LSTM-based prediction plus a four-level fuzzy classifier is applied to SDN server load balancing and is shown in a small simulation to avoid overload better than random or round-robin selection.
Sip Overload Control Testbed: Design, Building and Evaluation
1 Pith paper cite this work. Polarity classification is still indexing.
abstract
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.
citation-role summary
citation-polarity summary
fields
cs.NI 1years
2025 1verdicts
CONDITIONAL 1roles
background 1polarities
unclear 1representative citing papers
citing papers explorer
-
Optimizing Server Load Distribution in Multimedia IoT Environments through LSTM-Based Predictive Algorithms
LSTM-based prediction plus a four-level fuzzy classifier is applied to SDN server load balancing and is shown in a small simulation to avoid overload better than random or round-robin selection.