This paper compares the power consumption of Long-Term Evolution (LTE), 5G Non-Standalone (5G-NSA), 5G-Standalone (5G-SA), and private 5G-SA networks at two locations. Our findings reveal that 5G-NSA consumes 92% to 111% more energy than LTE, while 5G-SA consumes 79% more. Although 5G-SA is 6.5% more efficient than 5G-NSA, both are less efficient than LTE. Notably, private 5G-SA is 63% more energy-efficient than public 5G-SA. These results highlight the need for optimized network design and technology selection based on specific use case requirements to ensure energy-efficient mobile communication.

Wide Area Network (WAN) management faces significant complexity in characterizing heterogeneous traffic from diverse services, which complicates unified feature extraction for operational tasks like anomaly detection. Key challenges persist in difficulty of creating generic feature sets across diverse traffic patterns and insufficient historical data for machine learning (ML) generalization. Meta-learning algorithms can be applied to learn dynamic feature sets to improve model generalizability on a limited number of data records. However, prior research focuses on algorithm design, with a lack of study on its application to in-band network monitoring. This work proposes a workflow to adaptively collect new feature sets and promptly learn from them. An adaptive in-band feature selection and extraction method is proposed for programmable switch. Meta learning algorithm is introduced for prompt decision in controller based on few-shot records. Evaluation results have shown that it outperforms prior methods in accuracy and inference time on public datasets.

The widespread use of IoT devices has unveiled overlooked security risks. With the advent of ultrareliable low-latency communications (URLLCs) in 5G, fast threat defense is critical to minimize damage from attacks. IoT gateways, equipped with wireless/wired interfaces, serve as vital frontline defense against emerging threats on IoT edge. However, current gateways struggle with dynamic IoT traffic and have limited defense capabilities against attacks with changing patterns. In-network computing offers fast machine learning (ML)-based attack detection and mitigation within network devices, but leveraging its capability in IoT gateways requires new continuous learning capability and runtime model updates. In this work, we present P4Pir, a novel in-network traffic analysis framework for IoT gateways. P4Pir incorporates programmable data plane into IoT gateway, pioneering the utilization of in-network ML inference for fast mitigation. It facilitates continuous and seamless updates of in-network inference models within gateways. P4Pir is prototyped in P4 language on raspberry pi and Dell Edge Gateway. With ML inference offloaded to gateway’s data plane, P4Pir’s in-network approach achieves swift attack mitigation and lightweight deployment compared to prior ML-based solutions. Evaluation results using three public data sets show that P4Pir accurately detects and fastly mitigates emerging attacks (>30% accuracy improvement and submillisecond mitigation time). The proposed model updates method allows seamless runtime updates without disrupting network traffic.

The expanding use of Internet-of-Things (IoT) has driven machine learning (ML)-based traffic analysis. 5G networks’ standards, requiring low-latency communications for time-critical services, pose new challenges to traffic analysis. They necessitate fast analysis and response, preventing service disruption or security impact on network infrastructure. Distributed intelligence on IoT edge has been studied to analyze traffic, but introduces delays and raises privacy concerns. Federated learning can address privacy concerns, but does not meet latency requirements. In this article, we propose FLIP4: an efficient federated learning-based framework for in-network traffic analysis. Our solution introduces a lightweight federated tree-based model, offloaded and running within network devices. FLIP4 consumes less resources than previous solutions and reduces communication overheads, making it well-suited for IoT edge traffic analysis. It ensures prompt mitigation and minimal impact on services in the presence of false alerts using two approaches (metering and dropping), thereby balancing learning accuracy and privacy requirements.

The numerous applications of Unmanned Aerial Vehicles (UAVs) have the prospects of stirring the global economic growth. Besides having a relatively small carbon footprint, the operating cost of UAVs is significantly less than that of manned aircrafts. Conventionally, civilian UAVs are flown such that the UAV controller is in Visual Line of Sight (VLOS) with the UAV. This mode of operation limits possible UAV applications to the visual acuity of the UAV operator. To explore all possible applications of UAVs, it is often required that they operate in large quantities and Beyond Visual Line of Sight (BVLOS). In this article, the radio channel parameters between a UAV and a live 5G NR (New Radio) cellular network, operating on 3.5 GHz frequency was measured and analyzed. This was done by field measurements with TSMA6B - an industrial-grade mobile frequency scanner, attached to a rotary-wing UAV. Using the network configurations obtained by the MNO (Mobile Network Operator), measurement campaigns were carried out at altitudes (22 - 35 meters) within the elevation angle of the transmitting antenna. Collected results were used to fit a path loss regression line for each altitude using the measured power of the reference signal and the instantaneous distance of the UAV from the base station. Findings from the analysis show that the path loss model is height dependent with altitude-specific cell edge requirements. In conclusion, the findings indicate that a 3.5GHz radio channel, deployed in a rural scenario, approximates a free space channel with an increase in altitude. This is because the channel conditions are similar to a line-of-sight scenario with increased altitude.

Data processing architectures are currently evolving to enable the deployment of critical real-time applications, particularly in the railway environment. Indeed, these new computing architectures could contribute to the definition of innovative services: platooning, remote driving, autonomous trains, etc. This is why many studies today aim at setting up optimal Edge Computing architectures that would allow critical services to be deployed as close as possible to the end user. It is therefore necessary to design a powerful simulation/emulation environment that could be used to validate the proposed solutions. In this paper we demonstrate how the platform we have implemented, Emu5GNet, could be used to enable the rapid design and evaluation of new Edge Computing solutions. We present the potential applications of Emu5GNet and a reusable use case comparing Edge and Cloud deployment as well as different strategies for Edge resources management.

MQTT is currently one of the most widely used protocols at the application layer for the Internet of Things (IoT). To manage an increasing number of IoT devices and optimize the transmission of information, the distribution of the MQTT broker (MQTT cluster) and the integration of the SDN technology in the MQTT architecture are nowadays strongly promoted ideas. Unfortunately, existing proposals have several limitations: 1) they are incompatible with currently deployed solutions, 2) they induce significant delays for information exchange between MQTT brokers within the same cluster, and 3) they do not take into account the distribution of data to the end users (subscribers). That is why, in this paper, we propose a new SDN-based Real-Time Distributed MQTT Broker: SoD-MQTT. The architecture and protocols described aim to minimize communication delays between brokers and to support very low latency applications (e-health, transportation). By leveraging the advantages of SDN, subscription, and publishing can also be efficiently managed. The conducted evaluations demonstrate the relevance of the solution in terms of latency and network utilization optimization compared to existing SDN-based MQTT brokers.

Cellular coverage measurements for 5th generation mobile networks (5G), Long-Term Evolution (LTE), Narrowband-IoT (NB-IoT), and LTE for Machine Type Communication (LTEM) have been carried out above 450 feet in the airspace OD 1 near Hans Christian Andersen (HCA) Airport, Denmark, and the results for Reference Signal Received Power (RSRP) and Signal to Interference & Noise Ratio (SINR) is presented. The main objective of this empirical work is to investigate the reachability of cellular technology for drone communication and navigation. The results conclude that 5G has good signal strength and acceptable communication signal quality compared to LTE, LTE-M, and NB-IoT.

Narrow-band Internet of Things (NB-IoT) and LTE-M are two emerging Low Power Wide Area Network (LPWAN) technologies in the IoT space. Both NB-IoT and LTE-M are based on the 3GPP LTE standard with added features specifically designed for Low Power, remote, and reliable IoT applications. Among other things, these Cellular-IoT (C-IoT) technologies promise improved deep-indoor performance (at least 20 dBm) over traditional LTE standards. In this paper, we have tried to evaluate the deep-indoor performance of NB-IoT and LTE-M. The technologies have been evaluated based on End-to-End delay, bitrate, received signal quality, and packet drop in uplink (UL) and downlink (DL) directions. The tests have been performed using the commercially deployed NB-IoT and LTE-M networks by operators in Denmark. These tests were conducted in the underground tunneling system of the Technical University of Denmark at levels L-1 and L-2 from the ground surface. The outcome of these tests was then compared with the outcome from the best-case scenario, where the base station is in the Line of Site (LOS) to the User Equipment(UE). In total, the tests were conducted at 18 different locations with a total of approx—two hundred eighty-eight thousand packets sent using both technologies, over two telecom operators with varying packet sizes. The goal behind experiments is to test the performance of C-IoT technologies in multi-technology deployment (in parallel with GSM, LTE, etc.) and gather real-world performance data from the networks. The idea is to determine whether C-IoT can be used for deep-indoor applications deployment. The results from these tests indicate that C-IoT networks had a degraded and unreliable performance in poor radio conditions.

In Dual Connectivity (DC), a User Equipment (UE) can be configured with two radio access nodes in order to aggregate the available resources at both nodes. As with dual connectivity each node has independent radio resource management, the maximum power allocation at the UE can be easily exceeded and the interference can be increased. Hence, the power distribution among the carriers needs to be optimized and has to minimize the required coordination among the nodes. In this paper we propose an optimal power allocation based on the load of the cells and cell effective interference. Additionally, we determine criteria for configuration of UEs with dual connectivity. The simulation results show performance improvement by the proposed algorithm with respect to the achieved user throughput. Performance gains (threefold gain in median user throughput) are evident in low as well as high loads in the cell.

We are happy to present you this special issue dedicated to Energy Efficiency in Large-Scale Distributed Systems conference (EE-LSDS2013) of Concurrency and Communications: Practice and Experience.

This paper proposes new energy efficient routing algorithms in optical core networks, with the application of solar energy sources and bundled links. A comprehensive solar energy model is described in the proposed network scenarios. Network performance in energy savings, connection blocking probability, resource utilization and bundled link usage are evaluated with dynamic network simulations. Results show that algorithms proposed aiming for reducing the dynamic part of the energy consumption of the network may raise the fixed part of the energy consumption meanwhile.

This paper presents an integration of multicast and unicast traffic scheduling algorithms for input-queued cell switches. The multi-level round-robin multicast scheduling (ML-RRMS) algorithm with the look-ahead (LA) mechanism provides a highly scalable architecture and is able to reduce the head-ofline (HOL) blocking problem that the weight-based algorithm (WBA) suffers from. Leveraging the FILter & Merge (FILM) scheme, multicast and unicast traffic are independently scheduled based on their requests. Decisions are integrated following a specific policy. Remainder is looped back to the filtering module that filters out the conflicting requests to ensure fairness. Simulation results show that comparing with the scheme using WBA for the multicast scheduling, the scheme proposed in this paper reduces the HOL blocking problem for multicast traffic and provides a significant improvement in terms of latency.

This paper focuses on the problem of coherent resource allocation within home and access networks. The interdomain QoS signaling discussed here enables the initiation of the QoS provisioning in the home and access from the end device in users home. The home network considered in this paper is UPnP-QoS enabled while the access network is GMPLS based. We propose and implement an interface between aforementioned network segments allowing for end-to-end QoS establishment. We present the QoS parameters and mechanisms in both UPnP-QoS and GMPLS and how they can be matched to create a coherent QoS architecture. Additionally we investigate the complexity of such a solution and present implementation results.

Providing QoS in home networks seems to be more and more important in triple and quadruple play service scenarios. This paper focuses on the analysis of certain aspects of UPnP QoS Architecture designed to provision QoS in home networks. Basic signaling performance is discussed and preemption algorithms are proposed and evaluated.

Enabling the coexistence of non-UPnP Devices in UPnP QoS Architecture is an important issue that might have a major impact on the deployment and usability of UPnP in future home networks. The work presented here shows potential issues of placing a non-UPnP Device in the network managed by UPnP QoS. We address this issue by extensions to UPnP QoS Architecture that can prevent non-UPnP Devices from degrading the overall QoS level. The obtained results show that deploying Network Based Control Point service with efficient traffic classifier, improves significantly the end-to-end packet delay characteristics.

In the past few years, Ethernet Passive Optical Networks (EPONs) have rapidly gained large popularity in broadband access networks. However the current standard has no management protocols aiming at reducing power consumption. In this paper, we propose an Energy Management Mechanism (EMM) within the IEEE 802.3ah control scheme. The main idea is to switch Optical Network Units (ONUs) to sleep mode and determine a suitable wakeup time schedule at the Optical Line Terminal (OLT). In the proposed EMM there is a trade-off between maximizing the power saving and guaranteeing the network performance. We compare two types of downstream scheduling schemes, Upstream Centric Scheduling (UCS) and Downstream Centric Scheduling (DCS), which are different in the way they assign 'active' and 'sleep' states to ONUs. Simulation results in terms of energy consumption and queuing delay are shown for the EMM based EPON system.

The QoS provisioning in home networks is being more often considered for future use cases, where multiple high bandwidth flows are accommodated in the home environment. This paper investigates chosen characteristics of one of the home network control and management protocol suites, namely UPnP. Using network modeling tools, we evaluate UPnP QoS Architecture and its resource management influence on the end-to-end packet delay characteristics for different scheduling approaches.

In order for service providers to provide their users high quality services in the home network, Quality of Service (QoS) provisioning is needed to protect premium services. In this paper, we describe how a Universal Plug-and-Play (UPnP) based home network architecture solves this problem in a heterogeneous home network. We outline how it both relieves the end user from troublesome configuration and still offers control to the service provider. We particularly present performance assessment results for UPnP-QoS v3, based on a fully operational experimental implementation. The quantitative measurement results are further used in extensive simulations demonstrating acceptable response times and clear QoS admission differentiation.

In this paper, we propose cell breathing as a load balancing mechanism into WiMAX network with an integrated EPON backbone. Cell breathing is a well known cellular telephony concept that handles congestion by changing the coverage area of a fully loaded cell tower. In WiMAX, cell breathing can be achieved by changing the transmitting powers of the base stations. In the integrated EPON-WiMAX system, access gateways, i.e. EPON integrated base stations, report their residual downlink queue sizes to the central office using modified multi-point control protocol. Centralized gateway selection and power allocation can be made jointly in the central office for all connected access gateways. An iterative algorithm is proposed that equalizes the expected transmission time based on the reported queue sizes and adjusted transmission power level. The performance of the proposed cell breathing in integrated EPON-WiMAX system is simulated. The results show that cell breathing significantly outperforms fixed power scheme.

User-generated podcasting service over human-centric opportunistic network can facilitate user-generated content sharing while humans are on the move beyond the coverage of infrastructure networks. We focus on the aspects of designing efficient forwarding and cache replacement schemes of such service under the constraints of limited capability of handheld device and limited network capacity. In particular, the design of those schemes is challenged by the lack of podcast channel popularity information at each node which is crucial for forwarding and caching decisions. We design a distributed reputation system based on modified Bayesian framework that enable each node estimates the channel popularity in a efficient way. It estimates channel popularity by not only first hand observations but also second hand observations from other nodes. Our simulation result shows reputation system can always well estimate most popular, intermediate and low popular channels, compare to history-based rank scheme which can only well estimate a few most popular channels. Reputation system significantly outperforms history-based rank when the public cache size is small or "a" parameter of Zipf-like distribution is small.

Human opportunistic networks can facilitate wireless content dissemination while humans are on the move. In such a network, content is disseminated via nodes relaying and nodes mobility (human mobility). Thus it is essential to understand and model the real human mobility. We present a heterogeneous community-based random way-point (HC-RWP) mobility model that captures the four important properties of real human mobility. These properties are based on both intuitive observations of daily human mobility and analysis of empirical mobility traces. By discrete event simulation, we show HC-RWP captures essential statistic features of wide range of real human mobility traces reported in previous studies.

We present a routing solution which eliminates the inherent path exploration problem of BGP and thereby enhances survivability in multi-domain networks. The path exploration problem is caused by the dependency among paths learned from neighboring domains. We propose to solve this issue by using two domain level disjoint paths. Our work is based on the aggregated representation of transit domains. The aggregated scheme we use is obtaining the shortest path between each pair of border routers for the associated domain. We also propose to use a single node to represent the destination domain, thereby the size of routing table is 2*(n-1). To implement our solution, domain level source routing is used and a SDRP header is added to the delivered packet. This avoids re-calculation and path exploration when repairing inter-domain link failures. Inter-domain link failures must be repaired at domain level, while intra-domain link failures can be repaired by neighboring nodes, border routers or at domain level. The intra-domain repair methods are compared by simulation and based on the results border router repairing is recommended.

Future mobile communication systems such as IEEE 802.16 are expected to deliver a variety of multimedia services with diverse QoS requirements. To guarantee the QoS provision, appropriate scheduler architecture and scheduling algorithms have to be carefully designed. In this paper, we propose an adaptive bandwidth distribution algorithm for the aggregate scheduler in a two-level hierarchical scheduler, which can provide more organized service differentiation among different service classes. By taking the backlogged traffic, the spectral efficiency in terms of modulation efficiency, and the QoS satisfaction into account, the proposed algorithm adaptively allocates bandwidth to each service class with the objective of increasing the spectral efficiency while satisfying the QoS requirements. Through system-level simulation, it is shown that the proposed algorithm can adapt to the performance of the class schedulers and distribute the bandwidth among them more efficiently than the conventional schemes.

In this paper, promising technologies and a network architecture are presented for future optical packet switched networks. The overall network concept is presented and the major choices are highlighted and compared with alternative solutions. Both long and shorter term approaches are considered, as well as both the wide-area network and multiple-area networks parts of the network. The results presented in this paper were developed in the frame of the research project DAVID (Data And Voice Integration over DWDM) project, funded by the European Commission through the IST-framework.

In this paper, we propose a hybrid medium access control protocol for supporting broadband integrated services in the wireless ATM networks.The integrated services include CBR, VBR and ABR traffic varying from low bit-rate to very high bit-rate.The proposed protocol is an excellent compromise of contention, reservation and polling access techniques based on the dynamic TDMA system.Extensive simulation results using realistic data traffic sources, show that the proposed medium access scheme may provide QoS guarantee to different ATM traffic including the realistic MPEG video traces with low cell transfer delay and very high channel utilization of 90%.

An efficient bandwidth allocation scheme is proposed for supporting integrated services in wireless ATM networks. These include CBR, VBR and ABR types of traffic. The proposed scheme is based on A-PRMA for carrying ATM traffic in a dynamic TDMA type access system. It allows mobile users to adjust the reserved bandwidth according to their current demands and the wireless channel status. Extensive simulation results show that the proposed scheme can provide QoS guarantees with low cell transfer delay, high channel utilization (more than 70%) and short buffer length requirements.

A new multilink concept, called string mode, is presented that can be used in an asynchronous transfer mode (ATM) network to balance the load and thereby increase the efficiency of the network. Performance evaluation shows an efficiency improvement of about 50% when the concept is used with bursty sources with a relatively high peak bitrate. Two different chopper algorithms are investigated, one is distributing strings in cyclic order, while the other uses a uniform random distribution. Results show that a better performance can be obtained by using cyclic distribution. However, cyclic distribution requires a counter for every source to store information about the previous selected links, while a random generator used to determine the next output link can be a shared resource for a number of sources.>

A multilink concept, called string mode, that can be used in an asynchronous transfer mode (ATM) network to balance the load and thereby increase the efficiency of the network is introduced. The principle of the concept is to chop bursts into smaller subbursts, called strings, and distribute them onto a number of parallel links. Performance evaluation shows an efficiency improvement of more than 50% when the concept is used with bursty sources with a relatively high peak bit rate. The traffic shaping property and balancing of the load obtained in using the string mode protocol allow a simpler load control mechanism. The dissociation between service bit rate and link bit rate makes it possible to provide a high-bit-rate service using less advanced technology, and it will lower the blocking probability, as the total bandwidth does not have to be found on the same link.>

Four measurement algorithms for flow enforcement in asynchronous transfer mode (ATM) networks are presented. The algorithms are the leaky bucket, the rectangular sliding window, the triangular sliding window, and the exponentially weighted moving average. A comparison, based partly on teletraffic theory and partly on signal processing theory, is carried out. It is seen that the time constant involved increases with the increasing burstiness of the connection. It is suggested that the RMS measurement bandwidth be used to dimension linear algorithms for equal flow enforcement characteristics. Implementations are proposed on the block diagram level, and dimensioning examples are carried out when flow enforcing a renewal-type connection using the four algorithms. The corresponding hardware demands are estimated aid compared.>