present initial results.

A code construction and repair scheme for optimal functional regeneration of multiple node failures is presented, which is based on stitching together short MDS codes on carefully chosen sets of points lying on a linearized polynomial. The nodes are connected wirelessly, hence all transmissions by helper nodes during a repair round are available to all the nodes being repaired. The scheme is simple and practical because of low subpacketization, low I/O cost and low computational cost. Achievability of the minimum-bandwidth regenerating (MBR) point, as well as an interior point, on the optimal storage-repair bandwidth tradeoff curve is shown. The subspace properties derived in the paper provide insight into the general properties of functional regenerating codes.

Repair of multiple partially failed cache nodes is studied in a distributed wireless content caching system, where r out of a total of n cache nodes lose part of their cached data. Broadcast repair of failed cache contents at the network edge is studied; that is, the surviving cache nodes transmit broadcast messages to the failed ones, which are then used, together with the surviving data in their local cache memories, to recover the lost content. The trade-off between the storage capacity and the repair bandwidth is derived. It is shown that utilizing the broadcast nature of the wireless medium and the surviving cache contents at partially failed nodes significantly reduces the required repair bandwidth per node.

Minimum-Storage Regenerating (MSR) codes have emerged as a viable alternative to Reed-Solomon (RS) codes as they minimize the repair bandwidth while they are still optimal in terms of reliability and storage overhead. Although several MSR constructions exist, so far they have not been practically implemented mainly due to the big number of I/O operations. In this paper, we analyze high-rate MDS codes that are simultaneously optimized in terms of storage, reliability, I/O operations, and repair-bandwidth for single and multiple failures of the systematic nodes. The codes were recently introduced in [1] without any specific name. Due to the resemblance between the hashtag sign # and the procedure of the code construction, we call them in this paper HashTag Erasure Codes (HTECs). HTECs provide the lowest data-read and data-transfer, and thus the lowest repair time for an arbitrary sub-packetization level α, where α ≤ r⌈k/r⌉, among all existing MDS codes for distributed storage including MSR codes. The repair process is linear and highly parallel. Additionally, we show that HTECs are the first high-rate MDS codes that reduce the repair bandwidth for more than one failure. Practical implementations of HTECs in Hadoop release 3.0.0-alpha2 demonstrate their great potentials.

In a multihop wireless network, it is crucial but challenging to schedule transmissions in an efficient and fair manner. In this paper, a novel distributed node scheduling algorithm, called Local Voting, is proposed. This algorithm tries to semi-equalize the load (defined as the ratio of the queue length over the number of allocated slots) through slot reallocation based on local information exchange. The algorithm stems from the finding that the shortest delivery time or delay is obtained when the load is semi-equalized throughout the network. In addition, we prove that, with Local Voting, the network system converges asymptotically toward the optimal scheduling. Moreover, through extensive simulations, the performance of Local Voting is further investigated in comparison with several representative scheduling algorithms from the literature. Simulation results show that the proposed algorithm achieves better performance than the other distributed algorithms in terms of average delay, maximum delay, and fairness. Despite being distributed, the performance of Local Voting is also found to be very close to a centralized algorithm that is deemed to have the optimal performance.

Bufferless network operation is favorable in many application domains such as industrial networks, on-chip networks and optical packet switching (OPS). The main challenge with zero buffers is the avoidance or handling of contention; indeed, many domain-specific contention resolution techniques have been proposed in the literature. In this paper, we propose a generic combined forward error correction (FEC) and network coding (NC) scheme, which mitigates the negative impact of contentions at the network layer. Specifically, we present a case study for OPS utilizing FEC at the ingress node and NC at an intermediary optical packet switch to reduce packet loss due to contention. Our analysis shows that if used in a smart way, our mechanism can reduce decoding error and packet loss with multiple orders of magnitude while adhering to buffering limitations and meeting delay requirements. We believe that such a combined coding scheme has the potential to be utilized both in OPS (data center and core networks) and other networks where (near-)zero buffers are required.

This paper presents the Coded Packet Transport (CPT) scheme, a novel transport mechanism for Optical Packet/Burst Switched (OPS/OBS) networks. The CPT scheme exploits the combined benefits of source coding by erasure codes and path diversity to provide efficient means for recovering from packet loss due to contentions and path failures, and to provide non-cryptographic secrecy. In the CPT scheme, erasure coding is employed at the OPS/OBS ingress node to form coded packets, which are transmitted on disjoint paths from the ingress node to an egress node in the network. The CPT scheme allows for a unified view of Quality of Service (QoS) in OPS/OBS networks by linking the interactions between survivability, performance and secrecy. We provide analytical models that illustrate how QoS aspects of CPT are affected by the number of disjoint paths, packet overhead and processing delay.

We introduce a definition for Families of Optimal Binary Non-MDS Erasure Codes for [n, k] codes over GF(2), and propose an algorithm for finding those families by using hill climbing techniques over Balanced XOR codes. Due to the hill climbing search, those families of codes have always better decoding probability than the codes generated in a typical Random Linear Network Coding scenario, i.e., random linear codes. We also show a surprising result that for small values of k, the decoding probability of our codes in GF(2) is very close to the decoding probability of the codes obtained by Random Linear Network Coding but in the higher finite field GF(4).