One of the recent methods for effectively utilising the available bandwidth of the network as conditions change is in-network packet trimming. It has advantages for applications which rely on low-latency and low-loss, such as video streaming. Packet trimming allows a network node to reduce the size of packets as they travel across the network, by removing some of the content, during the journey of each packet. In our previous work, we presented a system for layered SVC video streaming, and showed how the trimming process can be successfully implemented and utilised as a virtualized edge deployed function. If trimming is needed, there is a task which has to unpack all the video content and meta-data, including associated significance values, then determine which data to remove, and finally repack and rebuilding a new packet. Conversely, a simple scheme for packet trimming, in the form of a basic buffer cutting process, has been implemented in switches. This process keeps the first bytes of a packet, and drops the rest. Here we investigate if a buffer cutting process can be used for layered video, and describe the issues arising and the design aspects needed to adapt from packet rebuilding to packet cutting.

As developments in Beyond 5G/6G continue to accelerate, the requirements of applications that will run on 6G networks will be rapidly increasing accordingly. It is expected that multimedia, which is the most popular network application, will require extra low latency and low loss. New transport mechanisms which take these factors into consideration are being developed in order to cope with these highly demanding requirements. This motivates us to investigate the use of the packet trimming technique, which allows the network to shrink packets, by eliminating some of the content, during their journey. In this paper, we propose an architecture suitable for using packet trimming in 6G. To support this, we present different bandwidth utilization algorithms and evaluate their performance for data transfer and packet trimming using real mobile datasets with highly dynamic bandwidths. This addresses these aspects, as well as providing effective bandwidth utilization compared to traditional dropping of packets.

The utilization of the packet trimming technique as part of 6G has previously been described. It allows a network node to reduce packet sizes, by removing some of the content, during the journey of each packet. This approach has been successful in many ways, but can be limited when there is very little bandwidth. In this paper, we propose an approach using an architecture suitable for 6G, which overcomes some of these issues by removing extra content from the packets, when network conditions are restricted.

Edge Computing harnesses resources close to the data sources to reduce end-to-end latency and allow real-time process automation for verticals such as Smart City, Healthcare and Industry 4.0. Edge resources are limited when compared to traditional Cloud data centres; hence the choice of proper resource management strategies in this context becomes paramount. Microservice and Function as a Service architectures support modular and agile patterns, compared to a monolithic design, through lightweight containerisation, continuous integration/deployment and scaling. The advantages brought about by these technologies may initially seem obvious, but we argue that their usage at the Edge deserves a more in-depth evaluation. By analysing both the software development and deployment lifecycle, along with performance and resource utilisation, this paper explores microservices and two alternative types of serverless functions to build edge real-time IoT analytics. In the experiments comparing these technologies, microservices generally exhibit slightly better end-to-end processing latency and resource utilisation than serverless functions. One of the serverless functions and the microservices excel at handling larger data streams with auto-scaling. Whilst serverless functions natively offer this feature, the choice of container orchestration framework may determine its availability for microservices. The other serverless function, while supporting a simpler lifecycle, is more suitable for low-invocation scenarios and faces challenges with parallel requests and inherent overhead, making it less suitable for real-time processing in demanding IoT settings.

With the deployment of network slicing in fifth generation (5G) systems, telecom operators can partition their physical infrastructure into a number of distinct network services. However, the advantages of network slicing come at the price of higher complexity in operating and managing telecom networks. To cope with such complexity, the ETSI zero-touch network and service management (ZSM) framework is designed as a next-generation management system that aims to ideally have all operational processes and tasks executed automatically. ETSI has defined a procedure to deploy the network-slice-as-a-service (NSaaS) scenario using the ZSM reference architecture. Two important use-cases for a more ambitious NSaaS model are MANO-as-a-service (MANOaaS) and heterogeneous MANO-as-a-service (H-MANOaaS), where multiple instances of the same (MANOaaS) or different (H-MANOaaS) MANO frameworks are deployed over the same physical substrate. We propose a conceptual model for supporting the never-addressed H-MANOaaS use-case. We also offer a blueprint to integrate the MANOaaS and H-MANOaaS use-cases into the ZSM procedures and mechanisms. We then validate the H-MANOaaS deployment use-case with a proof-of-concept where our proposed solution is instantiated using a real-world slice-as-a-service platform and some relevant implementations of different MANO frameworks.

In the context of 6G, the use of drones / UAVs and satellite is a high priority. One of the main issues is that there is limited and varying bandwidth in these environments, so the question arises: how do we provide high Quality of Experience (QoE) to the users. BPP is a recent protocol which is effective when used with Scalable Video Coding (SVC) streams and limited bandwidth environments. We present an end-to-end architecture, with a drone sending video, utilizing functions for dynamically constructing the content of packets, and then dynamically processing those packets during their transmission across a network, all managed by a multi-domain orchestrator. These functions are implemented as virtualized network elements, as in our previous work. In this current work, we investigate how different packing strategies for filling packets impact different QoE parameters, when evaluated using a number of different bandwidths. These insights can be utilized for choosing the best QoE, and will be especially useful in 5G / 6G environments. Index Terms-6G,

This paper describes the effects of running in-network quality adaption by trimming the packets of layered video streams at the edge. The video stream is transmitted using the BPP transport protocol, which is like UDP, but has been designed to be both amenable to trimming and to provide low-latency and high reliability. The traffic adaption uses the Packet Wash process of Big Packet Protocol (BPP) on the transmitted Scalable Video Coding (SVC) video streams as they pass through a network function which is BPP-aware and embedded at the edge. Our previous work has either demonstrated the use of Software Defined Networking (SDN) controllers to implement Packet Wash directly, or the use of a network function in the core of the network to do the same task. This paper presents our effort to deploy and evaluate such a process at the edge, highlighting the packet trimming algorithm and showing the packet trimming effects on the streams. We compare the performance of transmitting video using BPP and the Packet Wash trimming, against alternative transmission schemes, namely UDP and HTTP adaptive streaming (HAS), presenting a number of quality parameters. The results demonstrate that providing traffic engineering using in-network quality adaption using packet trimming, provides high quality at the receiver.

Fog computing, combined with traditional cloud computing, offers an inherently distributed infrastructure – referred to as the cloud-to-edge continuum – that can be used for the execution of low-latency and location-aware IoT services. The management of such an infrastructure is complex: resources in multiple domains need to be accessed by several tenants, while an adequate level of isolation and performance has to be guaranteed. This paper proposes the dynamic allocation of end-to-end slices to perform the orchestration of resources and services in such a scenario. These end-to-end slices require a unified resource management approach that encompasses both data centre and network resources. Currently, fog orchestration is mainly focused on the management of compute resources, likewise, the slicing domain is specifically centred solely on the creation of isolated network partitions. A unified resource orchestration strategy, able to integrate the selection, configuration and management of compute and network resources, as part of a single abstracted object, is missing. This work aims to minimise the silo-effect, and proposes end-to-end slices as the foundation for the comprehensive orchestration of compute resources, network resources, and services in the cloud-to-edge continuum, as well acting as the basis for a system implementation. The concept of the end-to-end slice is formally described via a graph-based model that allows for dynamic resource discovery, selection and mapping via different algorithms and optimisation goals; and a working system is presented as the way to build slices across multiple domains dynamically, based on that model. These are independently accessible objects that abstract resources of various providers – traded via a Marketplace – with compute slices, allocated using the bare-metal cloud approach, being interconnected to each other via the connectivity of network slices. Experiments, carried out on a real testbed, demonstrate three features of the end-to-end slices: resources can be selected, allocated and controlled in a softwarised fashion; tenants can instantiate distributed IoT services on those resources transparently; the performance of a service is absolutely not affected by the status of other slices that share the same resource infrastructure.

The end-to-end delivery of video from drones at one edge, to clients at another edge raises a number of architectural and implementation issues. A specific use-case of collecting video from a football field is presented, with a particular focus on the energy used by the drones, when doing positioning and video collection. It is impossible to send continuous video from all of the drones without having an energy management and a recharging process. Therefore an analysis and formulation of the consumed energy for a flight strategy for successful video collection is developed. Results of doing edge processing of the video streaming application, using a packet trimming process and using the Big Packet Protocol (BPP) protocol, demonstrate that the techniques presented provide a low latency, high QoE stream at the client.

The emergence of a number of network communication facilities such as Network Function Virtualization (NFV), Software Defined Networking (SDN), the Internet of Things (IoT), Unmanned Aerial Vehicles (UAV), and in-network packet processing, holds a potential to meet the low latency, high precision requirements of various future multimedia applications. However, this raises the corresponding issues of how all of these elements can be used together in future networking environments, including newly developed protocols and techniques. This paper describes the architecture of an end-to-end video streaming platform for video surveillance, consisting of a UAV network domain, an edge server implementing in-network packet trimming operations with the use of Big Packet Protocol (BPP), utilization of Scalable Video Coding (SVC) and multiple video clients which connect to a network managed by an SDN controller. A Virtualized Edge Function at the drone edge utilizes SVC and in communication with the Drone Control Unit to manage the transmitted video quality. Experimental results show the potential that future multimedia applications can achieve the required high precision with the use of future network components and the consideration of their interactions.

This paper presents new techniques and mechanisms for carrying streams of layered video using Scalable Video Coding (SVC) from servers to clients, utilizing the Packet Wash mechanism which is part of the Big Packet Protocol (BPP). BPP was designed to handle the transfer of packets for high-bandwidth, low-latency applications, aiming to overcome a number of issues current networks have with high precision services. One of the most important advantages of BPP is that it allows the dynamic adaption of packets during transmission. BPP uses Packet Wash to reduce the payload, and the size of a packet by eliminating specific chunks. For video, this means cutting out specific segments of the transferred video, rather than dropping packets, as happens with UDP based transmission, or retrying the transmission of packets, as happens with TCP. The chunk elimination approach is well matched with SVC video, and these techniques and mechanisms are utilized and presented. An evaluation of the performance is provided, plus a comparison of using UDP or TCP, which are the other common approaches for carrying media over IP. Our main contributions are the mapping of SVC video into BPP packets to provide low latency, low loss delivery, which provides better QoE performance than either UDP or TCP, when using those techniques and mechanisms. This approach has proved to be an effective way to enhance the performance of video streaming applications, by obtaining continuous delivery, while maintaining guaranteed quality at the receiver. In this work we have successfully used an H264 SVC encoded video for layered video transmission utilizing BPP, and can demonstrate video delivery with low latency and low loss in limited bandwidth environments.

Summary Network Function Virtualization (NFV) offers flexibility in traffic engineering and network resource management, by taking advantage of Software Defined Networking (SDN). By using these network technologies, it is possible to enhance the performance of video streaming applications by placing network functions in suitable locations and rerouting flows. Our study addresses the “virtual cache placement” problem in dynamic networks, where traffic patterns and attachment points of the clients are changing rapidly. The cache placement is done by determining how many virtual caches are necessary to be able to provide acceptable service to the clients, as well as where to place those caches to meet demand. To this end, we provide a heuristic solution by taking advantage of NFV‐SDN and having the assistance of Server and Network Assisted DASH (SAND). Experimental results show that the proposed algorithms can improve the video client rebuffering by 150%–270% and also can provide an 8%–12% increase in average bitrate received by the client, compared to a number of benchmark algorithms. The obtained results indicate that the co‐operation between the client and the operator of an SDN‐enabled network, by exchanging client and network information, allows network resources to be efficiently used, and as a consequence, the Quality of Experience (QoE) on the client's side is improved.

The possibility of managing network infrastructures through software-based programmable interfaces is becoming a cornerstone in the evolution of communication networks. The Intent-Based Networking (IBN) paradigm is a novel declarative approach towards network management proposed by a few Standards Developing Organizations. This paradigm offers a high-level interface for network management that abstracts the underlying network infrastructure and allows the specification of network directives using natural language. Since the IBN concept is based on a declarative approach to network management and programmability, we argue that the use of declarative programming to achieve IBN could uncover valuable insights for this new network paradigm. This paper proposes a formalization of this declarative paradigm obtained with concepts from category theory. Taking this approach to Intent, an initial implementation of this formalization is presented using Haskell, a well-known functional programming language.

This paper describes the effects of the Packet Wash process on the transmission of layered SVC video streams. We show how the packet size is adapted when using a number of different packing strategies, that map the video data into the BPP packets, and discuss the relationship between the packing strategies on the sender side and the chunk removal in the washing process. We demonstrate how the packing strategy causes different impacts on the number of and the sizes of the washed chunks. As the bandwidth reduces, more of the chunks in a packet get washed away. Although the receiver gets packets that are much smaller than those transmitted by the sender, it is still able to play video with a high QoE as zero packets are dropped. This traffic engineering enables a direct implementation of an in-network video adaption scheme. The experimental evaluation highlights that the effects of Packet Wash become more obvious in environments where there is limited bandwidth.

Edge microservice applications are becoming a viable solution for the execution of real-time IoT analytics, due to their rapid response and reduced latency. With Edge Computing, unlike the central Cloud, the amount of available resource is constrained and the computation that can be undertaken is also limited. Microservices are not standalone, they are devised as a set of cooperating tasks that are fed data over the network through specific APIs. The cost of processing these feeds of data in real-time, especially for massive IoT configurations, is however generally overlooked. In this work we evaluate the cost of dealing with thousands of sensors sending data to the edge with the commonly used encoding of JSON over REST interfaces, and compare this to other mechanisms that use binary encodings as well as streaming interfaces. The choice has a big impact on the microservice implementation, as a wrong selection can lead to excessive resource consumption, because using a less efficient encoding and transport mechanism results in much higher resource requirements, even to do an identical job.

Cloud-network slicing is a promising approach to serve vertical industries delivering their services over multiple administrative and technological domains. However, there are numerous open challenges to provide end-to-end slices due to complex business and engineering requirements from service and resource providers. This article presents a reference architecture for the cloud-network slicing concept and the practical realization of the slice-as-a-service paradigm, which are key results from the Novel Enablers in Cloud Slicing (NECOS) project. The NECOS platform has been designed to consider modularity, separation of concerns, and multi-domain dynamic operation as prime attributes. The architecture comprises a set of interworking components to automatically create, manage, and decommission end-to-end cloud-network slice instances in a lightweight manner. NECOS orchestrates slices at runtime, spanning across core/edge data centers and wired/wireless network infrastructures. The novelties of the multi-domain NECOS platform are validated through three proof-of-concept experiments: (i) a touristic content delivery service slice deployment featuring on-demand virtual infrastructure management across three countries on different continents to meet particular slice requirements; (ii) intelligent slice elasticity driven by machine learning techniques; and (iii) market-place-based resource discovery capabilities.

The essence of this work is to show how SVC Scalable Video can be adaptated in the network in an effective way, when the Big Packet Protocol (BPP) is used. This demo shows the advantages of BPP, which is a recently proposed transport protocol devised for real-time applications. We will show that in-network adaption can be provided using this new protocol. We show how a network node can change the packets during their transmission, but still present a very usable video stream to the client. The preliminary results show that BPP is a good alternative transport for video transmission.

Big Packet Protocol (BPP), which is part of New IP, was designed to transfer packets for future networking applications, and aims to overcome obstacles within current networks for high precision services. One of the most important advantages of New IP is that it allows changes to packets during transmission. The strategy of BPP is to reduce the packet size by eliminating specific chunks, cutting out segments from the transferred video, rather than dropping or retransmitting packets. This provides an effective mechanism to enhance the performance of video streaming applications, by obtaining continuous delivery and minimum guaranteed quality at the receiver. In order to make video transmission over BPP effective, we need to select a video codec that can do multiple encodings for the same region, such as scalable video coding (SVC). To support such functionality, we have augmented the BPP packet structure in order to transfer video data. This paper describes the use of BPP for carrying video from servers to clients, and defines the packet structure for this purpose, plus the extensions needed to support SVC encoded video. To evaluate the proposed approach, we use SDN to facilitate BPP operations, with results showing a successful implementation of a system using these combined techniques.

This paper describes the use of the Big Packet Protocol (BPP) for carrying video from servers to clients, and how SDN controllers can effectively manage the flow-rate and QoE, based on the available bandwidth. BPP relies on meta-data being injected into packets in order to provide information for network nodes on how to process those packets. Given specific commands, the network node can drop parts of the payload, called chunks in BPP. When using BPP, the strategy is not to drop whole packets, but to reduce the packet size be eliminating specific chunks. The approach allows for reducing the load on the network, when there is a limited bandwidth, by having a flow of packets regularly arriving at the receiver, so there is continuous delivery and minimum guaranteed quality. To make video transmission over BPP effective, a video encoder and decoder that can do multiple encodings for the same region is selected–namely scalable video coding (SVC). The results show the successful implementation of a system using these combined techniques.

This paper explores and makes a case for allocating a Wide-area Infrastructure Manager (WIM) on-demand to support softwarized network slicing, as part of the full NFVI virtualised infrastructure foundation, to ensure that the connectivity attributes prescribed to network slices can be managed with flexibility and adaptability in a full end-to-end slice. We show how creating a WIM on-demand and dynamically allocating a new WIM for each network slice, rather than having one for the whole network, can be beneficial for various slicing scenarios, in a similar way that a Virtual Infrastructure Manager (VIM) on-demand has been utilized. The paper considers some of the components, abstractions, and mechanisms of WIM on-demand.