Queueing strategies for local overload control in SIP server Rosario G. Garroppo, Stefano Giordano, and Stella Spagna Dept. of Information Engineering, Univ. of Pisa, I email:
[email protected]
Abstract—As other signaling protocols in the past, also SIP suffers of server overload leading to performance collapse. In this framework, recent Internet drafts propose the improvements of overload control mechanisms already presented in SIP and/or a closed loop system model for overload avoidance. In this framework, the paper presents the system simulator developed extending the Network Simulator (ns-2) with logical for local overload control. Furthermore, the paper proposes a new queueing discipline obtained combining the simple First In First Out (FIFO) service discipline with the priority one. Then the paper presents a simulation analysis, aimed at evaluating the impact on system performance of different queueing structures, service disciplines, and buffer sizes. Simulation results clearly show that the proposed queueing discipline produces good system performance with a low complexity increase. Finally, the simulation results point out the weakness of the 503 Service Unavailable message mechanism, which does not introduce significant improvement when combined with the proposed solution.
I. I NTRODUCTION The Session Initiation Protocol (SIP) plays a key role in the modern communication networks. It is an application-layer signaling protocol for creating, modifying, and terminating multimedia sessions. Defined by the IEFT, SIP has been adopted by other communities, such as the 3GPP (3rd Generation Partnership Project) and ITU-T, and represents today a key building block for MoIP services. In this scenario, the experience matured with signaling system in circuit switched telephone networks [1] points out the need of analyzing the system performance under overload conditions. In the SIP scenario, overload occurs when SIP servers have insufficient resources to handle all the SIP messages they receive. Even though the SIP protocol provides a limited overload control mechanism through its 503 Service Unavailable response code, SIP servers are still vulnerable to overload. In this scenario, the recent research work points out two possible approaches to face overload: a remote overload control invoked by proxy signaling its neighbors of its state and a local overload control based on message throttling. Remote overload control is critical because proxy has no assumptions about the behaviour of senders and it has to deal with dynamic sources. Message throttling instead is based on the consideration that it is possible to protect proxy by selectively throttling signaling messages. Each request to the proxy usually results in a sequence of several messages; therefore the process of throttling messages may be done intelligently by throttling messages that initiate service request.
Saverio Niccolini NEC Laboratories Europe, Heidelberg, D email:
[email protected]
To apply local overload control each element is modeled with an internal overload detection mechanism and a control overload action. The paper discusses impact on system performance when different queueing structures, service disciplines and buffer sizes are considered. Furthermore, the most performing queueing scheme will be used in order to compare the improvement or worsening introduced by the 503 error message mechanism. The simulation study is carried out using the developed Overload Control Proxy (OCProxy) class in the Network Simulator (ns-2) [2] simulation environment. The paper is organized as follows. Section II discusses related work, while Section III presents an overview of SIP highlighting basic retransmission mechanism, SIP model and the 503 Service Unavailable message. Section IV describes our proposed mechanism for local overload control detailing the proxy and UA behaviour; in Section V we define simulation parameters and assumptions. Section VI presents the analysis of the simulation results, while Section VII concludes the paper. II. R ELATED W ORK SIP overload has been recently studied from both an algorithmic and a model point of view. In particular, [3] highlights the overload causes and describes the current SIP mechanism suggested by IETF to overcome it. This Internet draft correctly explains the mechanism weakness. In [4] the authors suggest some modifications to this mechanism, while [5] introduces a new system model based on feedback defining different degrees of cooperation among senders and receiver. The idea of remote overload control for SIP system has been investigated by [6] that proposes an application to SIP scenario of algorithm proposed by [7]. Our paper is focused on local overload control, as defined in [5]; it can be used in conjunction with an implicit or explicit overload control mechanism. Main goals of this paper are to determine more suitable combination in term of queueing structure and service discipline for local overload control and to evaluate if an explicit rejection mechanism could significantly improve system performance. Specifically on SIP simulation study of overload scenario, [8] shows the congestion collapse of SIP server under heavy load. It suggests the approach of using a priority queueing; our results confirm its conclusions and add new details to the analysis in comparison with explicit rejection mechanism and other queueing structures and service disciplines.
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III. SIP OVERVIEW In this Section we briefly highlight some basic concepts on SIP protocol. The basic SIP entities, described in [9], are the User Agent Client (UAC), responsible for transmitting request, the User Agent Server (UAS), responsible for sending response, and the SIP server. The entity composed by a UAC and a UAS is the User Agent (UA). SIP server can be grouped into SIP Proxy for messages routing and registration server, called Registrar, for UA registration. Furthermore, SIP Proxy can be classified as stateful or stateless. Stateful Proxy can store state information during the different phases of a session (i.e. set up, features modification, and tear down), while stateless Proxy cannot. A. SIP Signaling and Retransmission To set up a SIP session, the UAC sends an INVITE request to the UAS, as shown in Figure 1. Each element on the path confirms the reception of this request with a 100Trying. The UAS responds with a 180Ringing to indicate that the called user is being alerted and a 200OK to indicate that the user has accepted the session. The UAC confirms the 200OK reception with ACK request to complete the three way handshake of an INVITE transaction. Session can be terminated at any time and by any side by sending a BYE request, which is confirmed with a 200OK response. Message exchange during a basic session (i.e. with the set up and the tear down phase only) is composed by seven messages. SIP is an application layer protocol and can run over UDP, TCP, or TLS. To assure a fast call set up, application usually uses UDP; the reliability of the message delivery is managed by timers at SIP layer. In particular, [9] defines two types of retransmission procedures, one for INVITE message and one for non-INVITE message. INVITE retransmission is triggered by the timer TA , initialized to default value T1 = 500ms. When TA expires, the associated message is retransmitted and TA is exponentially increased until the total timeout period achieves the maximum value TB ; in this case, the UAC abandons the attempt to establish the session. Default value for TB is 32s. Retransmission mechanism for non-INVITE messages is omitted for sake of brevity and can be found in [9]. The receipt of provisional or definitive response (in case of UAC request message) and of ACK request (in case of final responses sent by UAS as final decision related to a session invitation) will quench the associated retransmission timers. B. 503 Service Unavailable To face the overload condition, the final response with error code 503 Service Unavailable has been introduced; it means the server is temporarily unable to process the request due to a temporary overloading or maintenance. This mechanism presents some problems, as underlined in [3]. In particular, SIP proxy can or cannot implement this mechanism to react to overload; if not, SIP server silently discards the new request. The error message 503 Service Unavailable stops the retransmission timer for that request
Fig. 1.
SIP Signaling
because it is a final response. Details about this mechanism can be found in paragraph 21.5.4 of [9]. C. SIP Model For a correct understanding of the SIP simulation model implemented in ns-2 [2], we describe the SIP protocol as a set of logical levels that are responsible for the action of transmitting, elaborating and receiving a message. Details about logical levels shown in Figure 2 can be found in [9]. We deepen Transaction level and Transaction User level. The Transaction level handles SIP message retransmissions, managing SIP timers and matching of responses to requests. When a SIP entity sends new requests, it instantiates a “client transaction”. Similarly, when a SIP entity receives a request, it instantiates a “server transaction”. Both “client transaction” and “server transaction” are governed by finite state machines. The Transaction User (TU) is a logical level that can be metaphorically linked to the conscience of the person who decides when and whether to submit a request. As an example, the dialing of the phone address required by the SIP based soft-phone is translated by the TU in a “client transaction”. Furthermore, during this operation, the TU also determines the IP address, the transport protocol, and the port number to use for sending the INVITE message. We refer to TU as a core; the SIP elements, i.e. UAs and SIP servers, contain a core that distinguishes them from each other. In Figure 2 we show the TU level and the transaction level put side by side because it is possible that a message passes from TU to transport level in a stateless way that means without going through the transaction level, for example the ACK to INVITE.
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IV. S IMULATION M ODEL We have developed a new module to study the SIP server overload mechanisms; hence the module only implements the control plane of SIP, the media involved in a session are not considered. We have assumed a SIP server acting as both SIP proxy and Registrar. Furthermore, we have considered stateful proxy. A. The Overload Control Proxy Model We have developed a new Agent class, called OCProxy (Overload Control Proxy). This new class interacts with the Transaction level of SIP layer, both client and server. Furthermore it implements the logic for overload control and it manages a set of counters allowing us to acquire statistics. In particular, the Transaction level manages the state machine associated to the client and server transaction, as specified in section 17 of [9]. The different active transactions are recorded in two lists, one for client transactions and another for server transactions, both represented as a queue in Figure 2. Once the finite state machine of a transaction achieves the state Terminated, the data about this transaction are canceled from the list (i.e. are dequeued from the buffer) and the counters are updated accordingly. The SIP messages arrive to the ns-2 class that implements the behaviour of the TU level. In the implementation of the TU level of OCProxy, we have developed the code to model the queueing system and the processing of all SIP packets, see Figure 2. This model allow us to take into account all SIP messages, even those that are not part of a transaction. The queueing system is flexible and allow us to simulate different queueing strategies, i.e. single or multiple buffers, service disciplines, and service processes. Finally, the developed module implements the mechanism of call rejection based on message error 503 Service Unavailable, which during the configuration of the simulation scenario could be optionally de-activated. The message processing time of the SIP proxy depends on the type of SIP messages; for example, the processing time of the INVITE is larger than the processing time of response messages, because of the localization process of the next hop. In the developed module, it is possible to set the assumed processing time for each kind of message. B. UA Model The UA model has both the UAC and the UAS side. The signaling involving SIP elements is represented in Figure 1. When the UAS receives the INVITE it consecutively sends the 100Trying, 180Ringing, and the 200OK response messages. The UAS model disregards the time needed to the device to start the ringing phase, which is necessary to the callee to answer the session invitation. After the reception of ACK message, the UAS waits for a time equal to Ts before starting the tear down procedure, i.e. sending the BYE request. The Ts parameter represents the time used for exchanging multimedia information between the session participants; Ts could be set both in a deterministic or random manner. When the UAs receives the 200OK message that closes the session, a
Fig. 2.
Structure of Overload Control Proxy
new event is scheduled after Ti . The action associated to this new event is the change of the role between the caller and the callee and the start of a new session. As shown in Figure 1, the previous callee becomes a caller for the new session. This mechanism allow us to have continuously alternation of sessions between the two end-points, where only Ts and Ti are the time intervals where no signaling actions are executed by the UAs. It is worth mentioning that in the case the UAC receives a 503 Service Unavailable message or timer TB expires, the UAC model schedules the start of the new session set up procedure after Ti . Furthermore, when the tear down procedure fails (e.g. the timer associated to BYE request expires) the UA model generates a warning message on the output files, but its behaviour is equal as in the case of correct conclusion of the procedure. These assumptions allow us to maintain the rate of calls per seconds produced by the set of UAs at a constant value, even in overload condition. The size of the SIP messages used during the simulation is set as follows: INVITE (800 bytes), 200OK-100Trying180Ringing-503 Service Unavailable (250 bytes), ACK-BYE (300 bytes). V. S IMULATION SCENARIO In the setting of the simulation scenario, we have focused on server-to-server overload problem and on multiple sources scenario presented in [5]. Figure 3 shows the network configuration; as shown in the figure, we set (n + 1) domains, each one having a SIP proxy and a router. Each one of the first n domains contains m SIP UAs, while the last one (denoted as bottleneck domain, BD) has n · m SIP UAs. The routers of the first n domains are directly connected with the router of the BD. Each UA belonging to the first n domains is involved in sessions with a particular UA of the BD. Hence, the SIP proxy of BD is the only bottleneck of the system. In order to vary the offered load to the bottleneck SIP proxy, we have varied the number of UAs, m = 10, ..., 98, in each of the first n = 10 domains. Ts is obtained from an
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have assumed that each UAs of the first n domains, generically indicated as U Ak , starts the first session set up procedure after a time tk from the simulation beginning; tk is generated according to a random variable uniformly distributed in [0, 200 s]. A. Setting of TU queueing system
Fig. 3.
Simulation Scenario
exponential random variable with a mean value equal to 30 s, representing the mean session duration. Ti is also obtained from an exponential random variable with a mean value equal to 10 s. To estimate the load, λ, offered to the SIP proxy of BD, we have taken into account that each session involves the exchange of 7 SIP messages. Hence, the average SIP message arrival rate can be estimated as [8] 7·m·n (1) Ts + Ti We have defined the normalized offered load, ρo , of a SIP λ , where μsip is the mean service rate of SIP proxy as ρo = μsip messages. We can estimate this parameter taking into account the service time associated to each SIP message type. In particular, in the simulation scenario, we have set the processing time of the INVITE to 40 ms and the processing time of a non-INVITE message to 5 ms. Taking into account that a basic session is composed by 1 INVITE and 6 non-INVITE, the average processing time of a SIP message is 10 ms; hence μsip = 100 mess/s. The maximum throughput of the SIP proxy is 14.28 calls/s, taking into account seven messages per session. To eliminate the problems associated to synchronous session set up request of all UAs at the begin of the simulation, we λ=
In the developed module, SIP messages are queued at TU level. To study the impact of the structure of queueing system on SIP proxy performance, we have set up two different models: a single buffer and a two buffer structure. The single buffer structure is characterized by a simple First In First Out (FIFO) service discipline. In the case of two buffers, we reserve one to INVITE messages and the other to non-INVITE ones. In this case, we consider two different service disciplines. In the first one, the messages in the two buffers are served using a simple Round Robin service discipline. In the second one, we propose to use the FIFO discipline when the system is not in overload state, otherwise the two buffers are served using a priority discipline, assigning the highest priority to the non-INVITE messages. This service discipline is maintained until the system comes out from the overload condition, then the system returns to adopt FIFO discipline. We refer to this strategy as Combined FIFO and Priority service discipline. The rationale behind this strategy is that INVITE messages refer generally to new sessions and non-INVITE to transactions or sessions that have previously been accepted into the system. Therefore, in an overload condition the proposed strategy encourages the ending of sessions previously accepted by the system rather than accepting new ones. To detect the overload condition we have set two thresholds, HighT H and LowT H, on the INVITE messages buffer. The proxy comes in the overload state when the number of INVITEs in the dedicated buffer is higher than HighT H, then to exit from this state the buffer occupancy must be under the LowT H. We have run a set of simulation varying these watermarks and we have obtained the better results by setting HighT H and LowT H as 80% and 60% of the INVITE buffer space respectively. In particular, setting HighT H to higher values implies a slow reaction to overload, while setting LowT H to lower values leads to the rejection of INVITEs that could be served by the proxy. Furthermore, increasing beyond the 20% the distance between these thresholds implies the enlargement of the rejection phase risking the proxy underutilization. These reasons explain our pick, confirmed by simulation analysis omitted for sake of brevity. In order to set the buffer space, we consider that during a session the SIP proxy manages seven messages: one INVITE and six non-INVITE. Hence the size of the two buffers are set accordingly to this ratio, i.e. 1 to 6. The simulation study for the diverse queueing structures is carried out assuming the same overall buffer space for the queueing system, independently if it has one or two buffers. The overall buffer space is indicated as B. Then the size of buffer reserved for INVITE messages, denoted as dimM AX, is equal to 1/7 of B, both in
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case of Round Robin or ”Combined FIFO and Priority” service discipline. Obviously, in case of single buffer dimM AX is set equal to B. During the simulation we have analyzed the system performance using two different values of B. In particular, the two values of B have been chosen according to the following considerations. When B = 49, in no-overload condition the queueing delay of a message is in the worst case 490 ms. This implies that there are no INVITE retransmissions triggered by the SIP timers. In the case of setting B around 100, the worst case queueing delay is about 1 s. Hence INVITE retransmissions happen with a probability increasing with the increase of the offered load. In summary we have considered two set of simulations, for each set we consider the three different service disciplines considered for the queueing system at TU level. The parameters for these simulation sets are the following: • Simulation set number 1: B = 49 and dimM AX = 7 in the case of two buffers; • Simulation set number 2: B = 105 and dimM AX = 15 in the case of two buffers. VI. S IMULATION RESULTS The simulation study has been organized in two phases. The first one is aimed at evaluating the impact on system performance of the scheduling discipline adopted at TU level and of buffer size B. The second phase concerns the simulation of system performance in presence and in absence of the 503 Service Unavailable error message. In the evaluation of system performance, we use the following definition: • Call Set up Delay (CSD) is estimated as the difference between the time when the ACK arrives to the UAS (corresponding to the end of the session set up procedure) and the time when the UAC sends the INVITE message (corresponding to the begin of the session set up procedure), see Figure 1 • Accepted INVITE: INVITE message entered in the TU queueing system (i.e. the messages arrived to TU, but dropped due to buffer overflow, are not considered) • Terminated INVITE: INVITE message whose associated state machine arrives to the Terminated state; this corresponds to the event the session set up procedure has been ended. A. Queueing discipline and buffer size In the simulation analysis, we indicate with FIFO, RR and Priority the results respectively referring to the FIFO, the Round Robin and the Combined FIFO and Priority service discipline. The simulation time for each run has been set to 10.000 s. However, the performance parameters have been measured after the transient period estimated equal to 500 s; during this period no data have been collected. The simulation results reported in this paragraph have been obtained assuming a ρo = 0.8. To quantitatively compare the system performance, we summarize the results in Table I. The Table clearly shows that better results are obtained by Priority with B = 49.
TABLE I Q UEUEING S TRUCTURES C OMPARISON
#Accepted #Terminated
PRIO 182678 152725
B = 49 mess. FIFO RR 167936 183211 130304 130304
B = 105 mess. PRIO FIFO RR 230983 234439 179059 149103 130534 134487
TABLE II P ERFORMANCE COMPARISON FOR DIFFERENT SERVICE DISCIPLINES AND VALUES OF B
Terminated
B=49 mess. PRIO FIFO RR 83% 77% 71%
B=105 mess. PRIO FIFO RR 80% 55% 75%
Indeed, it has the higher number of Terminated INVITE compared to the accepted ones. This means that the probability to successfully conclude the session setup procedure once the INVITE message has been accepted is higher for the Priority scheme. In fact, when overload occurs the non-INVITE messages associated to a previous accepted INVITE have higher priority than other messages and it assures the completion of sessions already accepted by the overloaded proxy. Table II reports the results in terms of percentage of Terminated INVITEs (i.e. terminated call set up procedures) with respect to the Accepted ones. This Table clearly indicates the Priority scheme with B = 49 is the solution providing the best performance. Focusing the analysis on buffer size B and on the total number of accepted INVITEs, we observe an increase of 26.4%, while the percentage of Terminated INVITEs passes from 83% for B = 105 to 80% for B = 49. This negligible improvement after the increase of B can be explained observing that in overload condition the surplus of buffer space is mainly consumed by the retransmitted INVITEs. These messages increase the offered traffic and processing work, but have no effect on the number of session set up procedures successfully completed (i.e. number of Terminated INVITEs). Indeed, retransmissions are absorbed by the already existing state machines. On the contrary, the presence of the retransmitted INVITEs increases the queueing delay and then stimulates new retransmissions. The simulation results obtained with the two values of B show that the 66% of terminated sessions in case of B = 49 has a CSD 10s (an acceptable CSD for the end user), while for B = 105 this value is reduced to 63.5%. This behaviour is confirmed even increasing the offered load to ρo = 0.95. B. With vs without 503 error message In the second phase of the simulation study, we have analyzed the impact on system performance of the adoption of the mechanism based on the 503 Service Unavailable. The analysis discussed in the previous subsection leads us to carry out the simulation study assuming the Priority scheme and B = 49. In the developed OCProxy class, we model the generation of the 503 error message with a processing time of 5 ms. The algorithm used for the service scheme and generation of 503 error message is the following:
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in no overload state, the service discipline is simple FIFO when the proxy comes into the overload state, i.e. the buffer occupancy is higher than HighT H, the buffer is served using a priority discipline; meantime for each INVITE message served in this period, the OCProxy generates the 503 error message • the proxy comes out the overload state when the INVITE buffer occupancy is below the LowT H The analysis of CSD highlights that in the case of no503 scenario the 88.3% of terminated sessions has a CSD 10s, while when the 503 error message is used this value is reduced to 66.2%. Furthermore, comparing the results obtained in the no503 and the 503 scenarios, we observe that the number of failed INVITEs (i.e. the difference between Accepted and Terminated INVITEs) is increased of 220% leading to an overall performance worsening. Indeed, the explicit rejection does not inhibit the UAC to attempt for a trial of session set up. •
Throughput/Goodput (normalized cps)
•
1 throughput FIFO throughput Prio goodput PRIO
0.9 0.8 0.7 0.6 0.5 0.4 0.3 0.2 0.1 0
0
0.2
0.4
Fig. 4.
0.6
0.8 1 1.2 1.4 1.6 Offered load (normalized cps)
1.8
2
Priority vs FIFO scheme
C. Offered load vs. Throughput In the last analysis, we have studied the throughput of served calls as a function of the offered load. In particular, we have defined as normalized CPS. We have reported in a plot the curves representing the Throughput of the SIP proxy as a function of Offered load, both expressed in terms of normalized calls/s (CPS). The normalized CPS is defined as the ratio between the considered number of calls/s and the maximum throughput of the SIP Proxy. The curves, shown in Figure 4, refer to the simulation results obtained with the FIFO and the PRIO schemes. Furthermore, in the same figure we have reported the Goodput curve for the PRIO scheme, which is defined as the rate of successful session set up procedures with a CSD 10 s; also in this case the measured values are normalized to the maximum throughput of the SIP Proxy. In all curves also the 99% confidence intervals estimated with 15 independent simulation runs are reported. The figure clearly shows that the simple adoption of the proposed Combined FIFO and Priority queueing discipline, with the thresholds mechanism used to detect the overload condition, allows us to achieve an interesting performance improvement with respect to the simple FIFO discipline, paying it with a very low complexity increase.
R EFERENCES [1] M. P. Rumsewicz, “Analysis of the effects of ss7 message discard schemes on call completion rates during overload,” IEEE/ACM Trans. Netw., vol. 1, no. 4, pp. 491–502, 1993. [2] ns-2 Development Core Team, “The Network Simulator ns-2,” 2009. http://www.isi.edu/nsnam/ns/. [3] C. J.Rosenberg, “Requirements for Management of Overload in the Session Initiation Protocol,” July 2008. SIPPING Working Group Internet Draft. [4] B. L.-L. V. Hilt, “Essential Correction to the Session Initiation Protocol (SIP) 503 (Service Unavailable) Response,” May 2007. SIP Working Group - Internet Draft. [5] B. L.-L. V. Hilt, “Design Considerations for Session Initiation Protocol (SIP) Overload Control,” March 2009. SIPPING Working Group Internet Draft. [6] C. Shen, H. Schulzrinne, and E. Nahum, “Session initiation protocol (sip) server overload control: Design and evaluation,” in Principles, Systems and Applications of IP Telecommunications. Services and Security for Next Generation Networks: Second International Conference, IPTComm 2008, Heidelberg, Germany, July 1-2, 2008. Revised Selected Papers, (Berlin, Heidelberg), pp. 149–173, Springer-Verlag, 2008. [7] P.Hosein, “Adaptive rate control based on estimation of message queueing delay.,” 2002. United States Patent US 6,442,139 B1. [8] M. Ohta, “Overload protection in a sip signaling network,” Internet Surveillance and Protection, International Conference on, p. 11, 2006. [9] J. Rosenberg, H. Schulzrinne, G. Camarillo, A. Johnston, J. Peterson, R. Sparks, M. Handley, and E. Schooler, “Sip: Session initiation protocol,” 2002. IETF RFC 3261.
VII. C ONCLUSION The paper presents the system simulator developed extending the network simulator v.2 (ns-2) with logic for local overload control and analyzes alternatives obtained by combining queuing structures, service disciplines, and preferred buffer size. In particular, the paper proposes a queueing structure obtained combining the simple FIFO service discipline with the priority one. The simulation results clearly show that the proposed solution produces good system performance with a low complexity increase. Furthermore, the simulation results point out the weakness of the 503 Service Unavailable message mechanism, which does not introduce significant improvements with respect to the proposed solution.
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