Overlay Protection Against Link Failures Using Network Coding

This paper introduces a network coding-based protection scheme against single and multiple link failures. The proposed strategy ensures that in a connection, each node receives two copies of the same data unit: one copy on the working circuit, and a second copy that can be extracted from linear combinations of data units transmitted on a shared protection path. This guarantees instantaneous recovery of data units upon the failure of a working circuit. The strategy can be implemented at an overlay layer, which makes its deployment simple and scalable. While the proposed strategy is similar in spirit to the work of Kamal '07 & '10, there are significant differences. In particular, it provides protection against multiple link failures. The new scheme is simpler, less expensive, and does not require the synchronization required by the original scheme. The sharing of the protection circuit by a number of connections is the key to the reduction of the cost of protection. The paper also conducts a comparison of the cost of the proposed scheme to the 1+1 and shared backup path protection (SBPP) strategies, and establishes the benefits of our strategy.Comment: 14 pages, 10 figures, accepted by IEEE/ACM Transactions on Networkin

Network Coding-based Protection Strategies Against a Single Link Failure in Optical Networks

In this paper we develop network protection strategies against a single link failure in optical networks. The motivation behind this work is the fact that $$ of all available links in an optical network suffers from a single link failure. In the proposed protection strategies, denoted NPS-I and NPS-II, we deploy network coding and reduced capacity on the working paths to provide a backup protection path that will carry encoded data from all sources. In addition, we provide implementation aspects and how to deploy the proposed strategies in case of an optical network with $n$ disjoint working paths.Comment: 6 pages, 3 figures, ICCES '0

Scalable and Cost Efficient Algorithms for Virtual CDN Migration

Virtual Content Delivery Network (vCDN) migration is necessary to optimize the use of resources and improve the performance of the overall SDN/NFV-based CDN function in terms of network operator cost reduction and high streaming quality. It requires intelligent and enticed joint SDN/NFV migration algorithms due to the evident huge amount of traffic to be delivered to end customers of the network. In this paper, two approaches for finding the optimal and near optimal path placement(s) and vCDN migration(s) are proposed (OPAC and HPAC). Moreover, several scenarios are considered to quantify the OPAC and HPAC behaviors and to compare their efficiency in terms of migration cost, migration time, vCDN replication number, and other cost factors. Then, they are implemented and evaluated under different network scales. Finally, the proposed algorithms are integrated in an SDN/NFV framework. Index Terms: vCDN; SDN/NFV Optimization; Migration Algorithms; Scalability Algorithms.Comment: 9 pages, 11 figures, 4 tableaux, conference Local Computer Networks (LCN), class

Blockage Prediction for Mobile UE in RIS-assisted Wireless Networks: A Deep Learning Approach

Due to significant blockage conditions in wireless networks, transmitted signals may considerably degrade before reaching the receiver. The reliability of the transmitted signals, therefore, may be critically problematic due to blockages between the communicating nodes. Thanks to the ability of Reconfigurable Intelligent Surfaces (RISs) to reflect the incident signals with different reflection angles, this may counter the blockage effect by optimally reflecting the transmit signals to receiving nodes, hence, improving the wireless network's performance. With this motivation, this paper formulates a RIS-aided wireless communication problem from a base station (BS) to a mobile user equipment (UE). The BS is equipped with an RGB camera. We use the RGB camera at the BS and the RIS panel to improve the system's performance while considering signal propagating through multiple paths and the Doppler spread for the mobile UE. First, the RGB camera is used to detect the presence of the UE with no blockage. When unsuccessful, the RIS-assisted gain takes over and is then used to detect if the UE is either "present but blocked" or "absent". The problem is determined as a ternary classification problem with the goal of maximizing the probability of UE communication blockage detection. We find the optimal solution for the probability of predicting the blockage status for a given RGB image and RIS-assisted data rate using a deep neural learning model. We employ the residual network 18-layer neural network model to find this optimal probability of blockage prediction. Extensive simulation results reveal that our proposed RIS panel-assisted model enhances the accuracy of maximization of the blockage prediction probability problem by over 38\% compared to the baseline scheme