University of Ontario Institute of Technology
Self-healing solutions for LTE evolved packet core
Abstract
dc:description.abstractThe 3GPP Long Term Evolution (LTE) is considered as a dominant future cellular wireless technology in terms of performance and user experience. With technological advancement of the wireless networks, dependencies and business impact of the mobile network services have increased phenomenally. It is, therefore, crucial to address the issues regarding network infrastructure or service failure. In this thesis, a self-healing solution is presented for the LTE Evolved Packet Core (EPC) with a view to maintaining service continuity in the event of core network elements - the MME and S-GW failures. The core network element failures have significant impact on a larger number of subscribers in comparison to the access network element failures. In the proposed self-healing scheme, the restoration mechanisms and associate failover recovery procedures with regards to service survivability are described in details from the LTE network and protocol perspective. This thesis studies two different self-healing approaches - the centralized active-backup and distributed active-active and conducts simulation for each approach in various failure scenarios. The performances of each of these scenarios are evaluated in terms of service restoration time, throughput, EPS (Evolved Packet System) bearer delay etc. The results show that the proposed self-healing system can ensure service continuity at a certain level if resources are properly provisioned. And in terms of restoration delay, in general, the active-backup configuration performs better than the active-active configuration. The thesis presents analytical and simulation methods to estimate signaling message overhead at the LTE EPC that arises due to the recovery process. It also analyzes the bandwidth requirements of the signaling traffic that is incurred by the other operational procedures of the self-healing scheme and their ramification to the LTE core network.
Degree
thesis:*- Name thesis:degree_name
- Master of Science (MSc)
- Discipline thesis:degree_discipline
- Computer Science
- Grantor
- University of Ontario Institute of Technology
- Year dc:date.issued
- 2012
Author and committee
dc:creator, dc:contributor.*- Author dc:creator
-
- Rahman, Md. Mustafizur
- Advisor dc:contributor.advisor
-
- Heydari, Shahram
Subjects
dc:subject × 4Rights
- Language dc:language.iso
- en
Identifiers
dc:identifier.*- Handle dc:identifier.uri
- https://hdl.handle.net/10155/270
- OAI identifier oai:identifier
- oai:ontariotechu.scholaris.ca:10155/270