Decoding Delay Minimization in Inter-Session Network Coding

Intra-session network coding has been shown to offer significant gains in terms of achievable throughput and delay in settings where one source multicasts data to several clients. In this paper, we consider a more general scenario where multiple sources transmit data to sets of clients over a wireline overlay network. We propose a novel framework for efficient rate allocation in networks where intermediate network nodes have the opportunity to combine packets from different sources using randomized network coding. We formulate the problem as the minimization of the average decoding delay in the client population and solve it with a gradient-based stochastic algorithm. Our optimized inter-session network coding solution is evaluated in different network topologies and is compared with basic intra-session network coding solutions. Our results show the benefits of proper coding decisions and effective rate allocation for lowering the decoding delay when the network is used by concurrent multicast sessions.

Distributed Rate Allocation in Inter-Session Network Coding

In this work, we propose a distributed rate allocation algorithm that minimizes the average decoding delay for multimedia clients in inter-session network coding systems. We consider a scenario where the users are organized in a mesh network and each user requests the content of one of the available sources. We propose a novel distributed algorithm where network users determine the coding operations and the packet rates to be requested from the parent nodes, such that the decoding delay is minimized for all clients. A rate allocation problem is solved by every user, which seeks the rates that minimize the average decoding delay for its children and for itself. Since this optimization problem is a priori non-convex, we introduce the concept of equivalent packet flows, which permits to estimate the expected number of packets that every user needs to collect for decoding. We then decompose our original rate allocation problem into a set of convex subproblems, which are eventually combined to obtain an effective approximate solution to the delay minimization problem. The results demonstrate that the proposed scheme eliminates the bottlenecks and reduces the decoding delay experienced by users with limited bandwidth resources. We validate the performance of our distributed rate allocation algorithm in different video streaming scenarios using the NS-3 network simulator. We show that our system is able to take benefit of inter-session network coding for simultaneous delivery of video sessions in networks with path diversity.

Interactive free viewpoint video streaming using prioritized network coding

In free viewpoint applications, the images are captured by an array of cameras that acquire a scene of interest from different perspectives. Any intermediate viewpoint not included in the camera array can be virtually synthesized by the decoder, at a quality that depends on the distance between the virtual view and the camera views available at decoder. Hence, it is beneficial for any user to receive camera views that are close to each other for synthesis. This is however not always feasible in bandwidth-limited overlay networks, where every node may ask for different camera views. In this work, we propose an optimized delivery strategy for free viewpoint streaming over overlay networks. We introduce the concept of layered quality-of-experience (QoE), which describes the level of interactivity offered to clients. Based on these levels of QoE, camera views are organized into layered subsets. These subsets are then delivered to clients through a prioritized network coding streaming scheme, which accommodates for the network and clients heterogeneity and effectively exploit the resources of the overlay network. Simulation results show that, in a scenario with limited bandwidth or channel reliability, the proposed method outperforms baseline network coding approaches, where the different levels of QoE are not taken into account in the delivery strategy optimization.

Content-Aware Delivery of Scalable Video in Network Coding Enabled Named Data Networks

In this work, we propose a novel network coding enabled NDN architecture for the delivery of scalable video. Our scheme utilizes network coding in order to address the problem that arises in the original NDN protocol, where optimal use of the bandwidth and caching resources necessitates the coordination of the forwarding decisions. To optimize the performance of the proposed network coding based NDN protocol and render it appropriate for transmission of scalable video, we devise a novel rate allocation algorithm that decides on the optimal rates of Interest messages sent by clients and intermediate nodes. This algorithm guarantees that the achieved flow of Data objects will maximize the average quality of the video delivered to the client population. To support the handling of Interest messages and Data objects when intermediate nodes perform network coding, we modify the standard NDN protocol and introduce the use of Bloom filters, which store efficiently additional information about the Interest messages and Data objects. The proposed architecture is evaluated for transmission of scalable video over PlanetLab topologies. The evaluation shows that the proposed scheme performs very close to the optimal performance

NetCodCCN: a Network Coding approach for Content-Centric Networks

Content-Centric Networking (CCN) naturally supports multi-path communication, as it allows the simultaneous use of multiple interfaces (e.g. LTE and WiFi). When multiple sources and multiple clients are considered, the optimal set of distribution trees should be determined in order to optimally use all the available interfaces. This is not a trivial task, as it is a computationally intense procedure that should be done centrally. The need for central coordination can be removed by employing network coding, which also offers improved resiliency to errors and large throughput gains. In this paper, we propose NetCodCCN, a protocol for integrating network coding in CCN. In comparison to previous works proposing to enable network coding in CCN, NetCodCCN permit Interest aggregation and Interest pipelining, which reduce the data retrieval times. The experimental evaluation shows that the proposed protocol leads to significant improvements in terms of content retrieval delay compared to the original CCN. Our results demonstrate that the use of network coding adds robustness to losses and permits to exploit more efficiently the available network resources. The performance gains are verified for content retrieval in various network scenarios.

Approximate decoding approaches for network coded correlated data

This paper considers a framework where data from correlated sources are transmitted with the help of network coding in ad hoc network topologies. The correlated data are encoded independently at sensors and network coding is employed in the intermediate nodes in order to improve the data delivery performance. In such settings, we focus on the problem of reconstructing the sources at decoder when perfect decoding is not possible due to losses or bandwidth variations. We show that the source data similarity can be used at decoder to permit decoding based on a novel and simple approximate decoding scheme. We analyze the influence of the network coding parameters and in particular the size of finite coding fields on the decoding performance. We further determine the optimal field size that maximizes the expected decoding performance as a trade-off between information loss incurred by limiting the resolution of the source data and the error probability in the reconstructed data. Moreover, we show that the performance of the approximate decoding improves when the accuracy of the source model increases even with simple approximate decoding techniques. We provide illustrative examples showing how the proposed algorithm can be deployed in sensor networks and distributed imaging applications.

RC-NDN: Raptor Codes Enabled Named Data Networking

Information-centric networking (ICN) has been proposed to cope with the drawbacks of the Internet Protocol, namely scalability and security. The majority of research efforts in ICN have focused on routing and caching in wired networks, while little attention has been paid to optimizing the communication and caching efficiency in wireless networks. In this work, we study the application of Raptor codes to Named Data Networking (NDN), which is a popular ICN architecture, in order to minimize the number of transmitted messages and accelerate content retrieval times. We propose RC-NDN, which is a NDN compatible Raptor codes architecture. In contrast to other coding-based NDN solutions that employ network codes, RC-NDN considers security architectures inherent to NDN. Moreover, different from existing network coding based solutions for NDN, RC-NDN does not require significant computational resources, which renders it appropriate for low cost networks. We evaluate RC-NDN in mobile scenarios with high mobility. Evaluations show that RC-NDN outperforms the original NDN significantly. RC-NDN is particularly efficient in dense environments, where retrieval times can be reduced by 83% and the number of Data transmissions by 84.5% compared to NDN.

Network Store: Exploring Slicing in Future 5G Networks

In this paper, we present a revolutionary vision of 5G networks, in which SDN programs wireless network functions, and where Mobile Network Operators (MNO), Enterprises, and Over-The-Top (OTT) third parties are provided with NFV-ready Network Store. The proposed Network Store serves as a digital distribution platform of programmable Virtualized Network Functions (VNFs) that enable 5G application use-cases. Currently existing application stores, such as Apple's App Store for iOS applications, Google's Play Store for Android, or Ubuntu's Software Center, deliver applications to user specific software platforms. Our vision is to provide a digital marketplace, gathering 5G enabling Network Applications and Network Functions, written to run on top of commodity cloud infrastructures, connected to remote radio heads (RRH). The 5G Network Store will be the same to the cloud as the application store is currently to a software platform.

Feasibility and acceptance of electronic quality of life assessment in general practice: an implementation study

Background Patients' health related quality of life (HRQoL) has rarely been systematically monitored in general practice. Electronic tools and practice training might facilitate the routine application of HRQoL questionnaires. Thorough piloting of innovative procedures is strongly recommended before the conduction of large-scale studies. Therefore, we aimed to assess i) the feasibility and acceptance of HRQoL assessment using tablet computers in general practice, ii) the perceived practical utility of HRQoL results and iii) to identify possible barriers hindering wider application of this approach. Methods Two HRQoL questionnaires (St. George's Respiratory Questionnaire SGRQ and EORTC QLQ-C30) were electronically presented on portable tablet computers. Wireless network (WLAN) integration into practice computer systems of 14 German general practices with varying infrastructure allowed automatic data exchange and the generation of a printout or a PDF file. General practitioners (GPs) and practice assistants were trained in a 1-hour course, after which they could invite patients with chronic diseases to fill in the electronic questionnaire during their waiting time. We surveyed patients, practice assistants and GPs regarding their acceptance of this tool in semi-structured telephone interviews. The number of assessments, HRQoL results and interview responses were analysed using quantitative and qualitative methods. Results Over the course of 1 year, 523 patients filled in the electronic questionnaires (1–5 times; 664 total assessments). On average, results showed specific HRQoL impairments, e.g. with respect to fatigue, pain and sleep disturbances. The number of electronic assessments varied substantially between practices. A total of 280 patients, 27 practice assistants and 17 GPs participated in the telephone interviews. Almost all GPs (16/17 = 94%; 95% CI = 73–99%), most practice assistants (19/27 = 70%; 95% CI = 50–86%) and the majority of patients (240/280 = 86%; 95% CI = 82–91%) indicated that they would welcome the use of electronic HRQoL questionnaires in the future. GPs mentioned availability of local health services (e.g. supportive, physiotherapy) (mean: 9.4 ± 1.0 SD; scale: 1 – 10), sufficient extra time (8.9 ± 1.5) and easy interpretation of HRQoL results (8.6 ± 1.6) as the most important prerequisites for their use. They believed HRQoL assessment facilitated both communication and follow up of patients' conditions. Practice assistants emphasised that this process demonstrated an extra commitment to patient centred care; patients viewed it as a tool, which contributed to the physicians' understanding of their personal condition and circumstances. Conclusion This pilot study indicates that electronic HRQoL assessment is technically feasible in general practices. It can provide clinically significant information, which can either be used in the consultation for routine care, or for research purposes. While GPs, practice assistants and patients were generally positive about the electronic procedure, several barriers (e.g. practices' lack of time and routine in HRQoL assessment) need to be overcome to enable broader application of electronic questionnaires in every day medical practice.

Highly accurate evaluation of GPS synchronization for TDOA localization

Clock synchronization is critical for the operation of a distributed wireless network system. In this paper we investigate on a method able to evaluate in real time the synchronization offset between devices down to nanoseconds (as needed for positioning). The method is inspired by signal processing algorithms and relies on fine-grain time information obtained during the reconstruction of the signal at the receiver. Applying the method to a GPS-synchronized system show that GPS-based synchronization has high accuracy potential but still suffers from short-term clock drift, which limits the achievable localization error.

An Evaluation of Compression Schemes for Wireless Networks

Data gathering, either for event recognition or for monitoring applications is the primary intention for sensor network deployments. In many cases, data is acquired periodically and autonomously, and simply logged onto secondary storage (e.g. flash memory) either for delayed offline analysis or for on demand burst transfer. Moreover, operational data such as connectivity information, node and network state is typically kept as well. Naturally, measurement and/or connectivity logging comes at a cost. Space for doing so is limited. Finding a good representative model for the data and providing clever coding of information, thus data compression, may be a means to use the available space to its best. In this paper, we explore the design space for data compression for wireless sensor and mesh networks by profiling common, publicly available algorithms. Several goals such as a low overhead in terms of utilized memory and compression time as well as a decent compression ratio have to be well balanced in order to find a simple, yet effective compression scheme.

TARWIS - A Testbed Management Architecture for Wireless Sensor Network Testbeds

With research on Wireless Sensor Networks (WSNs) becoming more and more mature in the past five years, researchers from universities all over the world have set up testbeds of wireless sensor networks, in most cases to test and evaluate the real-world behavior of developed WSN protocol mechanisms. Although these testbeds differ heavily in the employed sensor node types and the general architectural set up, they all have similar requirements with respect to management and scheduling functionalities: as every shared resource, a testbed requires a notion of users, resource reservation features, support for reprogramming and reconfiguration of the nodes, provisions to debug and remotely reset sensor nodes in case of node failures, as well as a solution for collecting and storing experimental data. The TARWIS management architecture presented in this paper targets at providing these functionalities independent from node type and node operating system. TARWIS has been designed as a re-usable management solution for research and/or educational oriented research testbeds of wireless sensor networks, relieving researchers intending to deploy a testbed from the burden to implement their own scheduling and testbed management solutions from scratch.