Controlling Overload in SIP Proxies: An Adaptive Window Based Approach Using No Explicit Feedback

Homayouni, Maryam; Nemati, Hani; Azhari, Vahid; Akbari, Ahmad

doi:10.1109/glocom.2010.5684311

Cited by 24 publications

(17 citation statements)

References 8 publications

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“…Homayouni, Maryam, et al [5] proposed a distributed and end-to-end adaptive window based overload control algorithm, by which upstream SIP servers control the amount of calls that are forwarded to a downstream SIP server in an attempt to prevent it from being overloaded. It takes nature and cause of overload together.…”

Section: Rate-based Overload Controlmentioning

confidence: 99%

Conforming normalised behaviour of SIP server overload control mechanism

Mishra¹,

Srivastava²,

Upadhyay³

2014

2014 IEEE International Conference on Advanced Communications, Control and Computing Technologies

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Overload in SIP servers is maj or hurdle for communications, especially during multimedia sessions or VoIP Calls. Earlier used mechanisms are based on multiplicative decrease with a fixed mathematical factor. This paper laid emphasis on normalization of this mathematical factor and conforming the applicability of probabilistic change during a SIP Server overload condition. This probabilistic change is based on earlier used AIMD algorithm. We show that mechanism is quite effective, preventive, and fair than the AIMD algorithm with a range of mathematical factors. Rate of transmission between the sender and receivers are adj usted accordingly.

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Section: Rate-based Overload Controlmentioning

confidence: 99%

Conforming normalised behaviour of SIP server overload control mechanism

Mishra¹,

Srivastava²,

Upadhyay³

2014

2014 IEEE International Conference on Advanced Communications, Control and Computing Technologies

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“…By considering a dataset consists of h-tuple of ( ̅ , ̅ , , p ̅ q , m ̅ q ) =1,..,ℎ , the proposed model determine the optimal values of and , where ̅ , ̅ , , ̅ , and ̅ indicating the number of local calls in server , number of outbound calls of server , CPU and memory usages in server , respectively. By considering the first constraint, the objective functions in these two models are designed in a way that minimizes the sum of difference between measured values of ̅ and ̅ as 1 is used. Finally, to implement LB-CAC and solve the mathematical models, MATLAB software is utilized.…”

Section: B Calculation Of α and βmentioning

confidence: 99%

“…SIP is an application layer signaling protocol standardized by IETF for initiating, modifying, and tearing down multimedia sessions [1]. The architecture of SIP protocol consists of two entities including User Agent (UA) and SIP Server (briefly referred as server).…”

Section: Introductionmentioning

confidence: 99%

Overload Control in SIP Networks: A Heuristic Approach Based on Mathematical Optimization

Montazerolghaem¹,

Moghaddam²,

Tashtarian³

2014

2015 IEEE Global Communications Conference (GLOBECOM)

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Abstract-The Session Initiation Protocol (SIP) is an application-layer control protocol for creating, modifying and terminating multimedia sessions. An open issue is the control of overload that occurs when a SIP server lacks sufficient CPU and memory resources to process all messages. We prove that the problem of overload control in SIP network with a set of n servers and limited resources is in the form of NP-hard. This paper proposes a Load-Balanced Call Admission Controller (LB-CAC) based on a heuristic mathematical model to determine an optimal resource allocation in such a way that maximizes call admission rates regarding the limited resources of the SIP servers. In fact, LB-CAC by having some critical information of SIP servers determines the optimal "call admission rates" and "signaling paths" for admitted calls along optimal allocation of CPU and memory resources of the SIP servers through a new linear programming model. A comparison between the numerical and experimental results implies the efficiency of the proposed method.

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“…When a transaction finishes, its delay is calculated and added to the list of recent transactions' delays; then the average of recent delays is calculated and if the amount of this average is more than multiplication of alpha by momentary delay, the magnitude of window will be equal to one and the window potential size, which we call WINth afterwards, reduces to half of the window size. The threshold of WINth accelerates the proceeding of window increase so that if the window size is lower than WINth, window size will be increase by one unit; and if it is higher than that, it will increase by amount of 1/W [33]. The pseudo-code of how window size will change during establishing a connection is as follows.…”

Section: Overload Control Algorithmmentioning

confidence: 99%

SIP Overload Control Testbed: Design, Building and Evaluation

Montazerolghaem¹,

Yaghmaee²

2013

IJASA

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Having facilities such as being in text form, end-to-end connection establishment, and being independence from the type of transmitted data, SIP protocol is a good choice for signaling protocol in order to set up a connection between two users of an IP network. Although utilization of SIP protocol in a wide range of applications has made various vulnerabilities in this protocol, amongst which overload could make serious problems in SIP servers. A SIP is overloaded when it does not have sufficient resources (majorly CPU processing power and memory) to process all messages. In this paper the window-based overload control mechanism which does not require explicit feedback is developed and implemented on Asterisk open source proxy and evaluated. The results of implementation show that this method could practically maintain throughput in case of overload. As we know this is the only overload control method which is implemented on a real platform without using explicit feedback. The results show that the under load server maintains its throughput at the maximum capacity.

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Controlling Overload in SIP Proxies: An Adaptive Window Based Approach Using No Explicit Feedback

Cited by 24 publications

References 8 publications

Conforming normalised behaviour of SIP server overload control mechanism

Conforming normalised behaviour of SIP server overload control mechanism

Overload Control in SIP Networks: A Heuristic Approach Based on Mathematical Optimization

SIP Overload Control Testbed: Design, Building and Evaluation

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