This paper studies the impact of tunable parametersin the NB-IoT stack on the energy consumption of a user equipment(UE), e.g., a wireless sensor. NB-IoT is designed to enablemassive machine-type communications for UE while providing abattery lifetime of up to 10 years. To save battery power, most oftime the UE is in dormant state and unreachable. Still, duringthe CONNECTED and IDLE state, correct tuning of criticalparameters, like Discontinuous reception (DRX), and extendedDiscontinuous reception (eDRX), respectively, are essential to savebattery power. Moreover, the DRX and eDRX actions relate tovarious parameters which are needed to be tuned in order toachieve a required UE battery lifetime. The objective of thispaper is to observe the influence of an appropriate tuning ofthese parameters to reduce the risk of an early battery drainage

We present the latency-aware multipath schedulerZQTRTT that takes advantage of the multipath opportunities ininformation-centric networking. The goal of the scheduler is touse the (single) lowest latency path for transaction-oriented flows,and use multiple paths for bulk data flows. A new estimatorcalled zero queue time ratio is used for scheduling over multiplepaths. The objective is to distribute the flow over the paths sothat the zero queue time ratio is equal on the paths, that is,so that each path is ‘pushed’ equally hard by the flow withoutcreating unwanted queueing. We make an initial evaluation usingsimulation that shows that the scheduler meets our objectives.

The demand for mobile communication is continuously increasing, and mobile devices are now the communication device of choice for many people. To guarantee connectivity and performance, mobile devices are typically equipped with multiple interfaces. To this end, exploiting multiple available interfaces is also a crucial aspect of the upcoming 5G standard for reducing costs, easing network management, and providing a good user experience. Multi-path protocols, such as multi-path TCP (MPTCP), can be used to provide performance optimization through load-balancing and resilience to coverage drops and link failures, however, they do not automatically guarantee better performance. For instance, low-latency communication has been proven hard to achieve when a device has network interfaces with asymmetric capacity and delay (e.g., LTE and WLAN). For multi-path communication, the data scheduler is vital to provide low latency, since it decides over which network interface to send individual data segments. In this paper, we focus on the MPTCP scheduler with the goal of providing a good user experience for latency-sensitive applications when interface quality is asymmetric. After an initial assessment of existing scheduling algorithms, we present two novel scheduling techniques: the block estimation (BLEST) scheduler and the shortest transmission time first (STTF) scheduler. BLEST and STTF are compared with existing schedulers in both emulated and real-world environments and are shown to reduce web object transmission times with up to 51% and provide 45% faster communication for interactive applications, compared with MPTCP's default scheduler.

Protection and automation in a smart grid environmentoften have stringent real-time communication requirementsbetween devices within a substation as well as between distantlylocated substations. The Generic Object Oriented SubstationEvent (GOOSE) messaging service has been proposed to achievethis goal as it allows to transfer time-critical information within afew milliseconds. However, the transmission of GOOSE messagesare often limited to a small Local Area Network (LAN).In this paper, we propose the use of the fifth generation ofmobile networks (5G) as a means to transport GOOSE messagesin a large scale smart grid environment. The end-to-end delay ismeasured between GOOSE devices over an 5G network with thefocus on the core network using the Open5GCore platform in alab environment. Although there is a lack of a real radio accessnetwork, the experimental results confirm that the delay withinthe rest of the 5G network is small enough for it to be feasiblefor inter-substation GOOSE transmissions.

An increasing number of cellular congestion controlalgorithms (CCAs) are relying on measurements of the deliveryrate observed at the receiver. Accordingly, early detection ofchanges in the receiver’s rate would improve the performanceof such algorithms. Rate measurements over short time intervalscould allow fast detection of change in the rate observed bythe upper layers of a cellular receiver. However, upper layerrate measurements for cellular receivers over a short time scaleproduce unreliable results due to the effect of underlying lowerlayer mechanisms. In this paper, we introduce a rate estimationapproach that reduces the variability observed in short timescale receiver rate measurements and allows faster rate changedetection.

An increasing number of cellular congestion controlalgorithms (CCAs) are relying on measurements of the deliveryrate observed at the receiver. Accordingly, early detection ofchanges in the receiver’s rate would improve the performanceof such algorithms. Rate measurements over short time intervalscould allow fast detection of change in the rate observed bythe upper layers of a cellular receiver. However, for cellularreceivers, upper-layer rate measurements over short time scalesproduce unreliable results due to the effect of underlying lowerlayer mechanisms such as scheduling and retransmissions. In thispaper, we introduce a rate estimation approach that reduces thevariability observed in short time scale receiver rate measurementsand allows faster rate change detection. We also integratean adaptive mechanism to improve online measurements overdifferent time scales.

Information-centric networking (ICN) with its design around named-based forwarding and in-network caching holds great promises to become a key architecture for the future Internet. Still, despite its attractiveness, there are many open questions that need to be answered before wireless ICN becomes a reality, not least about its congestion control: Many of the proposed hop-by-hop congestion control schemes assume a fixed and known link capacity, something that rarely – if ever – holds true for wireless links. As a first step, this paper demonstrates that although these congestion control schemes are able to fairly well utilise the available wireless link capacity, they greatly fail to keep the link delay down. In fact, they essentially offer the same link delay as in the case with no hop-by-hop, only end- to-end, congestion control. Secondly, the paper shows that by complementing these congestion control schemes with an easy- to-implement, packet-train link estimator, we reduce the link delay to a level significantly lower than what is obtained with only end-to-end congestion control, while still being able to keep the link utilisation at a high level. 

A recently proposed congestion control algorithm (CCA) called BBR (Bottleneck Bandwidth and Round-trip propagation time) has shown a lot of promise in avoiding some of the problems that have plagued loss-based CCAs. Nevertheless, deployment of a new alternative algorithm requires a thorough evaluation of the effect of the proposed alternative on established transport protocols like TCP CUBIC. Furthermore, evaluations that consider the heterogeneity of Internet traffic sizes would provide a useful insight into the deployability of an algorithm that introduces sweeping changes across multiple algorithm components. Yet, most evaluations of BBR's impact and competitive fairness have focused on the steady-state performance of large flows. This work expands on previous studies of BBR by evaluating BBR's impact when the traffic consists of flows of different sizes. Our experiments show that under certain circumstances BBR's startup phase can result in a significant reduction of the throughput of competing large CUBIC flows and the utilization of the bottleneck link. In addition, the steady-state operation of BBR can have negative impact on the performance of bursty flows using loss-based CCAs over bottlenecks with buffer sizes as high as two times the bandwidth-delay product. 

In this paper, we aim at tackling the scalability ofthe Mobility Management Entity (MME) which is one of the key control plane entities of the 4G Evolved Packet Core (EPC). One of the solutions to this problem is to virtualize the MME by adopting the Network Function Virtualization (NFV) technology and deploy it as a pool of virtualized instances (vMMEs) with a frontend load balancer. Although several designs have been proposed, a large part of them does not consider the load balancing aspect. To this end, we propose using a Weighted Round Robin (WRR) algorithm for balancing signaling load in a MME architecture. We implement and compare its performance to two currently used algorithms: random and round robin. Experimental results show that the WRR algorithm can significantly reduce the control plane latency as compared to the other two schemes.