In an increasingly competitive environment it is more important than ever for operators to keep their end users satisfied. User satisfaction is often characterised in terms of Quality of Experience (QoE), a subjective metric with multiple dimensions such as expectations, content, terminal, environment, cost and performance. QoE is typically quantified as MOS, mean opinion score, which is obtained by averaging the ranks of a number of voluntary users for controlled combinations content/ terminals/performance etc. While this approach has many advantages, there are also a number of difficulties such as representativeness (the number of users as well as the number of objects and devices all have to be kept small); validity (the results may be biased by the situation, the setting, the remuneration and so on); and applicability (it is not clear how different numbers map to notions such as “acceptable” or “unacceptable” and operators alone cannot do very much about factors such as content).
Quantifying quality of experience for network applications is challenging as it is a subjective metric with multiple dimensions such as user expectation, satisfaction, and overall experience. Today, despite various techniques to support differentiated Quality of Service (QoS), the operators still lack of automated methods to translate QoS to QoE, especially for general web applications.
As mobile networks are witnessing huge growth in the volumes of data traffic from smartphone and tablet. Mobile operators start to look into CDN and caching in order to offload increasingly overloaded mobile networks, reduce network and peering cost, and improve mobile user's quality of experience.
Energy efficiency features are being integrated in network protocols and management systems. Simulations can provide input on how a particular algorithm would perform in different network conditions. However, building an environment that is able to comprehensively account for interactions between different network functions is difficult.
High availability is a key non-functional requirement that software and telecom service providers strive to achieve. With the on-going shift to Cloud computing, the challenges of satisfying the high availability requirement become more arduous, as the Cloud introduces additional features, such as on-demand access, scalability, virtualization, etc. that add to the complexity of the high availability solution.
Network Service Chaining (NSC) is a service deployment concept that promises increased flexibility and cost efficiency for future carrier networks. NSC has received considerable attention in the standardization and research communities lately. However, NSC is largely undefined in the peer-reviewed literature. In fact, a literature review reveals that the role of NSC enabling technologies is up for discussion, and so are the key research challenges lying ahead.
A “network embedded cloud”, also known as a “carrier cloud”, is a distributed cloud platform where the computing resources are embedded in, and distributed across the carrier’s network. This is a transformation of carrier-grade networks toward a platform for cloud services and the emergence of cloud computing in a telecommunication environment. In this platform the network resources are simply another set of cloud resources.
Dense-wavelength-division multiplexing (DWDM)-centric metro/aggregation networking is defined as predominantly using packet aggregation at the edges of the aggregation domain, while using DWDM at the center of the network.
The accuracy and granularity of network flow measurement play a critical role in many network management tasks, especially for anomaly detection. This work proposes a novel method that performs adaptive zooming in the aggregation of flows to be measured.
StEERING: A Software-Defined Networking for Inline Service Chaining by Ying Zhang, Neda Beheshti, Ludovic Beliveau, Geoffrey Lefebvre, Ramesh Mishra, Ritun Patney, Erik Rubow, Ramesh Subrahmaniam, Ravi Manghirmalani, Meral Shirazipour, Catherine Truchan and Mallik Tatipamula.