Certain data-communication protocols hog the spotlight, but all of them have a lot in common. Computer Networking: A Top-Down Approach Featuring the Internet explains the engineering problems that are inherent in communicating digital information from point to point. The top-down approach mentioned in the subtitle means that the book starts at the top of the protocol stack--at the application layer--and works its way down through the other layers, until it reaches bare wire. The authors, for the most part, shun the well-known seven-layer Open Systems Interconnection (OSI) protocol stack in favor of their own five-layer (application, transport, network, link, and physical) model. It's an effective approach that helps clear away some of the hand waving traditionally associated with the more obtuse layers in the OSI model. The approach is definitely theoretical--don't look here for instructions on configuring Windows 2000 or a Cisco router--but it's relevant to reality, and should help anyone who needs to understand networking as a programmer, system architect, or even administration guru.The treatment of the network layer, at which routing takes place, is typical of the overall style. In discussing routing, authors James Kurose and Keith Ross explain (by way of lots of clear, definition-packed text) what routing protocols need to do: find the best route to a destination. Then they present the mathematics that determine the best path, show some code that implements those algorithms, and illustrate the logic by using excellent conceptual diagrams. Real-life implementations of the algorithms--including Internet Protocol (both IPv4 and IPv6) and several popular IP routing protocols--help you to make the transition from pure theory to networking technologies. --David WallTopics covered: The theory behind data networks, with thorough discussion of the problems that are posed at each level (the application layer gets plenty of attention). For each layer, there's academic coverage of networking problems and solutions, followed by discussion of real technologies. Special sections deal with network security and transmission of digital multimedia.

Computer Networking: A Top-Down Approach

Elements of Information Theory (2nd ed.). Thomas M. Cover and Joy A. Thomas

Network Simulator NS2

Today’s Internet has witnessed an increase in the popularity of mobile video streaming, which is expected to exceed 3/4 of the global mobile data traffic by 2019. To satisfy the considerable amount of mobile video requests, video service providers have been pushing their content delivery infrastructure to edge networks—from regional content delivery network (CDN) servers to peer CDN servers (e.g., smartrouters in users’ homes)—to cache content and serve users with storage and network resources nearby. Among the edge network content caching paradigms, Wi-Fi access point caching and cellular base station caching have become two mainstream solutions. Thus, understanding the effectiveness and performance of these solutions for large-scale mobile video delivery is important. However, the characteristics and request patterns of mobile video streaming are unclear in practical wireless network. In this paper, we use real-world data sets containing 50 million trace items of nearly 2 million users viewing more than 0.3 million unique videos using mobile devices in a metropolis in China over two weeks, not only to understand the request patterns and user behaviors in mobile video streaming, but also to evaluate the effectiveness of Wi-Fi and cellular-based edge content caching solutions. To understand the performance of edge content caching for mobile video streaming, we first present temporal and spatial video request patterns, and we analyze their impacts on caching performance using frequency-domain and entropy analysis approaches. We then study the behaviors of mobile video users, including their mobility and geographical migration behaviors, which determine the request patterns. Using trace-driven experiments, we compare strategies for edge content caching, including least recently used (LRU) and least frequently used (LFU), in terms of supporting mobile video requests. We reveal that content, location, and mobility factors all affect edge content caching performance. Moreover, we design an efficient caching strategy based on the measurement insights and experimentally evaluate its performance. The results show that our design significantly improves the cache hit rate by up to 30% compared with LRU/LFU.

Understanding Performance of Edge Content Caching for Mobile Video Streaming

Conventional Internet of Things (IoT) ecosystems involve data streaming from sensors, through Fog devices to a centralized Cloud server. Issues that arise include privacy concerns due to third party management of Cloud servers, single points of failure, a bottleneck in data flows and difficulties in regularly updating firmware for millions of smart devices from a point of security and maintenance perspective. Blockchain technologies avoid trusted third parties and safeguard against a single point of failure and other issues. This has inspired researchers to investigate blockchain’s adoption into IoT ecosystem. In this paper, recent state-of-the-arts advances in blockchain for IoT, blockchain for Cloud IoT and blockchain for Fog IoT in the context of eHealth, smart cities, intelligent transport and other applications are analyzed. Obstacles, research gaps and potential solutions are also presented.

A survey on the adoption of blockchain in IoT: challenges and solutions

The hybrid architecture of content distribution network (CDN) and peer to peer (P2P) is promising in providing online streaming media services. In this paper, we conducted a comprehensive measurement study on Kankan, one of the leading VoD streaming service providers in China that is based on a hybrid CDN-P2P architecture. Our measurements are multi-fold, as follows. 1) Kankan adopts a loosely-coupled hybrid architecture , in which the user requests are handled by its CDN and P2P network independently. 2) Kankan deploys a small-scale CDN densely in three geographic clusters in China. It adopts specific redirection servers to dispatch the nationwide requests. 3) Kankan adopts a dual-server mechanism to enhance start-up video streaming. It also provides the CDN acceleration in case of inefficient P2P streaming performance. 4) According to our studies on the peer cache lists, the video contents stored in Kankan peers update quite slowly. The average lifetime of cached videos is longer than one week. Our results show that, by utilizing the slow-varying contents cached in peers and deploying various CDN enhancement mechanisms , Kankan provides a large-scale VoD streaming service with a small-scale fixed infrastructure. Insights obtained in this study will be valuable for the development and deployment of future hybrid CDN-P2P VoD streaming systems.

Unreeling Xunlei Kankan: Understanding Hybrid CDN-P2P Video-on-Demand Streaming

Recently, researchers around the world in medical institutions and pharmaceutical companies are demanding a wider access to healthcare data for secondary use in order to provide enhanced and personalized medical services. For this purpose, healthcare information exchange between health authorities can be leveraged as a fundamental concept to meet these demands and enable the discovery of new insights and cures. However, health data are highly sensitive and private information that requires strong authentication and authorization procedures to manage the access to them. In this regard, the cloud paradigm has been used in these e-healthcare solutions, but they remain inefficient due to their inability to adapt to the expanding volume of data generated from body sensors and their vulnerability against cyberattacks. Hence, collaborative and distributed data governance supported by edge computing and blockchain promises enormous potentials in improving the performance and security of the whole system. In this paper, we present a secure and efficient data management framework, named ”EdgeMediChain”, for sharing health data. The proposed architecture leverages both edge computing and blockchain to facilitate and provide the necessary requirements for a healthcare ecosystem in terms of scalability, security, as well as privacy. The Ethereum-based testbed evaluations show the effectiveness of EdgeMediChain in terms of execution time with a reduction of nearly 84.75% for 2000 concurrent transactions, higher throughput compared to a traditional blockchain, and scalable ledger storage with a linear growth rate.

EdgeMediChain: A Hybrid Edge Blockchain-Based Framework for Health Data Exchange

High density Wi-Fi networks require load balancing in order to ensure quality of service (QoS) In the traditional Wi-Fi networks, the wireless stations learn the access points (APs) load and make the association decisions themselves leading to uneven load distribution among the APs The new paradigm, software defined networking (SDN), has a centralized architecture, which allows to manage, measure and control high density Wi-Fi networks easily In this paper we propose a QoS-aware load balancing strategy (QALB) for software defined Wi-Fi networks (SD-Wi-Fi), as a solution to address the problem of Wi-Fi congestion among the OpenFlow enabled APs (OAPs) The SDN controller selects a load level up to which the association decisions are made by the OAPs without consulting the controller The wireless stations from an overloaded OAP are handed to an underloaded OAP by considering multi-metrics such as the packet loss rate, received signal strength indicator (RSSI) and throughput An emulation platform and a large-scale-low-cost testbed with the same settings are constructed to evaluate the performance of our load balancing strategy The results show that in comparison to four non-static schemes such as, channel measurement based access selection scheme (CMAS), (DL-SINR) downlink-signal to interference plus noise ratio AP selection scheme (DASA), mean probe delay scheme (MPD) and RSSI scheme, the proposed QALB, optimizes the throughput up to 16%, reduces the average frame delay up to 19%, minimizes the number of re-transmissions by 49%, reduces the number of handoffs by 15%, improves the degree of load balancing by 22% and minimizes the re-association times by 38%, in high density SD-Wi-Fi

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Towards QoS-Aware Load Balancing for High Density Software Defined Wi-Fi Networks

WiFi has become one of the major network access networks due to its simple technical implementation and high-bandwidth provisioning. In this paper, we studied software defined WiFi networks (SDWN) against traditional WiFi networks to understand the potential benefits, such as the ability of SDWN to effectively hide the handover delay between access points (AP) of the adoption of the SDWN architecture on WiFi networks and identify representative application scenarios where such SDWN approach could bring additional benefits. This study delineated the performance bottlenecks such as the throughput degradation by around compared with the conventional WiFi networks. In addition, our study also shed some insights into performance optimization issues. All of the performance measurements were conducted on a network testbed consisting of a single basic service set (BSS) and an extended service set (ESS) managed by a single SDN controller deployed with various laboratory settings. Our evaluation included the throughput performance under different traffic loads with different number of nodes and packet sizes for both TCP and UDP traffic flows. Handover delays were measured during the roaming phase between different APs against the traditional WiFi networks. Our results have demonstrated the tradeoff between performance and programmability of software defined APs.

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On the Tradeoff between Performance and Programmability for Software Defined WiFi Networks

Falls commonly occur for elder citizens which may lead to severe injuries. In this paper, we propose a cloud-network-edge architecture to enhance fall detection, prevention and protection which consists of the medical cloud, edge networks and end-devices, such smart helmet. The smart helmet is integrated with wearable cameras, accelerometers, gyroscope sensors; hence, it is able to sense daily activities of the elderly based on data fusion from multi sensors collaboratively. The processing of the sensor data can be offloaded at the edge for reducing delay and preserving privacy. The medical data can be delivered over a secure medical network to the medical cloud for services, such as fall alarm. In particular, we evaluate the performance of multimode processing algorithms for video and accelerometer data to enhance fall detection. Our experimental results show that the proposed algorithms are able to increase the accuracy and reduce the false alarm effectively.

Wenqing Cheng

Papers

Unreeling Xunlei Kankan: Understanding Hybrid CDN-P2P Video-on-Demand Streaming

EdgeMediChain: A Hybrid Edge Blockchain-Based Framework for Health Data Exchange

Towards QoS-Aware Load Balancing for High Density Software Defined Wi-Fi Networks

On the Tradeoff between Performance and Programmability for Software Defined WiFi Networks

Enhancing Fall Detection for Elderly with Smart Helmet in a Cloud-Network-Edge Architecture