IP centric QoS model for mobile networks

IP centric QoS model for mobile networks Packet based QoS management for Intra-bearer arrangements Isabelle Hamchaoui, William Diego and Sébastien Jobert Orange Labs Networks Orange Lannion, France {isabelle.hamchaoui, william.diego, sebastien.jobert}@orange.com Abstract — The mobile ecosystem is currently facing tremendous changes; in particular, the actual deployment of 4G will probably not be sufficient to totally fit the upcoming mobile data traffic explosion. This mismatch may be explained by the low marginal revenues expectable from mobile data compared to huge investments it requires. Consequently, congestion may appear soon in radio access networks, thus degrading the customer experience. QoS mechanisms are then required to preserve the most sensitive and/or valuable flows. In this respect, the 3GPP proposes a model capable of supporting several levels of QoS. However, this model was inherited from connectionoriented legacy networks and raises issues in terms of scalability, efficiency, performances and flexibility when used in the context of the foreseen mobile Internet. In this paper, we present an IPcentric approach which aims at adapting usual internet QoS management schemes (e.g. DiffServ) to wireless networks. This approach leverages most of the 3GPP multi-bearer model limitations while offering low-cost open mechanisms in line with usual web-oriented services. This IP centric architecture is described together with its strengths, issues and possible implementations in the radio scheduler of base stations. Simulations results are then presented in order to evaluate the efficiency of such IP aware scheduling. Keywords — radio congestion; IP aware; mobile Internet, scheduling; DiffServ; QoS; LTE

I.

INTRODUCTION

In the recent years, attention has legitimately focused on the skyrocketing explosion of mobile data [1]. However, less visible changes are currently challenging the legacy mobile ecosystem. Indeed, the mobile market is currently experiencing ground-breaking evolution in terms of business models and mobile uses. Urged by the increasing power of terminals together with always growing access rates, the mobile internet is on the way together with its swarm of web services; Featuring highly multitask terminals and supporting new ways to share the mobile internet connection (i.e. tethering, Mobile Wi-Fi), this emerging mobile internet is also impacted by a major shift in the balance of power between the various actors of the ecosystem. As a matter of fact, Over-The-Top (OTT) actors are becoming key players [11] in the mobile landscape, bringing with them web-oriented interfaces, services and models from the fixed internet world. This may have a somewhat disruptive

effect on the solutions standardized by legacy mobile operators (e.g. IMS) to support telco-oriented services. This generally means an important loss of value for mobile operators. One of the most striking examples of these diverging views between legacy mobile operators and internet actors relates to Quality of Service (QoS); the internet world used to deal with loose QoS commitments, which often turn into Best Effort transport. This model is not adapted to stringent QoS requirements on a flow by flow basis, but it revealed cheap, highly scalable and robust. On the contrary, 3GPP specifications aim at offering fine-tuning QoS management through the new standard evolution of mobile system called LTE/EPC system. In contrast to the older standards (i.e. UMTS), which consist of a circuit switched domain for voice and a packet switched domain for data, this standard is based on an all-IP architecture with a unique packet switched domain for voice and data both; however, it inherits many characteristics of legacy standards, and particularly its QoS model. More precisely, QoS specifications of 3GPP release 8 are based on a circuit-oriented model, described in [4]. The main element of this model is a virtual circuit called “bearer”. Bearers provide an end-to-end transport service with specific QoS attributes. For a unique terminal, multiple bearers can be established, one per required QoS level. In the context of a ubiquitous mobile internet, this model raises issues in terms of scalability (number of bearers), efficiency (signaling load) and performance (bearer establishment delay). None of these issues appear insurmountable, but they probably lead to prohibitive costs in a context of low margins market. Based on the foregoing, it makes sense to investigate more cost-effective QoS mechanisms. These QoS mechanisms should have a low complexity of implementation to decrease costs without degrading too much the Quality of Experience (QoE), in the spirit of fixed Internet. Therefore, well-known IP QoS management functions could be adapted to fit the mobile ecosystem. Indeed, these IP mechanisms had proven to be flexible, cheap, scalable, easy-to-configure and well adapted to open ecosystems. This paper presents below a flexible “IP-centric” architecture based on IP paradigms in order to address QoS issues in mobile networks. It has already drawn interest amongst some major actors of the mobile industry community, such as Nokia [7], Alcatel-Lucent and AT&T [6].

Note that the wireless segment deserves special attention, since it corresponds to a sensitive network segment where user traffic is often bottlenecked. An IP-centric eNB (evolved Node B) has then been detailed and modeled in the present paper, and its performances have been evaluated using the simulator ns-3. Finally, the IP-centric model may serve as a basis for implementation of IP QoS mechanisms in any wireless access points (e.g. eNB, wifi hotspots), leading then to a graceful fixed/mobile convergence. II.

3GPP QOS MANAGEMENT

As mentioned above, the QoS management in 3G/4G networks is clearly connection-oriented. A connected entity, called EPS bearer, should be set up between two endpoints (e.g. a User Equipment UE, and a Packet Data Network GateWay, P-GW) before any traffic can be exchanged between them. This EPS bearer provides for a transport service with specific QoS attributes. At UE attachment, a default bearer is first established, in order to provide for basic connectivity. Other bearers could be further set up, one per required QoS level as show in Figure 1. Bearers are operated in connected mode, that is, established, modified or disconnected via mobile control plane signaling protocols.

Proportional Fair (PF) algorithm is generally implement by mobile network vendors and is widely used for operating the default bearer. This algorithm proposes a trade-off between cell throughput optimization and fairness (see [2] and [3] ). III.

Nowadays, the first LTE deployments generally do not implement the full 3GPP QoS policies and only operate a mono-bearer Best-Effort architecture. Note that very few deployment of multi-bearer QoS architecture is observed in 3G networks. As a consequence, the vast majority of mobile terminals are only connected through a unique default bearer, their whole traffic being transported on a best effort basis. Many reasons may be given for this, but it is a fact that the 3GPP QoS solution is often seen as complex and expensive. In this mono-bearer context, it appears then clearly that increasing bearer resource allocation through GBR (Guaranteed Bit Rate) or weighted Proportional Fair is not always the most appropriate solution to improve customer experience. For example, when several applications are running on the same UE (this situation is expected to be fairly common with tethering, Mobile Wi-Fi, etc.), it may be much more efficient to properly schedule the user flows without modifying his global resources allocation. This implies intrabearer QoS differentiation where, for a given UE, sensitive flows are favored against less sensitive flows, as proposed in [12]. Note that this may be performed without modifying the user radio resources allocation. This allows for cell capacity preservation as replacing basic Proportional Fair by QoS aware scheduling (e.g. GBR or weighted PF) statistically reduces this capacity (see [13]). IV.

Figure 1: 3GPP QoS model

QoS levels are defined through mobile QoS parameters (e.g. QCI, QoS Class Identifier). The QoS parameters are transported via mobile control plane and are used by eNB as inputs to configure the radio scheduler which allocates radio resources to the different bearers. The radio scheduler plays an important role on the QoS over the radio segment, and consequently, it dramatically impacts the end-to-end customer experience. On the P-GW side, downstream traffic flows are sent to the relevant EPS bearer thanks to a filter describing the matching between the traffic flows (identified via their TCP/IP headers for example, etc.) and the bearers. Every TTI (Transmission Time Interval), radio resources are dynamically allocated to the active UEs of the cell according to a scheduling algorithm. Various examples of radio scheduling algorithms can be found in the literature.

QOS POLICIES IN MOBILE NETWORKS OF TODAY

IP CENTRIC ARCHITECTURE - PACKET BASED QOS MANAGEMENT

An alternate QoS architecture for mobile networks can be envisaged, built on the experience acquired on fixed Internet: Fixed IP networks are generally operated in connectionless mode, using information contained in each packet header to deliver it to the right destination with the required QoS; The associated QoS management could simplify the 3GPP QoS model and open the door to fixed-mobile convergence, through a so-called IP-centric QoS architecture. In this IP-centric model, see Figure 2, eUE connectivity is still operated in connected mode through an EPS bearer, but QoS is managed on a packet by packet basis; hence, packets are transported on a unique multi-QoS bearer. The DSCP (DiffServ Code Point) should be potentially taken into account by each node supporting the green IP E2E layer in order to schedule properly the packets of a given bearer/eUE. However, this requirement may be relaxed as QoS management is only effective on bottlenecks. As the wireless segment is generally considered as the main bottleneck, an IP multiplexing stage should be added before the radio scheduling in the eNB, in order to schedule packets on the radio interface according to their DSCP. Note that this IP E2E layer reduces to a part of the User plane (queue management is

included in standard forwarding functions) and does not imply control plane functions (e.g. no routing required) in the eNB.

optimization is not spoiled. This is a major difference compared to the second model, where cell throughput may be impacted.

Figure 3: Intra-bearer arrangements model

Figure 2: IP-centric model - packet bases QoS management

We distinguish two main types of behavior for that IPcentric architecture: 



Intra-bearer arrangements: the allocation of radio resources is independent of the traffic mix waiting for transmission; in this case, radio resources allocated to a given user are determined by a basic radio scheduler (e.g. Proportional Fair), taking into account the radio conditions of the UE as usual. The addition of an IP priority queuing system per user before the radio scheduler (without influencing it) allows for prioritization of the sensitive flows of a given user against his own other flows when populating the radio frame. A model of “Intra-bearer arrangements” is detailed in ‎[12] for 3G networks, and promising simulations results for LTE are presented below. Inter-bearer arrangements: the allocation of the radio resources depends on the traffic mix waiting for transmission; in this case, the radio resources allocated to one UE depend not only on the radio conditions of the UE, but also on the traffic mix offered to the IP queuing system. This traffic mix is defined through the DSCP of its constitutive packets. Several approaches are possible (e.g. weighting the allocation according to the prioritized traffic volume / priority queue backlog, ensuring a maximum latency for specific classes, etc.)

This paper focuses on the first behavior, which is referred to as “intra-bearer arrangement” model, see Figure 3. This intra-bearer arrangement model consists in adding an IP queuing stage per user prior to the radio scheduler, without changing the radio resources allocation between the various mobile terminals. Packets of a given UE are simply prioritized based on their DSCP marking in the bearer rate envelope allocated to the UE. As the proportional fair resource allocation per UE is left unchanged, the overall cell resource

More precisely, the intra-bearer IP centric model consists of two stages: The first stage is an IP priority queuing system composed of “n” finite queues per terminal (class based model - one queue per level of QoS). These queues are operated according to a non-preemptive service policy. This means that if one or more high priority packets arrive when a packet of lower priority is served, the high priority packets will be served only after the current service of a low priority packet is complete. For the sake of simplicity, we propose to use a strict priority policy between IP queues, but other policies are also possible, such as weighted fair queuing/weighted round robin. The service rate of this IP queuing system is constant during each TTI. It is calculated for each terminal at each TTI by the second stage described below. The stage level is a radio scheduler which shares the available radio resources (e.g. RB – Resources Block in LTE) between the terminals. Different scheduling algorithms are possible for the allocation of radio resources depending on the optimization criteria (delay, throughput, etc., or trade-off between some of these criteria). On the present model, Proportional Fair scheduler, without any modification, is suggested because it offers a good trade-off between cell throughput and fairness between terminals. Besides, it is very popular amongst base stations. Every TTI, PF shares the available radio resources between active terminals, regardless of the first level queuing process described above. The PF scheduler algorithm takes into account the radio conditions (e.g. CQI - Channel Quality Indicator in LTE) provided by each terminal. This two-stage model has been used in the simulations presented in the next section. V.

PERFORMANCE EVALUATION

First results of simulations based on NS-3 simulator are provided below. In early LTE deployments, all the traffic is usually transmitted on a single bearer; this mono bearer BestEffort scenario is taken as reference. The performances of an IP centric NB is then compared to this reference in terms of delay, jitter and packet loss. In the related simulation, an NS-3 IP router model has been modified in order to emulate the behavior of an eNB by

implementing a simplistic radio layer. For this purpose, pointto-point links (radio link) between the eNB router and each UE are established, see Figure 4. Each of these links is affected with a variable data rate, which is computed every TTI thanks to a PF algorithm. The PF algorithm takes into account the CQI (Channel Quality Indication) provided by each UE.

this simulation, the maximum throughput calculated by the PF for each UE is:  

UE1 ≈ 25 Mbps: as the aggregate applicative rate cannot exceed 16 Mbps, this UE will never undergo congestion. UE2 ≈ 1.4 Mbps: as the aggregate applicative rate is at least 15Mbps, this UE will always experience congestion.

Predictably, the number of queued packets remains very low for UE1 (the maximum is 2 for BE queue) due to lack of congestion. On the contrary, the length of the two AF queues, devoted to FTP and video traffics respectively, increases progressively as depicted in Figure 5 for UE2. This reflects the fact that UE2 cannot obtain sufficient radio resources to support its flows at application rate.

Figure 4: NS-3 simulation schema

The following assumptions have been considered for these simulations:  LTE network configuration: frequency band = 20MHz (100 Physical Resources Blocks), no radio loss  Radio scheduling algorithm: Proportional Fair  IP non-preemptive Priority Queuing system added before this radio scheduler, without influencing it. Three finite queues per UE: one queue served in strict priority (called EF queue), and two other queues in Round Robin (called AF queues)  Three independent application streams: FTP (TCP cubic), Video (TCP cubic) and VoIP (UDP). FTP starts first, then Video and VoIP (at time t = 20s).  One terminal in good radio conditions UE1 (CQIs vary uniformly in [10, 15])  One terminal in bad radio conditions UE2 (CQIs vary uniformly in [1, 5]) – NB: full CQI range is [1-15] Number of terminals

2

Transmission Time Interval (TTI) duration

1 ms

Data rate of VoIP traffic (UDP)

68.8 kbps

Data rate of Video (TCP)

Appl. rate: 1 Mbps

Data rate of FTP (TCP)

Appl. rate: 15 Mbps

Packet size of VoIP traffic

172 bytes

Packet size of Video traffic

1460 bytes

Packet size of FTP traffic

1460 bytes

Queue size (EF and AF)

15 000 Packets

Simulation time

60 seconds

TABLE I.

PARAMETERS CONSIDERED DURING THE SIMULATIONS

At each TTI, the PF algorithm determines a data rate to each UE which depends on the UE’s radio conditions only; in

Figure 5: Queues states for the UE2

The backlog of AF queues supporting UE2 flows (FTP and video) never exceeds 850 packets, which is far from their maximum capacity (15 000 packets); therefore, these queues never overflow, and FTP and video flows do not experience packet losses but large delays. It is suspected that this behavior is related to TCP flow control in presence of large Round Trip Time. Thanks to the IP-aware mechanism, it can be observed on Figure 5 (zoom on VoIP queue state) that the VoIP flow is preserved, as the related EF queue is served according to a strict priority discipline. As a matter of fact, the backlog of the EF queue devoted to VoIP UE2 traffic never exceeds one packet. As FTP and video traffics are handled through two separate AF queues served in a round robin fashion, each of these traffics obtain about the same amount of resources, as shown on Figure 6-a : FTP and video flows share more or less equally the bandwidth remaining after deducing VoIP consumption (about 1.3Mbps), meaning about 0.65Mbps for each flow. As the video application rate is equal to 1Mbps, the related AF queue devoted to UE2 video gradually increases, as mentioned on figure 5. If video had been served in strict

priority over FTP, then it is expected that the video traffic would not have suffered from such buffering effects when using the IP aware mechanism. Figure 6 below compares the data rate experienced by each service for UE2with and without IP aware.

Figure 7: Comparison of VoIP delay with and without IP aware (UE1 and UE2)

Figure 6: Comparison of the data rates per service for the UE2, with and without IP aware

When IP aware is turned off in the eNB (Figure 6-b), all traffics are supported with the same level of priority in a single queue per UE. As a matter of fact, FTP traffic strongly impacts video and VoIP flows: before t=20s, FTP is the only active application. Its traffic is buffered in the eNB, as the radio segment constitutes a bottleneck. At t=20s, VoIP and video are started, and the related packets arrive in a non-empty queue due to previous FTP activity. The first VoIP (respectively video) packet has to wait for transmission of all FTP packets which were already present in the queue at t=20s. It results in a strong delay of about 7 seconds, which makes VoIP service unusable. Moreover, the throughput of the video flow remains very low probably due to huge RTT impacting TCP flow control. On the contrary, when the IP aware mechanism is activated, VoIP packets do not suffer from the huge delay observed in the previous case. The TCP session of the video flow increases gradually and shares equally the available throughput with the other TCP session carrying FTP traffic. Figure 7-a shows the histograms of delays experienced by VoIP packets during the simulation for UE1 and UE2 when the IP aware mechanism is activated (Figure 7-a) and when it is not activated (Figure 7-b). When IP aware is activated (Figure 7-a) the delays experienced by VoIP packets are obviously lower for UE1, which enjoy better radio conditions, than for UE2.

The minimum delays reported in Figure 7-a are equal to the propagation delay of VoIP packets (~200 bytes): - For UE1: 0.06ms ~ (1 Packet x 200 bytes) / 25 Mbps - For UE2: 1ms ~ (1 Packet x 200 bytes) / 1.4 Mbps As a matter of fact, voice is handled in a non-preemptive strict priority manner in our simulation. This means that a VoIP packet should potentially wait until the end of the ongoing transmission of a lower priority packet. The maximum delay affecting a VoIP packet is then obtained when it arrives just at the beginning of the low priority packet (~1500 bytes) transmission. It should consequently wait for the whole transmission duration of this low priority packet. - For UE1: 9ms ~ (1 Packet x 1500 bytes) / 25 Mbps - For UE2: 0.5ms ~ (1 Packet x 1500 bytes) / 1.4 Mbps In both cases for UE1 and UE2, the delays are fairly low (even without pre-emption), thanks to the IP aware mechanism which prioritizes the VoIP packets. Figure 7-b show delay histograms, delay experienced by the VoIP packets during the simulation for UE 1 and UE2 when the IP aware mechanism is not used and that all the flows are carried as Best Effort. For UE1, although the delay experienced by the VoIP packets is, in average, slightly higher than in the IP aware case reported in Figure 7-a, it is still reasonable. Again, the reason is that UE1 has enough bandwidth to carry all the flows at the application rate. However, for UE2, the situation is critical for the VoIP packets: they experience more than 7 seconds of delay, and a delay variation of about 350ms. VI.

DISCUSSION ON IP AWARE MODEL

A. Impact on radio resources In the typical 3GPP multi-bearer scheme, bearers are always associated with resources; as a consequence, the set-up of a secondary bearer between a P-GW and a UE increases

automatically the amount of resources allocated to this UE. Moreover, in case an enhanced QoS is required for this secondary bearer (e.g. Guaranteed Bit Rate, GBR), the global cell capacity is impacted; Indeed, when a eUE is in bad radio conditions, less efficient coding schemes must be used, therefore, maintaining a GBR to an eUE in bad conditions can consume lot of radio resources. Potentially, if no threshold is defined, all radio resources can be allocated to this eUE facing very bad radio conditions at the expense of others eUE. On the contrary, in the context of IP aware intra-bearer QoS management, introducing QoS differentiation through relative priorities inside the customer rate envelope does not impact at all radio resource sharing. No extra-resources are allocated to the UE whatever the number of QoS levels; no impact on global cell capacity is to be mentioned. Of course, the intra-bearer IP aware scheme does not provide for hard GBR commitments. However, it opens the door to relative QoS levels inside a bearer without any impact on the others eUEs. As a consequence, the intra-bearer QoS management scheme gives an easy answer to security issues. Indeed, whatever the packet marking, this will only impact the eUE flows; thus, depending on the associated business model, this marking can possibly be delegated to third parties or to customers without risk to other customers. B. Business models IP aware QoS management in RAN is in line with typical OTT business models: Instead of the flow by flow API suggested by 3GPP typical architectures, third parties may interact with mobile operators through static SLAs at interconnection point. The SLA should define the marking and the maximum rate for each QoS class at interconnection point, as depicted on figure 8. Note that this model is totally consistent with fixed IP networks QoS architecture, and paves the way to seamless services and access agnostic applications. This opens the door to valuable multilevel QoS agreements between content providers and operators.

VII. CONCLUSIONS AND FURTHER STUDIES Simulation have highlighted the efficiency of IP aware scheduling when multiple flows are supported simultaneously inside the same bearer towards the same terminal, as compared to a “no QoS” scenario – very common in early LTE deployments. In particular, it has been shown in very simple scenarios that VoIP delays can be strongly reduced with this mechanism. Running multiple services simultaneously is expected to become quite common with LTE mobile networks, especially with shared mobile connection (e.g. Mobile Wi-Fi, tethering, etc). As the 3GPP multibearer QoS model is making little headway in the mobile landscape, we believe that the IP aware architecture is a real opportunity to offer cheap QoS in RAN, in line with web-oriented service providers business models. Further studies are currently going on in order to complete this preliminary analysis with more realistic models for the radio segment using LENA NS-3 modules (see [14]). In addition, it is planned to submit the IP centric model to standardization bodies in order to address future releases of 3GPP and Wifi standards. VIII. REFERENCES [1]

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Figure 8: possible business model with IP aware RAN

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