Towards Efficient and Scalable Data-Intensive Content Delivery: State-of-the-Art, Issues and Challenges

Abstract

This chapter presents the authors' work for the Case Study entitled "Delivering Social Media with Scalability" within the framework of High-Performance Modelling and Simulation for Big Data Applications (cHiPSet) COST Action 1406. We identify some core research areas and give an outline of the publications we came up within the framework of the aforementioned action. The ease of user content generation within social media platforms, e.g. check-in information, multimedia data, etc., along with the proliferation of Global Positioning System (GPS)-enabled, always-connected capture devices lead to data streams of unprecedented amount and a radical change in information sharing. Social data streams raise a variety of practical challenges: derivation of real-time meaningful insights from effectively gathered social information, a paradigm shift for content distribution with the leverage of contextual data associated with user preferences, geographical characteristics and devices in general, etc. In this article we present the methodology we followed, the results of our work and the outline of a comprehensive survey, that depicts the state-of-the-art situation and organizes challenges concerning social media streams and the infrastructure of the data centers supporting the efficient access to data streams in terms of content distribution, data diffusion, data replication, energy efficiency and network infrastructure. The challenges of enabling better provisioning of social media data have been identified and they were based on the context of users accessing these resources. The existing literature has been systematized and the main research points and industrial efforts in the area were identified and analyzed. In our works, in the framework of the Action, we came up with

DISCERNER: Dynamic selection of resource manager in hyper-scale cloud-computing data centres

“…Resource managers can be classified as centralised, distributed, or hybrid [1,3]. The majority of the actual industry data centres rely on centralised approaches, in particular:…”

An Effective Fairness Scheme for Named Data Networking

“…The performance of the proposed fairness scheme is depicted in Figure 5 using Jain's fairness index, which is the measure of fairness (or lack thereof) among the active flows in a network. The index ranges between 1 n and 1 (n being the number of active flows), representing "worst" and "best" fairness respectively [31]. Since there are only two active flows: "ndn://facebook.com/" and "ndn://netflix.com/"-the fairness index ranges between 0.5 and 1.0 (representing worst and best fairness respectively).…”

“…Numerous information and content delivery networks (CDNs) have been deployed on top of the existing IP networks to support information delivery. However, CDNs face issues such as efficiency, sustainability, and scalability [1,2].…”

Congestion and throughput optimization protocol for providing better quality of service and experience

“…IoT applications play a significant role in generating multimedia traffic [11]. To handle this demand, network providers optimize infrastructure, use efficient transmission protocols, and employ traffic management techniques like content delivery networks (CDNs) [12]. Multimedia traffic drives the need for network advancements to meet the demands of multimedia applications and services.…”