Computer communications

From the Publisher:
Real-Time Systems is both a valuable reference for professionals and an advanced text for Computer Science and Computer Engineering students. 

Real world real-time applications based on research and practice

State-of-the-art algorithms and methods for validation

Methods for end-to-end scheduling and resource management

More than 100 illustrations to enhance understanding

Comprehensive treatment of the technology known as RMA (rate-monotonic analysis) methods

A supplemental Companion Website www.prenhall.com/liu

http://user.it.uu.se/~yi/courses/rts/dvp-rts-08/notes/Course-INFO.pdf

Real-Time Systems

Distributed denial of service (DDoS) resilience in cloud

With companies such as Netflix and YouTube accounting for more than 50% of the peak download traffic on North American fixed networks in 2015, video streaming represents a significant source of Internet traffic. Multimedia delivery over the Internet has evolved rapidly over the past few years. The last decade has seen video streaming transitioning from User Datagram Protocol to Transmission Control Protocol-based technologies. Dynamic adaptive streaming over HTTP (DASH) has recently emerged as a standard for Internet video streaming. A range of rate adaptation mechanisms are proposed for DASH systems in order to deliver video quality that matches the throughput of dynamic network conditions for a richer user experience. This survey paper looks at emerging research into the application of client-side, server-side, and in-network rate adaptation techniques to support DASH-based content delivery. We provide context and motivation for the application of these techniques and review significant works in the literature from the past decade. These works are categorized according to the feedback signals used and the end-node that performs or assists with the adaptation. We also provide a review of several notable video traffic measurement and characterization studies and outline open research questions in the field.

A Survey of Rate Adaptation Techniques for Dynamic Adaptive Streaming Over HTTP

Call for papers for Special Issue of ACM Transactions on Multimedia Computing, Communications and Applications on Interactive Digital Television

ACM Transactions on Multimedia Computing, Communications and Applications (ACM TOMCCAP)

We introduce a cloud-enabled defense mechanism for Internet services against network and computational Distributed Denial-of-Service (DDoS) attacks. Our approach performs selective server replication and intelligent client re-assignment, turning victim servers into moving targets for attack isolation. We introduce a novel system architecture that leverages a "shuffling" mechanism to compute the optimal re-assignment strategy for clients on attacked servers, effectively separating benign clients from even sophisticated adversaries that persistently follow the moving targets. We introduce a family of algorithms to optimize the runtime client-to-server re-assignment plans and minimize the number of shuffles to achieve attack mitigation. The proposed shuffling-based moving target mechanism enables effective attack containment using fewer resources than attack dilution strategies using pure server expansion. Our simulations and proof-of-concept prototype using Amazon EC2 [1] demonstrate that we can successfully mitigate large-scale DDoS attacks in a small number of shuffles, each of which incurs a few seconds of user-perceived latency.

Catch Me If You Can: A Cloud-Enabled DDoS Defense

http://mason.gmu.edu/~hwang14/files/COMCOM14.pdf

A moving target DDoS defense mechanism

An important issue in IP-based QoS networks is the effective management of packets at the router level. Specifically, if the arriving packets cannot all be stored in a buffer, or if the packets have deadlines by which they must be delivered, the router needs to identify the packets that should be dropped. In recent work, Kesselman et al. [6] propose a model, called buffer management with bounded delay, which can be thought of as an online scheduling problem on a single machine: packets arrive at a network switch and are stored in a buffer of size B. Each packet has a positive weight and a deadline, with the weight representing the value of transmitting the packet by its deadline. At each integer time step, exactly one packet can be transmitted, and the objective is to maximize the total weight of the transmitted packets. If B = ∞, this is the online version of the scheduling problem 1| pj = 1, rj, dj |Σ wj Uj. (We assume that rj and dj are integers.)

/pdf/an-optimal-online-algorithm-for-packet-scheduling-with-14ih27h3oe.pdf

An optimal online algorithm for packet scheduling with agreeable deadlines

As the Internet becomes more mature, there is a realization that improving the performance of routers has the potential to substantially improve Internet performance in general. Currently, most routers forward packets in a First-In-First-Out (FIFO) order. However, the diversity of applications supported by modern IP-based networks has resulted in unpredictable packet flows, and heterogeneous network traffic. Thus, it is becoming more reasonable to consider differentiating between different types of packets, and perhaps to consider allowing packets to specify a deadline by which it must be processed. These issues have made buffer management at routers a critical issue in providing effective quality of service to the various applications that use the network.In this paper, we study an online problem in which each packet is described by its discrete arrival time, non-negative weight and discrete deadline; arriving packets are buffered for delivery and all packets have the same processing time. The packets arrive online, and our objective is to maximize the sum of weights of those packets that are sent by their deadlines. We describe an online deterministic algorithm with a competitive ratio of 1.854, improving the best previous known competitive ratio of 1.939 (Bartal et al. STACS 2004).The algorithmic framework we use has several interesting features. First, we do not use a potential function. Instead, after each step we modify the adversary's buffer. Second, we introduce "dummy packets" to facilitate the decision making.

/pdf/better-online-buffer-management-2x0eeinfq9.pdf

Better online buffer management

With the ever-increasing P2P Internet traffic, recently much attention has been paid to the topology mismatch between the P2P overlay and the underlying network due to the large amount of cross-ISP traffic.  Mainly focusing on BitTorrent-like file sharing systems, several recent studies have demonstrated how to efficiently bridge the overlay and the underlying network by leveraging the existing infrastructure, such as CDN services or developing new application-ISP interfaces, such as P4P. However, so far the traffic locality in existing P2P live streaming systems has not been well studied. In this work, taking PPLive as an example, we examine traffic locality in Internet P2P streaming systems. Our measurement results on both popular and unpopular channels from various locations show that current PPLive traffic is highly localized at the ISP level. In particular, we find: (1) a PPLive peer mainly obtains peer lists referred by its connected neighbors (rather than tracker servers) and up to 90\% of listed peers are from the same ISP as the requesting peer; (2) the major portion of the streaming traffic received by a requesting peer (up to 88\% in popular channels) is served by peers in the same ISP as the requestor; (3) the top 10\% of the connected peers provide most (about 70\%) of the requested streaming data and these top peers have smaller RTT to the requesting peer.  Our study reveals that without using any topology information or demanding any infrastructure support, PPLive achieves such high ISP level traffic locality spontaneously with its decentralized, latency based, neighbor referral peer selection strategy. These findings provide some new insights for better understanding and optimizing the network- and user-level performance in practical P2P live streaming systems.

/pdf/a-case-study-of-traffic-locality-in-internet-p2p-live-7ab6xn9197.pdf

Fei Li

Papers

Catch Me If You Can: A Cloud-Enabled DDoS Defense

A moving target DDoS defense mechanism

An optimal online algorithm for packet scheduling with agreeable deadlines

Better online buffer management

A Case Study of Traffic Locality in Internet P2P Live Streaming Systems