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Accurate prediction of maximum flow latency is crucial for ensuring the efficient transport of latency-sensitive fronthaul traffic in packet-switched Xhaul networks while maintaining the reliable operation of 5G and beyond Radio Access Networks (RANs). Deterministic worst-case (WC) models provide strict latency guarantees but tend to overestimate actual delays, resulting in resource over-provisioning and inefficient network utilization. To address this limitation, this study evaluates a data-driven Quantile Regression (QR) model for latency prediction in Time-Sensitive Networking (TSN)-enabled packet-switched Xhaul networks operating under dynamic traffic conditions. The proposed QR model estimates high-percentile (tail) latency values by leveraging both deterministic and queuing-related data features. Its performance is quantitatively compared with the WC estimator across diverse network topologies and traffic load scenarios. The results demonstrate that the QR model achieves significantly higher prediction accuracy—particularly for midhaul flows—while still maintaining compliance with latency constraints. Furthermore, when applied to dynamic Xhaul network operation, QR-based latency predictions enable a reduction in active processing-node utilization compared with WC-based estimations. These findings confirm that data-driven models can effectively complement deterministic methods in supporting latency-aware optimization and adaptive operation of 5G/6G Xhaul networks.

The 5th generation mobile networks (5G) based on virtualized and centralized radio access networks will require cost-effective and flexible solutions for satisfying high-throughput and latency requirements. The next generation fronthaul interface (NGFI) architecture is one of the main candidates to achieve it. In the NGFI architecture, baseband processing is split and performed in radio (RU), distributed (DU), and central (CU) units. The mentioned entities are virtualized and performed on general-purpose processors forming a processing pool (PP) facility. Given that the location of PPs may be spread over the network and the PPs have limited capacity, it leads to the optimization problem concerning the placement of DUs and CUs. In the NGFI network scenario, the radio data between the RU, DU, CU, and a data center (DC)—in which the traffic is aggregated—are transmitted in the form of packets over a convergent packet-switched network. Because the packet transmission is nondeterministic, special attention should be put on ensuring the appropriate quality of service (QoS) levels for the latency-sensitive traffic flows. In this paper, we address the latency-aware DU and CU placement (LDCP) problem in NGFI. LDCP concerns the placement of DU/CU entities in PP nodes for a given set of demands assuming the QoS requirements of traffic flows that are related to their latency. To this end, we make use of mixed integer linear programming (MILP) in order to formulate the LDCP optimization problem and to solve it. To assure that the latency requirements are satisfied, we apply a reliable latency model, which is included in the MILP model as a set of constraints. To assess the effectiveness of the MILP method and analyze the network performance, we run a broad set of experiments in different network scenarios.

We consider a flow-level model for packet-switched telecommunications networks handling elastic flows with concurrent occupancy of resources, in which digital objects are transferred at a rate determined by capacity allocation on each route. The capacity of each node is dynamically allocated to the routes passing by it through a weighted proportional fair sharing policy, and the arrival request for transfer on each route is generated by N heavy-tailed On/Off sources. Under heavy-traffic, we combine state space collapse ( SSC ) and an Invariance Principle to show that when N → + ∞ the conveniently scaled workload and flow count processes converge. SSC establishes a relationship between the corresponding limits by means of a deterministic operator. In Theorem 1 we prove that assuming the other hypotheses hold, SSC is not only sufficient for the convergence, but necessary. In Theorem 2 we prove that when r → + ∞ , r being a scale parameter, the workload limit process converges to a reflected fractional Brownian motion on a polyhedral cone.

Optical packet switching (OPS) networks and its subsystems, like the burst-mode receiver, are an essential technology currently used in passive optical networks (PONs). Moreover, OPS may play a fundamental role on future hybrid optical circuit switching (OCS)/OPS networks and datacenter networks. This paper focuses on two fundamental subsystems of packetized optical networks: the digital coherent burst-mode receiver and the electro-optical switch. We describe and experimentally characterize a novel digital coherent burst-mode receiver that makes uses of the Stokes parametrization to rapidly estimate the state of polarization (SOP) and optimize the equalizer convergence time. This burst-mode receiver is suitable for optical packetized networks that make use of advanced modulation formats such as quadrature amplitude modulation (QAM). We study the suitability of (Pb,La)(Zr,La)O3 (PLZT) optical switches for amplitude-variable coherent polarization division multiplexing (PDM) 16QAM modulation format and demonstrate a switching capacity of 10.24 Tb/s/port. We demonstrate a full 2 × 2 OPS node with a control plane capable of solving packet contention by means of packet dropping or buffering with a switching capacity of 10.24 Tb/s/port. Finally, we demonstrate the operation of the 2 × 2 OPS node with a record capacity of 12.8 Tb/s/port plus 100 km of dispersion-compensated fiber transmission.

RPL (IPv6 routing protocol for low power and lossy networks) proposed by the IETF (Internet Engineering Task Force) ROLL (routing over low-power and lossy networks) working group is a de facto standard routing protocol for IoT environments. Since the standardization was proposed, RPL has been extensively improved for diverse application scenarios and environments. Congestion control is one of the most important reasons why RPL has been improved. In an LLN (low power and lossy network), congestion may even lead to network lifetime reduction. In resource-constrained networks where end-to-end congestion control is not feasible, RPL should play a more crucial role in congestion control. In this survey, we review the RPL schemes proposed for congestion control and load-balancing and discuss future research directions.

The Internet of Things (IoT) is the next big challenge for the research community where the IPv6 over low power wireless personal area network (6LoWPAN) protocol stack is a key part of the IoT. Recently, the IETF ROLL and 6LoWPAN working groups have developed new IP based protocols for 6LoWPAN networks to alleviate the challenges of connecting low memory, limited processing capability, and constrained power supply sensor nodes to the Internet. In 6LoWPAN networks, heavy network traffic causes congestion which significantly degrades network performance and impacts on quality of service aspects such as throughput, latency, energy consumption, reliability, and packet delivery. In this paper, we overview the protocol stack of 6LoWPAN networks and summarize a set of its protocols and standards. Also, we review and compare a number of popular congestion control mechanisms in wireless sensor networks (WSNs) and classify them into traffic control, resource control, and hybrid algorithms based on the congestion control strategy used. We present a comparative review of all existing congestion control approaches in 6LoWPAN networks. This paper highlights and discusses the differences between congestion control mechanisms for WSNs and 6LoWPAN networks as well as explaining the suitability and validity of WSN congestion control schemes for 6LoWPAN networks. Finally, this paper gives some potential directions for designing a novel congestion control protocol, which supports the IoT application requirements, in future work.

In this paper we initiate the generalization of the Adversarial Queueing Theory ( aqt ) model to capture the dynamics of continuous scenarios in which the usually assumed synchronicity of the evolution is not required anymore. We propose an asynchronous model, named continuous aqt ( caqt ), in which packets can have arbitrary lengths, and the network links may have different speeds (or bandwidths) and propagation delays. With respect to the standard aqt model, these new features turn out to be significant for the stability of packet scheduling policies that take them into account, but not so much for the stability of networks. From the network point of view, we show that networks with directed acyclic topologies are universally stable, i.e., stable independently of the scheduling policies and traffic patterns used in it. Interestingly enough, this even holds for traffic patterns that make links to be fully loaded. Finally, it turns out that the set of universally stable networks remains the same as in the aqt model and, therefore, the property of universal stability of networks is decidable in polynomial time. Concerning packet scheduling policies, we show that the well-known lis , sis , ftg and nfs scheduling policies remain universally stable in the caqt model. We introduce other scheduling policies that, although being universally stable in the aqt model, they are unstable under the caqt model.

In WSN, nodes collect the information from the surrounding environment and transferring to base station. Multiple data transmission in a WSN causes the nodes near the base station to get congested. Here we propose to develop a congestion avoidance and mitigation technique. For that, we select routes based on the distance between sender and receiver, relative success rate (RSR) value of node and buffer occupancy of a node. Based on these three parameters, we define a utility function to be applied to each neighbor of a transmitter node. Hence the transmitter node chooses the highest U-valued node as its next hop node among its neighbors in packet forwarding. Thus we avoid congestion by choosing non-congested nodes as its next hop node and then we mitigate congestion based on RSR values.

Wireless Sensor Network has been widely used in a variety of applications such as; medical, agriculture, military, monitoring environment and so on. In healthcare wireless sensor networks, sensors which are placed on specific parts of the patient’s body, detect patient’s vital signs and transmit them to a medical center. As a matter of fact, too many of these sensors begin to simultaneously send the information congestion which is likely to happen in a network. In other words, when the sensors on the patient’s body are constantly sending data packets, the congestion is more likely to happen. This could result in an increase of packet loss ratio and thus efficiency decreases and it affects the overall performance of the system, In this regard, so the congestion control is a major challenge. Congestion detection and control are essential for such systems. In this protocol a new active queue management method is proposed to determine packet loss probability. The proposed AQM integrates the random early detection and fuzzy proportional integral derivative (FuzzyPID) controller methods together. When fuzzy logic combines with PID, it helps to control the target buffer queue. A fuzzy logical controller also estimates and adjusts the sending rate of each node. With the help of OPNET simulator and MATLAB, we compared this proposed protocol with Priority-based Congestion Control protocol and Optimized Congestion management protocol protocols, and simulation results suggest that the proposed protocol performs better than other approaches regarding aspects such as data loss rate and end-to-end delay.

The main objective of this research is to conduct a performance analysis of various multipath routing protocols in wireless multimedia sensor networks for the efficient transmission of the image, audio and video data. To provide efficient routing for the large sized multimedia content, various multipath routing protocols such as energy-aware routing, QoS based routing and geographical routing methods are analyzed. In this analysis, the efficient routing techniques including geographical routing techniques such as GPSR, DGR, PW-DGR presented for wireless multimedia sensor networks are studied and the performance of each technique is evaluated to determine the efficient multipath routing technique. Comparisons are made for evaluated protocols and it is proved that the PW-DGR provides better routing performance for the multimedia data. The findings of the research also show that the PW-DGR method efficiently overcomes the routing problems such as energy bottleneck problem, energy-hole, reduced network lifetime and high delay in packet transmission.