Abstract
Information-centric networking (ICN) is an emerging network architecture that has the potential to address demands related to transmission latency and reliability in fifth-generation (5G) communication technology and the Internet of Things (IoT). As an essential component of ICN, name resolution provides the capability to translate identifiers into locators. Applications have different demands on name-resolution latency. To meet the demands, deploying name-resolution servers at the edge of the network by dividing it into multilayer overlay networks is effective. Moreover, optimization of the deployment of distributed name-resolution servers in such networks to minimize deployment costs is significant. In this paper, we first study the placement problem of the name-resolution server in ICN. Then, two algorithms called IIT-DOWN and IIT-UP are developed based on the heuristic ideas of inter-layer information transfer (IIT) and server reuse. They transfer server placement information and latency information between adjacent layers from different directions. Finally, experiments are conducted on both simulation networks and a real-world dataset. The experimental results reveal that the proposed algorithms outperform state-of-the-art algorithms such as the latency-aware hierarchical elastic area partitioning (LHP) algorithm in finding more cost-efficient solutions with a shorter execution time.
Highlights
As a network technology, the Internet of Things (IoT) [1,2,3] connects a large number of devices that are integrated with sensing, recognition, processing, communication, and networking functions.Through seamless connections and interactions between a large number of heterogeneous devices, the IoT provides a rich range of services and novel applications, changing the way we live and work [4,5]
We model the problem of latency-bounded optimal server placement in multilayer overlay networks and formulate it as an integer linear program problem with the objective of minimizing the deployment costs; We develop two algorithms based on the heuristic ideas of inter-layer information transfer (IIT)
We extended the MDS in a multilayer (MDSM) appropriately to adapt to the problem; Random allocate (RA): in this algorithm, the Hierarchical Elastic Areas Manager (HM) is chosen randomly, and users are allocated to an hierarchical elastic areas (HEAs), depending on which HM is closest to them
Summary
The Internet of Things (IoT) [1,2,3] connects a large number of devices that are integrated with sensing, recognition, processing, communication, and networking functions. Placing servers at the edge of the network is a promising solution that makes servers closer to end-users, providing a short latency response and high rate access [24] This kind of approach implies a substantial increase in deployment and operational costs. As far as we know, most previous research has focused on the server placement problem in a single layer network Methods proposed in such studies do not work so well in multilayer overlay networks because these methods consider little about the coordination between layers. We model the problem of latency-bounded optimal server placement in multilayer overlay networks and formulate it as an integer linear program problem with the objective of minimizing the deployment costs; We develop two algorithms based on the heuristic ideas of inter-layer information transfer (IIT).
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