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Register a new userOptimized Routing and Spectrum Assignment for Video Communication over an Elastic Optical Network
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Elastic optical network (EON) efficiently utilize spectral resources for optical fiber communication by allocating the minimum necessary bandwidth to client demands. On the other hand, network traffic has been continuously increasing due to the wide penetration of video streaming services, so the efficient and cost-effective use of available bandwidth plays an important role in improving service provisioning. In this work, we formulate and solve an optimization problem to perform routing and spectrum assignment (RSA) in EON with focus on video streaming. In this formulation, EON and video constraints such as spectrum fragmentation and received video quality are considered jointly. In this way, we utilize a machine learning (ML) technique to estimate the video quality versus channel state. The proposed algorithm is evaluated over two benchmarks fiber-optic network, namely NSFNET and US-backbone using numerical simulations based on random traffic models. The results reveal that the mean optical signal-to-noise ratio (OSNR) for video content data in the receiver is remarkably higher than in non-video data. This is while the blocking ratio is the same for both data types.
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Elastic Optical Network (EON) has been considered as a promising optical networking technology to architect the next-generation backbone networks. Routing and Spectrum Assignment (RSA) is the fundamental problem in EONs to realize service provisioning. Generally, the RSA is solved by routing the requests with lightpaths first and then assigning spectrum resources to the lightpaths to optimize the spectrum usage. Thus, the spectrum assignment explicitly decide the final spectrum usage of EONs. However, besides the spectrum assignment, there are three other factors, the network topology, traffic distribution and routing scheme, implicitly impact on the spectrum usage. Few related work involves in the implicit impact mechanism. In this paper, we aim to provide a thoroughly theoretical analysis on the impact of the three key factors on the spectrum usage. To this end, two theoretical chains are proposed: (1) The optimal spectrum usage can be measured by the chromatic number of the conflict graph, which is positively correlated to the intersecting probability, emph{i.e.}, the smaller the intersecting probability, the smaller the optimal spectrum usage; (2) The intersecting probability is decided by the network topology, traffic distribution and routing scheme via a quadratic programming parameterized with a matrix of conflict coefficients. The effectiveness of our theoretical analysis has been validated by extensive numerical results. Meanwhile, our theoretical deductions also permit to give several constant approximation ratios for RSA algorithms.
Content Delivery Networks (CDN) are witnessing the outburst of video streaming (e.g., personal live streaming or Video-on-Demand) where the video content, produced or accessed by mobile phones, must be quickly transferred from a point to another of the network. Whenever a user requests a video not directly available at the edge server, the CDN network must 1) identify the best location in the network where the content is stored, 2) set up a connection and 3) deliver the video as quickly as possible. For this reason, existing CDNs are adopting an overlay structure to reduce latency, leveraging the flexibility introduced by the Software Defined Networking (SDN) paradigm. In order to guarantee a satisfactory Quality of Experience (QoE) to users, the connection must respect several Quality of Service (QoS) constraints. In this paper, we focus on the sub-problem 2), by presenting an approach to efficiently compute and maintain paths in the overlay network. Our approach allows to speed up the transfer of video segments by finding minimum delay overlay paths under constraints on hop count, jitter, packet loss and relay processing capacity. The proposed algorithm provides a near-optimal solution, while drastically reducing the execution time. We show on traces collected in a real CDN that our solution allows to maximize the number of fast video transfers.
High communication speed and sufficient energy supply are the directions of technological development. Energy and information available anywhere and anytime has always been peoples good wishes. On this basis, resonant beam system (RBS) has demonstrated its unique superiority in meeting the needs for energy and communication. The previous work has mostly focused on the analysis of charging performance of RBS and its steady-state characteristics. In order to analyze the communication performance of RBS more thoroughly, we propose a resonant beam charging and communication (RBCC) system and use the equivalent circuit analysis method to conduct transient analysis on it. The equivalent circuit reveals the dynamic establishment process of the resonant beam from scratch, which facilitates the analysis of the relaxation oscillation process and a deeper understanding of the energy transmission and communication performance. In addition, we explore the energy transmission and communication performance of the RBCC under different energy allocation strategies.
Even though channel assignment has been studied for years, the performance of most IEEE 802.11-based multi-hop wireless networks such as wireless sensor network (WSN), wireless mesh network (WMN), mobile ad hoc network (MANET) is limited by channel interference. Properly assigning orthogonal channels to wireless links can improve the throughput of multi-hop networks. To solve the dynamic channel assignment problem, a routing-based channel assignment algorithm called R-CA is proposed. R-CA can allocate channels for wireless nodes when needed and free channels after data transmission. Thus more channel resource can be explored by wireless nodes. Simulation results show that R-CA can effectively enhance the network throughput and packet delivery rate.
In this paper, we develop a framework for an innovative perceptive mobile (i.e. cellular) network that integrates sensing with communication, and supports new applications widely in transportation, surveillance and environmental sensing. Three types of sensing methods implemented in the base-stations are proposed, using either uplink or downlink multiuser communication signals. The required changes to system hardware and major technical challenges are briefly discussed. We also demonstrate the feasibility of estimating sensing parameters via developing a compressive sensing based scheme and providing simulation results to validate its effectiveness.
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