Information centric networking scheme for proactive content dissemination in named data mesh networks | |
| Author | Majeed, Muhammad Faran |
| Subject(s) | Computer networks Ad hoc networks (Computer networks) |
| Note | A dissertation submitted in partial fulfillment of the requirements for the Degree of Doctor of Philosophy in Computer Science |
| Publisher | Asian Institute of Technology |
| Abstract | From its origin, the Internet was based on sharing resources among end-systems. With the passage of time, it has spread world wide, and the primary purpose of the network has evolved from resource sharing among small distributed communities to information dissem ination and retrieval world-wide. Today, the use of the Internet is multimedia-centric. Small, powerful, and cheap hand-held devices are making multimedia information ubiquitous. Un fortunately, handling the near-term explosion of multimedia data is out of reach of the current Internet architecture. Under these circumstances, information centric networking (ICN) may prove to be a key component of the next-generation Internet architecture, because it consid ers content as the basic entity of communication instead of end-to-end systems connectivity. However, despite its promise, information centric networking has some issues that require further thorough research. Named data networking (NDN) is one of the promising architectures of ICN. In NDN, an interest message is generated by a consumer to request a content object from a producer that provides that content. Every chunk of content may beget many interests. Requiring an interest before content can be transmitted makes the NDN architecture more consumer centric than information- or content-centric. Similarly, when a multimedia content object is produced an interest for each content chunk is generated by the consumer. This not only overwhelms the network with interests but also increases latency proportional to the hop count between producer and consumer. In this dissertation, we propose a mechanism for pre-caching popular chunks of large content objects, such as videos, once they are requested by a consumer. We provide for cache col laboration between neighboring content routers (CRs) in mesh networks, keeping the cache capacity constraints of CRs in mind. We characterize pre-caching as an optimization prob lem in which the goal is to jointly minimize the number of hops from the caching node to the consumer and the number of replicas, while observing the cache constraints of each CR. We implement and empirically evaluate each of the schemes and find them to perform substantially better than the existing NDN-based schemes. Finally, we implement the architectures based on the current new forwarding daemon (NFD) of the NDN project for experiments in real world environments. NFD performs actual for warding in a live NDN-based network. The proposed architectures and schemes will help the future researchers to explore possibilities for enhance the video traffic communication for future Internet architectures. Also, the time to disseminate content among mobile nodes in a vehicular environment will be reduced. This research takes several steps toward more proactive content dissemination in named data mesh networks. It makes possible for the first time pre-caching of video content closer to possible consumers. The method reduces the hop count between the current location of the chunk and the requester, and enables proactive pushing of content and reduction of the latency between the consumer and producer. |
| Year | 2017 |
| Type | Dissertation |
| School | School of Engineering and Technology (SET) |
| Department | Department of Information and Communications Technologies (DICT) |
| Academic Program/FoS | Computer Science (CS) |
| Chairperson(s) | Dailey, Matthew N.;Apinun Tunpan (Co-Chairperson); |
| Examination Committee(s) | Kanchana Kanchanasut;Attaphongse Taparugssanagorn; |
| Scholarship Donor(s) | Shaheed Benazir Bhutto University, Sheringal Dir (Upper), Khyber Pakhtunkhwa, Pakistan;AIT Fellowship; |
| Degree | Thesis (Ph.D.) - Asian Institute of Technology, 2017 |