Spiking neural networks (SNN) are expected to enable several use-cases in future communication networks (beyond 5G and 6G), as edge AI and battery-constrained systems can leverage the fast computation and high-power efficiency offered by SNNs. In this work we consider a Distributed Wireless SNN (DW-SNN) system and we analyze its performance in terms of inference accuracy and total neural activity when radio losses are applied to spikes transferred during the inference phase. Our aim is to understand how radio losses impact performance when considering different SNN spike communication types, i.e., input, excitatory, and inhibitory spikes. Then we evaluate the impact of different traffic prioritization approaches among SNN spikes when considering a shared channel capacity being available for SNN activity. From these analyses, we derive some key insights and features that can be considered when applying a DW-SNN and handling its traffic over wireless communication systems. Finally, we report a prototype implementation of DW-SNN using custom-built IoT components, which we use to further investigate different coverage scenarios.

In this paper we demonstrate an effective way to classify repeated handovers (ping-pongs) in mobile broadband networks. The paper also presents a method that can significantly reduce unwanted ping-pongs in the network. The method combines a sub cell movement detection method and ping-pong detection to decide when it is most effective to apply handover threshold tuning (pinning) without increasing the risk of late or failed handovers. The algorithm was evaluated based on live network measurements.

Game traffic depends on two main factors, the game protocol and the gamers' behavior. Based on a few popular real-time multiplayer games, this paper investigates the latter factor showing how a set of typical game phases-e.g., player movement, changes in environment- impacts traffic. By understanding the nature of this impact an algorithm is introduced to grab specific events and states from passive traffic measurements. Further, a measurement example including a detailed analysis is shown from an operational broadband network. The collected data of player behavior in the gaming environment was analyzed and it was also shown that the long range dependence (LRD) property of gaming traffic is not due to the popular explanation based on the heavy-tailed periods of player activities.

We analyse throughput adaptation of high-speed TCP protocols during handovers in an emulation testbed. We use emulation characteristics reflecting current mobile networks and future network specifications as set by the relevant standards. We found that the performance of TCP protocols is satisfactory, except as follows. Traditional loss-based TCP-s like BIC, highspeed and scalable adapt slowly to sudden link capacity increases caused by handovers. Fast TCP adapts much faster, however depending on parameter settings it may under-utilise after a capacity decrease coupled with RTT increase. We also calculate the probability of buffer overflows at handover as the function of the buffer size and transmission parameters at the bottleneck link. This probability turns out to be significant for reasonable scenarios, and we suggest a dynamic buffer re-allocation method to eliminate such buffer overruns in mobile networks.

In this paper a passive methodology for TCP performance evaluation over general packet radio service (GPRS) networks is presented that relies on traffic monitoring at the GPRS ingress/egress router interface (Gi). Based on the IP and TCP headers of the packets we estimate the end-to-end performance of TCP connections such as connection setup behavior and data transfer goodput. In order to identify the effects behind the measured performance the introduced algorithms estimate round trip delays, packet loss ratios, available channel rates, throughput and cany out bottleneck analysis. Large-scale GPRS measurements in seven countries are presented to analyze TCP performance and demonstrate the applicability of the method. The effects of different TCP parameters such as maximum segment size, selective acknowledgements, timestamp usage and receiver window size are also quantified. GPRS measurement results are compared to a wireline dial-up network to identify the effects specific to the wireless environment

This paper presents a passive end-to-end loss monitoring method, which relies on traffic monitoring at a core or ingress router interface. The monitoring node captures the packets of TCP connections generated by end-hosts. Based on the seen sequence number pattern the loss ratios are estimated for the two segments of end-to-end path divided by the monitor. This feature is especially useful if the monitoring node is placed at the border of an autonomous system, e.g., at the egress point of an ISP. When applied to mobile Internet access, packet losses on the radio interface can be distinguished from losses in the core network or in the public Internet. The packet loss estimation algorithm is rigorously validated using simulations and testbed measurements. Additionally, measurement results and an application example in a dial-up ISP are presented.

We propose SWAN, a stateless network model which uses distributed control algorithms to deliver service differentiation in mobile wireless ad hoc networks in a simple, scalable and robust manner. We use rate control for UDP and TCP best-effort traffic, and sender-based admission control for UDP real-time traffic. SWAN uses explicit congestion notification (ECN) to dynamically regulate admitted real-time traffic in the face of network dynamics brought on by mobility or traffic overload conditions. We use the term "soft" real-time services to indicate that real-time sessions could be regulated or dropped due to mobility or excessive traffic overloading at mobile wireless routers. SWAN is designed to limit such conditions, however. A novel aspect of SWAN is that it does not require the support of a QOS-capable MAC. Rather, soft real-time services are built using existing best effort wireless MAC technology. Simulation, analysis, and results from an experimental wireless testbed show that real-time applications experience low and stable delays under various multi-hop, traffic and mobility conditions. The wireless testbed and ns-2 simulator source code are available from the Web (comet.columbia.edu/swan).

We propose SWAN, a stateless network model which uses distributed control algorithms to deliver service differentiation in mobile wireless ad hoc networks in a simple, scalable and robust manner. The proposed architecture is designed to handle both real-time UDP traffic, and best effort UDP and TCP traffic without the need for the introduction and management of per-flow state information in the network. SWAN supports per-hop and end-to-end control algorithms that primarily rely on the efficient operation of TC/IP protocols. In particular, SWAN uses local rate control for best-effort traffic, and sender-based admission control for real-time UDP traffic. Explicit congestion notification (ECN) is used to dynamically regulate admitted real-time sessions in the face of network dynamics brought on by mobility or traffic overload conditions. SWAN does not require the support of a QoS-capable MAC to deliver service differentiation. Rather, real-time services are built using existing best effort wireless MAC technology. Simulation, analysis, and results from an experimental wireless testbed show that real-time applications experience low and stable delays under various multihop, traffic, and mobility conditions.

This paper investigates differentiated services in wireless packet networks using a fully distributed approach that supports service differentiation, radio monitoring and admission control. Service differentiation is based on the IEEE 802.11 distributed coordination function (DCF) originally designed to support best-effort data services. We extend the distributed coordination function to provide service differentiation for delay sensitive and best-effort traffic. Two distributed estimation algorithms are proposed and analyzed. A virtual MAC (VMAC) algorithm passively monitors the radio channel and estimates locally achievable service levels. The virtual MAC estimates key MAC level statistics related to service quality such as delay, delay variation, packet collision and packet loss. We show the efficiency of the virtual MAC algorithm and consider significantly overlapping cells and highly bursty traffic mixes. A virtual source (VS) algorithm utilizes the virtual MAC to estimate application level service quality. The virtual source allows application parameters to be tuned in response to dynamic channel conditions based on "virtual delay curves". We demonstrate through simulation that when these distributed virtual algorithms are applied to the admission control of the radio channel then a globally stable state can be maintained without the need for complex centralized radio resource management. Finally, we discuss a distributed service level management scheme that builds on the proposed algorithms to offer continuous service with handoff.

This paper investigates differentiated services in wireless packet networks using a fully distributed approach that supports service differentiation, radio monitoring, and admission control. While our proposal is generally applicable to distributed wireless access schemes, we design, implement, and evaluate our framework within the context of existing wireless technology. Service differentiation is based on the IEEE 802.11 distributed coordination function (DCF) originally designed to support best-effort data services. We analyze the delay experienced by a mobile host implementing the IEEE 802.11 DCF and derive a closed-form formula. We then extend the DCF to provide service differentiation for delay-sensitive and best-effort traffic based on the results from the analysis. Two distributed estimation algorithms are proposed. These algorithms are evaluated using simulation, analysis, and experimentation. A virtual MAC (VMAC) algorithm passively monitors the radio channel and estimates locally achievable service levels. The VMAC estimates key MAC level statistics related to service quality such as delay, delay variation, packet collision, and packet loss. We show the efficiency of the VMAC algorithm through simulation and consider significantly overlapping cells and highly bursty traffic mixes. In addition, we implement and evaluate the VMAC in an experimental differentiated services wireless testbed. A virtual source (VS) algorithm utilizes the VMAC to estimate application-level service quality. The VS allows application parameters to be tuned in response to dynamic channel conditions based on "virtual delay curves." We demonstrate through simulation that when these distributed victual algorithms are applied to the admission control of the radio channel then a globally stable state can be maintained without the need for complex centralized radio resource management.

In this paper we demonstrate how TCP congestion control can show chaotic behavior. We demonstrate the major features of chaotic systems in TCP/IP networks with examples. These features include unpredictability, extreme sensitivity to initial conditions and odd periodicity. Previous work has shown the fractal nature of aggregate TCP/IP traffic and one explanation to this phenomenon was that traffic can be approximated by a large number of ON/OFF sources where the random ON and/or OFF periods are of length described by a heavy-tailed distribution. In this paper we show that this argument is not necessary to explain self-similarity, neither is randomness is required. Rather, TCP itself as a deterministic process creates chaos, which generates self-similarity. This property is inherent in today's TCP/IP networks and it is independent of higher layer applications or protocols. The two causes, heavy-tailed ON/OFF and chaotic TCP together contribute to the phenomenon, called the fractal nature of Internet traffic.