Overlay Network Research Articles

Distributed mitigation of content pollution in peer‐to‐peer video streaming networks

Video streaming has become increasingly popular in the Internet. Frequently, video transmissions are based on peer-to-peer networks, in which peers running on end-user hosts transmit data among themselves. An important security vulnerability of this strategy is that content can be easily altered by malicious users. Thus, it becomes essential to diagnose and fight content pollution in these systems. In this work, the authors present a novel strategy that relies on comparison-based diagnosis to mitigate content pollution in live video streaming peer-to-peer networks. This strategy is fully distributed and effectively combats the dissemination of content pollution. In the strategy, peers independently identify and avoid polluters. The solution works on top of the scalable overlay network Fireflies. Experimental results are presented showing the effectiveness and the low overhead of the solution. In particular, the strategy was able to significantly reduce content pollution propagation in diverse network configurations.

Scalable Decentralized Indexing and Querying of Multi-Streams in the Fog

NOA-AID (Network Overlays for Adaptive information Aggregation, Indexing and Discovery on the fog) is an approach for decentralized indexing, aggregation and discovery of data belonging to streams. It is organized on two network layers. The upper layer is in charge of delivering an information discovery approach by providing a distributed index structure. The lower layer is devoted to resource aggregation based on epidemic protocols designed for highly dynamic environment, well suited to stream-oriented scenarios. It defines a flexible approach to express queries targeting highly heterogeneous data, as well as a self-organizing dynamic system allowing the optimal resolution of queries on the most suitable stream producers. The paper also presents a theoretical study and discusses the costs related to information management operations; it also gives an empirical validation of findings. Finally, it reports an extended experimental evaluation that demonstrated the ability of NOA-AID to be effective and efficient for retrieving information extracted from streams in highly-dynamic and distributed processing architectures.

Development of algorithms of self-organizing network for reliable data exchange between autonomous robots

Factors affecting the reliability of data transmission in networks with nodes with periodic availability were considered. The principles of data transfer between robots are described; the need for global connectivity of communications within an autonomous system is shown, since the non-availability of information on the intentions of other robots reduces the effectiveness of the robotics system as a whole and affects the fault tolerance of a team of independent actors performing distributed activities. It is shown that the existing solutions to the problem of data exchange based on general-purpose IP networks have drawbacks; therefore, as the basis for organizing autonomous robot networks, we used developments in the domain of topological models of communication systems allowing us to build self-organizing computer networks. The requirements for the designed network for reliable message transfer between autonomous robots are listed, the option of organizing reliable message delivery using overlay networks, which expand the functionality of underlying networks, is selected. An overview of existing popular controlled and non-controlled overlay networks is given; their applicability for communication within a team of autonomous robots is evaluated. The features and specifics of data transfer in a team of autonomous robots are listed. The algorithms and architecture of the overlay self-organizing network were described by means of generally accepted methods of constructing decentralized networks with zero configurations. As a result of the work, general principles of operation of the designed network were proposed, the message structure for the delivery algorithm was described; two independent data streams were created, i.e. service and payload; an algorithm for sending messages between network nodes and an algorithm for collecting and synchronizing the global network status were developed. In order to increase the dependability and fault tolerance of the network, it is proposed to store the global network status at each node. The principles of operation of a distributed storage are described. For the purpose of notification on changes in the global status of the network, it is proposed to use an additional data stream for intra-network service messages. A flood routing algorithm was developed to reduce delays and speed up the synchronization of the global status of a network and consistency maintenance. It is proposed to provide network connectivity using the HELLO protocol to establish and maintain adjacency relations between network nodes. The paper provides examples of adding and removing network nodes, examines possible scalability problems of the developed overlay network and methods for solving them. It confirms the criteria and indicators for achieving the effect of self-organization of nodes in the network. The designed network is compared with existing alternatives. For the developed algorithms, examples of latency estimates in message delivery are given. The theoretical limitations of the overlay network in the presence of intentional and unintentional defects are indicated; an example of restoring the network after a failure is set forth.

Channel-Aware Power Allocation and Decoding Order in Overlay Cognitive NOMA Networks

To further improve spectral efficiency, this paper considers a non-orthogonal multiple access (NOMA)-assisted overlay cognitive radio network consisting of a pair of primary users and a pair of secondary users. In this network, communication between the pair of primary users is achieved with the help of the secondary transmitter (ST). In return, ST can communicate with the secondary receiver by sending a superimposed signal consisting of its own message and the received primary message. We intend to minimize the outage probability of the secondary system under quality-of-service constraints of the primary system by jointly optimizing the power allocation (PA) factor at ST and the decoding order (DO) at the receivers. When full channel state information (CSI) is available at ST, the optimal PA and DO are derived in closed form under the constraint that the target rate of the primary system should be guaranteed. When only statistical CSI is available at ST, the optimal PA and DO are derived in closed form or by using a bisection method, under the constraints that the outage probability of the primary system is not more than a predetermined threshold and is not larger than that of the secondary system. For the proposed strategies, outage probability expressions of the primary and secondary systems are derived in closed form or semi-closed form. Numerical results are shown to verify our analysis and demonstrate the superiority of the proposed strategies in different CSI-availability scenarios.

Research on Cloud Manufacturing Overlay Network Technology Based on Web of Things

In recent years, the combination of the Web of things and various manufacturing technologies has become a hot issue in academia. The emergence of intelligent manufacturing technology based on the Web of things has been repeatedly proposed by various industrial enterprises and researchers. On this basis, a new manufacturing mode of cloud manufacturing technology is proposed. It can be seen that the Web of things technology combined with cloud manufacturing is the key technology to realize intelligent manufacturing thinking in today’s society. This paper summarizes the overall architecture of the Web of things coverage network through a brief analysis of cloud manufacturing technology, and finally comes to a conclusion.

Routing Based Multi-Agent System for Network Reliability in the Smart Microgrid.

Microgrids help to achieve power balance and energy allocation optimality for the defined load networks. One of the major challenges associated with microgrids is the design and implementation of a suitable communication-control architecture that can coordinate actions with system operating conditions. In this paper, the focus is to enhance the intelligence of microgrid networks using a multi-agent system while validation is carried out using network performance metrics i.e., delay, throughput, jitter, and queuing. Network performance is analyzed for the small, medium and large scale microgrid using Institute of Electrical and Electronics Engineers (IEEE) test systems. In this paper, multi-agent-based Bellman routing (MABR) is proposed where the Bellman–Ford algorithm serves the system operating conditions to command the actions of multiple agents installed over the overlay microgrid network. The proposed agent-based routing focuses on calculating the shortest path to a given destination to improve network quality and communication reliability. The algorithm is defined for the distributed nature of the microgrid for an ideal communication network and for two cases of fault injected to the network. From this model, up to 35%–43.3% improvement was achieved in the network delay performance based on the Constant Bit Rate (CBR) traffic model for microgrids.

Two Optimization Algorithms for Name-Resolution Server Placement in Information-Centric Networking

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.

Research on the Load Distribution Strategy to Meet the QoE Requirements for Conversational Real-Time HD Video Service

A reliable transmission with QoE (Quality of Experience) guarantee is crucial for internet conversational service applications. However, due to the limited network bandwidth bottleneck effect and the drawback of transmission technology, there exists no mature and open QoE technical solution for this service. In this paper, we focused our attention on a load distribution strategy for multipath relay transmission to meet the QoE requirements of conversational real-time HD video services. It consisted of three stages: First, a series of relay nodes was deployed in the backbone network, and a software defined overlay network was constructed to perform the multipath relay transmission for the service. Second, by an analysis of the QoE feature, a bijection was built for each quantitative QoE and its MOS (Mean Opinion Score) score. Finally, considering the influence of the coupling relation between paths on the service quality in multipath relay transmission, fuzzy cooperative game theory was used to design the service load distribution strategy. Many experiments showed that compared with state-of-the-art methods in the single-path transmission scene, the strategy we designed can dynamically adjust the load distribution of each sub-path according to the change in QoS (Quality of Service) information of the transmission path in real time. While meeting the strict real-time constraints of the service, it can effectively avoid the impact of network random congestion on the service QoE.

BER Performance of Full-Duplex Cognitive Radio Network With Nonlinear Energy Harvesting

In this paper, the bit error rate (BER) performance of a full-duplex (FD) overlay cognitive radio (CR) network with linear/nonlinear energy harvesting (EH) capability is investigated. The considered overlay CR network consists of a primary transmitter/receiver (PT/PR) pair, a secondary transmitter (ST) and an FD mode operated secondary receiver (SR) where ST harvests energy from both PT and SR during the first communication time slot. In the second communication time slot, SR receives its intended signal from ST while cooperating with PT by transmitting its signal to PR. The bit error probability (BEP) expressions for the primary/secondary users (PU/SU) are analytically derived and validated through Monte-Carlo simulations according to both linear and nonlinear EH models applied at ST. In addition, the optimum distance value between PT and ST is determined considering the objective of minimizing BER of both PU and SU. Moreover, corresponding system performances are obtained regarding a power allocation coefficient at SR to obtain the trade-off between EH and information processing. The results show that the proposed FD-CR system with nonlinear EH improves the PU BEP performance compared to the non-cooperative (direct transmission) case while the SU benefits from the spectrum of PU with a significant BER performance.

On the Performance of NOMA-Assisted Overlay Multiuser Cognitive Satellite-Terrestrial Networks

In this letter, we investigate the performance of an overlay cognitive satellite-terrestrial network comprising a primary satellite source with its multiple terrestrial receivers and a secondary transmitter-receiver pair on the ground. Herein, the primary satellite source employs a non-orthogonal multiple access (NOMA) scheme to simultaneously serve its all users, while the secondary transmitter assists the primary communication through cooperative relaying technique in exchange for spectrum access. For this overall set-up, we obtain the closed-form expressions for the outage probability of primary satellite network and secondary terrestrial network by adopting pertinent heterogeneous fading models. Further, we derive the asymptotic outage behaviour at high signal-to-noise-ratio (SNR) for the primary and secondary networks, and thereby calculate the achievable diversity orders. Our analytical findings are corroborated through various numerical and simulation results.

Cluster system management

Cluster system management (CSM) was co-designed with the Department of Energy Labs to provide the support necessary to effectively manage the Summit and Sierra supercomputers. The CSM system administration tools provide a unified view of a large-scale cluster and the ability to examine and understand data from multiple sources. CSM consists of five components: 1) application programming interfaces (APIs) and infrastructure; 2) Big Data Store; 3) support for reliability, availability, and serviceability (RAS); 4) Diagnostic and Health Check; and 5) support for job management. APIs and infrastructure provide lightweight daemons for compute nodes, hardware and software inventory collection, job accounting, and RAS. Logs, environmental data, and performance data are collected in the Big Data Store for analysis. RAS events can trigger corrective actions by CSM. Diagnostic and Health Check are provided through a diagnostic framework and test results collection. To support job management, CSM coordinates with the Job Step Manager to provide an overlay network of JSM daemons. CSM is an open source and available at <uri xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">https://github.com/IBM/CAST</uri> . Documentation can be found at <uri xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">https://cast.readthedocs.io</uri> .

Vickrey Auction-Based Secondary Relay Selection in Cognitive Hybrid Satellite-Terrestrial Overlay Networks With Non-Orthogonal Multiple Access

In this letter, we investigate the Vickrey auction-based secondary relay selection in cognitive hybrid satellite-terrestrial overlay networks (CHSTONs) with non-orthogonal multiple access (NOMA). We analyze a cooperative spectrum sharing scheme for a multi-potential secondary relay selection scenario, in which the Vickrey auction is introduced to achieve an efficient secondary relay selection by one shot within the distributed computation. Both the decode-and-forward (DF) and amplify-and-forward (AF) protocols are considered for the relay to retransmit the primary user's message, separately. Besides, the NOMA scheme is implemented to increase the total capacity in the second temporal phase. Finally, simulation results validate that the proposed auction-based approach is more effective than conventional approaches in secondary relay selection. Also, the influence of key factors on the performance of the auction mechanism is analyzed by the simulations.

Characteristics and variability of functional brain networks

Functional brain networks were constructed from functional magnetic resonance imaging (fMRI) data originating from 96 healthy adults. These networks possessed a total of 360 nodes, derived from the latest multi-modal brain parcellation method. A novel group network (overlay network) analysis model is proposed to study common attributes as well as differences found in the human brain by analysis of the functional brain network. Currently, the mean network is generally used to represent the group network. But mean networks have a modularity problem making them distinct from real networks. The overlay network is constructed by calculating the connections between the whole brain network regions, and then filtering the connections by limiting the threshold value. We find that the overlay network is closer to the real network condition of the group in terms of network characteristics related to modularity. Multiple network features are applied to investigate the discrepancies between the new group network and the mean network. Individual divergences between brain regions of everyone are also explored. Results show that the brain network of different people has a high consistency in the global measures, while there exist great differences for local measures in brain regions. Some brain regions show variability over other brain regions on most measures. In addition, we explored the impact of different thresholds on the overlay network and find that different thresholds have a greater impact on the clustering coefficient, maximized modularity, strength, and global efficiency.

Rock, Paper, Scissors Game Based Model for Content Discovery in P2P MANETs

Resource discovery is a key challenge in dynamic environment such as Peer-to-Peer (P2P) MANETs. To leverage the lookup costs and efficiently discover the resources, the peers in a P2P network communicate with each other forming one-or-more overlay structure. And, thus the peer’s connections in such overlay networks plays a crucial role. To harness this, we propose a model that focuses on the underlying network topology as each virtual link of the overlay network is supported by a path in the underlying physical network. Also, we design a new resource discovery algorithm that uses the famous Rock-Paper-Scissors (RPS) game ideology. In this work, we present a Rock-Paper-Scissors-Game-Based (RPSGB) algorithm for content discovery in mobile peer-to-peer network. The proposed work focuses on providing efficient resource discovery scheme in such a dynamic network, using the game theory concepts. Our scheme is a light-weight model aimed to suit the unstructured architecture better. The major goal of this work, is to reduce the consumption of power, minimize the lookup cost, lower the bandwidth consumption, and increase the hit ratio. We compare our scheme with the traditional well-known benchmarked schemes. After evaluation, the simulation results justify the effectiveness of the proposed protocol. The obtained results show that the proposed scheme substantially decreases the network traffic, lowers the battery power and bandwidth consumption, while having good search efficiency. Also, the search latency is minimized. The result justifies that RPSGB algorithm proposes to make resource searching much more efficient, and improves the statistics against the posed challenges.

Enhancement of Security and Handling the Inconspicuousness in IoT Using a Simple Size Extensible Blockchain

Blockchain technology is increasingly used worldwide to enhance the performance and profit of any environment through its defining characteristics, such as security, auditability, immutability, and inconspicuousness. Owing to these characteristics, the blockchain can be used in various non-financial operations of some domains, such as the Internet of Things (IoT) and distributed computing. However, implementing blockchain technology in IoT is not always a feasible solution because blockchain deployment is costly, it has limited extensibility and provides irregular bandwidth and latency. In this regard, a simple size extensible (SSE) blockchain has been proposed to provide an optimal solution for IoT environments by satisfying the needs of the IoT environment as well as ensuring end-to-end security. The implementation of the proposed blockchain develops an overlay network to obtain a distributed environment where the blockchain is handled by the resources present therein. Two novel algorithms were introduced into the proposed system to minimize the irregularity and latency on one hand, and to maximize the throughput of the system on the other. The shared-time depending agreement algorithm (STD) minimizes the irregularity in the extraction operation and latency. The other, the shared throughput administration algorithm (STA) justifies the overall collection of the transmission load in the network and maintains the performance of the blockchain. The proposed system was applied to smart home IoT appliances to test the performance of the proposed system. The experimental results show that the proposed blockchain system minimizes nearly 70% of the data irregularity, latency, and furthermore, 30% of the blockchain extensibility is maximized as compared to the existing systems.

T0RTT: Non-Interactive Immediate Forward-Secret Single-Pass Circuit Construction

Abstract Maintaining privacy on the Internet with the presence of powerful adversaries such as nation-state attackers is a challenging topic, and the Tor project is currently the most important tool to protect against this threat. The circuit construction protocol (CCP) negotiates cryptographic keys for Tor circuits, which overlay TCP/IP by routing Tor cells over n onion routers. The current circuit construction protocol provides strong security guarantees such as forward secrecy by exchanging 𝒪(n 2) messages. For several years it has been an open question if the same strong security guarantees could be achieved with less message overhead, which is desirable because of the inherent latency in overlay networks. Several publications described CCPs which require only 𝒪(n) message exchanges, but significantly reduce the security of the resulting Tor circuit. It was even conjectured that it is impossible to achieve both message complexity 𝒪(n) and forward secrecy immediately after circuit construction (so-called immediate forward secrecy). Inspired by the latest advancements in zero round-trip time key exchange (0-RTT), we present a new CCP protocol Tor 0-RTT (T0RTT). Using modern cryptographic primitives such as puncturable encryption allow to achieve immediate forward secrecy using only 𝒪(n) messages. We implemented these new primitives to give a first indication of possible problems and how to overcome them in order to build practical CCPs with 𝒪(n) messages and immediate forward secrecy in the future.

Cognitive Radio-Assisted NOMA Broadcasting for 5G Cellular V2X Communications: Model of Roadside Unit Selection and SWIPT.

The outage performance is a significant problem to implement the Cognitive Radio (CR) paradigm in the Vehicle to Everything (V2X) networks. Recently, more interest has focused on Non-Orthogonal Multiple Access (NOMA) in wireless-powered communication. In the conventional CR-enabled V2X-NOMA network, spectrum sensing and limited battery capacity at the Roadside Unit (RSU) may cause serious outage performance. In this study, RSU selection scheme is adopted. This paper presents an interesting model of a system with Simultaneous Wireless Information and Power Transfer (SWIPT) and a CR-enabled V2X-NOMA network. In the downlink, the RSU harvests wireless energy from Radio Frequency (RF) signals and senses the spectrum state at the same time. A CR-enabled V2X-NOMA system performance is presented by deriving exact expressions of outage probability of distant vehicles. In the overlay CR-enabled V2X-NOMA network, the constraints are transmit power and the number of designed RSU that make significant impacts on system performance. Simulation results show that the CR-enabled V2X-NOMA get benefits from energy harvesting and RSU selection scheme.

Overlay Cognitive Radio NOMA Networks with Selected Relay and Direct Link

Overlay Cognitive Radio NOMA Networks with Selected Relay and Direct Link

Performance Analysis of Hardware-Impaired Overlay Cognitive Satellite–Terrestrial Networks With Adaptive Relaying Protocol

In this article, we consider an overlay cognitive hybrid satellite-terrestrial network consisting of a primary satellite source-receiver pair and a secondary transmitter-receiver pair on the ground while taking into account the practical hardware impairments (HIs) at the user devices. Herein, a secondary terrestrial user acts as a cooperative relay to assist the transmission of primary satellite user. In return for this kind of favor, the secondary user gets access to the primary's spectrum for its own communication. Further, we consider the distortion noises induced by all the hardware-impaired terrestrial nodes and demonstrate their detrimental impact on the system performance. We manifest analytically that, for the higher data rates, the HIs invoke ceiling effects which reprehensibly cap the fundamental capacity of the system. To mitigate the effect of HIs, we propose an adaptive relaying (AR) protocol for both amplify-and-forward and decode-and-forward operations and compare its performance with the competitive fixed relaying schemes. The proposed AR protocol efficiently utilizes the available degrees-of-freedom to enhance the system performance. We comprehensively analyze the overall system performance by deriving closed-form expressions for the outage probability of the primary and secondary networks under heterogeneous fading environments. Our theoretical developments are corroborated through various numerical and simulation results.

Big data deployment in containerized infrastructures through the interconnection of network namespaces

SummaryBig Data applications tackle the challenge of fast handling of large streams of data. Their performance is not only dependent on the data frameworks implementation and the underlying hardware but also on the deployment scheme and its potential for fast scaling. Consequently, several efforts have focused on the ease of deployment of Big Data applications, notably through the use of containerization. This technology was indeed raised to bring multitenancy and multiprocessing out of clusters, providing high deployment flexibility through lightweight container images. Recent studies have focused mostly on Docker containers. Notwithstanding, this article is actually interested in recent Singularity containers as they provide more security and support high‐performance computing (HPC) environments and, in this way, they can make Big Data applications benefit from the specialized hardware of HPC. Singularity 2.x, however, does not isolate network resources as required by most Big Data components. Singularity 3.x allows allocating each container with isolated network resources, but their interconnection requires a nontrivial amount of configuration effort. In this context, this article makes a functional contribution in the form of a deployment scheme based on the interconnection of network namespaces, through underlay and overlay networking approaches, to make Big Data applications easily deployable inside Singularity containers. We provide detailed account of our deployment scheme when using both interconnection approaches in the form of a “how‐to‐do‐it” report, and we evaluate it by comparing three Big Data applications based on Hadoop when performing on a bare‐metal infrastructure and on scenarios involving Singularity and Docker instances.