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

Journal of the ACM

Cognitive radio (CR) is a promising technology that can alleviate the spectrum shortage problem by enabling unlicensed users equipped with CRs to coexist with incumbent users in licensed spectrum bands while causing no interference to incumbent communications. Spectrum sensing is one of the essential mechanisms of CRs and its operational aspects are being investigated actively. However, the security aspects of spectrum sensing have garnered little attention. In this paper, we identify a threat to spectrum sensing, which we call the primary user emulation (PUE) attack. In this attack, an adversary's CR transmits signals whose characteristics emulate those of incumbent signals. The highly flexible, software-based air interface of CRs makes such an attack possible. Our investigation shows that a PUE attack can severely interfere with the spectrum sensing process and significantly reduce the channel resources available to legitimate unlicensed users. To counter this threat, we propose a transmitter verification scheme, called LocDef (localization-based defense), which verifies whether a given signal is that of an incumbent transmitter by estimating its location and observing its signal characteristics. To estimate the location of the signal transmitter, LocDef employs a non-interactive localization scheme. Our security analysis and simulation results suggest that LocDef is effective in identifying PUE attacks under certain conditions.

Defense against Primary User Emulation Attacks in Cognitive Radio Networks

In this paper we investigate distributed computation in dynamic networks in which the network topology changes from round to round. We consider a worst-case model in which the communication links for each round are chosen by an adversary, and nodes do not know who their neighbors for the current round are before they broadcast their messages. The model captures mobile networks and wireless networks, in which mobility and interference render communication unpredictable. In contrast to much of the existing work on dynamic networks, we do not assume that the network eventually stops changing; we require correctness and termination even in networks that change continually. We introduce a stability property called T -interval connectivity (for T >= 1), which stipulates that for every T consecutive rounds there exists a stable connected spanning subgraph. For T = 1 this means that the graph is connected in every round, but changes arbitrarily between rounds.We show that in 1-interval connected graphs it is possible for nodes to determine the size of the network and compute any com- putable function of their initial inputs in O(n2) rounds using messages of size O(log n + d), where d is the size of the input to a single node. Further, if the graph is T-interval connected for T > 1, the computation can be sped up by a factor of T, and any function can be computed in O(n + n2/T) rounds using messages of size O(log n + d). We also give two lower bounds on the token dissemination problem, which requires the nodes to disseminate k pieces of information to all the nodes in the network.The T-interval connected dynamic graph model is a novel model, which we believe opens new avenues for research in the theory of distributed computing in wireless, mobile and dynamic networks.

/pdf/distributed-computation-in-dynamic-networks-r29sfya8wl.pdf

Distributed computation in dynamic networks

A transformation is underway in electric power and energy systems (EPESs) to provide clean distributed energy for sustainable global economic growth. Internet of Things (IoT) is at the forefront of this transformation imparting capabilities, such as real-time monitoring, situational awareness and intelligence, control, and cyber security to transform the existing EPES into intelligent cyber-enabled EPES, which is more efficient, secure, reliable, resilient, and sustainable. Additionally, digitizing the electric power ecosystem using IoT improves asset visibility, optimal management of distributed generation, eliminates energy wastage, and create savings. IoT has a significant impact on EPESs and offers several opportunities for growth and development. There are several challenges with the deployment of IoT for EPESs. Viable solutions need to be developed to overcome these challenges to ensure continued growth of IoT for EPESs. The advancements in computational intelligence capabilities can evolve an intelligent IoT system by emulating biological nervous systems with cognitive computation, streaming and distributed analytics including at the edge and device levels. This review paper provides an assessment of the role, impact and challenges of IoT in transforming EPESs.

Review of Internet of Things (IoT) in Electric Power and Energy Systems

While it is well-known that BitTorrent is vulnerable to selfish behavior, this paper demonstrates that even entire files can be downloaded without reciprocating at all in BitTorrent. To this end, we present BitThief, a free riding client that never contributes any real data. First, we show that simple tricks suffice in order to achieve high download rates, even in the absence of seeders. We also illustrate how peers in a swarm react to various sophisticated attacks. Moreover, our analysis reveals that sharing communities—communities originally intended to offer downloads of good quality and to promote cooperation among peers—provide many incentives to cheat.

/pdf/free-riding-in-bittorrent-is-cheap-33t2ktwxvj.pdf

Free Riding in BitTorrent is Cheap.

In contrast to peer-to-peer file sharing, live streaming based on peer-to-peer technology is still awaiting its breakthrough. This may be due to the additional challenges live streaming faces, e.g., the need to meet real-time playback deadlines, or the increased demands on robustness under churn. This paper presents and evaluates novel neighbor selection and data distribution schemes for peer-to-peer live streaming. Concretely, in order to distribute data efficiently and with minimal delay, our algorithms combine low-latency push operations along a structured overlay with the flexibility of pull operations. The protocols ensure that all peers are able to obtain the required data blocks of a live stream in time, and that due to the loop-free dissemination paths, the overhead is low.

http://www.net.t-labs.tu-berlin.de/~stefan/disc07.pdf

Push-to-pull peer-to-peer live streaming

Peer-to-peer systems (p2p) are highly dynamic in nature. They may consist of millions of peers joining only for a limited period of time, resulting in hundreds of join and leave events per second. In this paper we introduce eQuus, a novel distributed hash table (DHT) suitable for highly dynamic environments. eQuus guarantees that lookups are always fast-- in terms of both the delay and the total number of routing hops--, although peers may join and leave the network at any time and concurrently. 1 Introduction

/pdf/equus-a-provably-robust-and-locality-aware-peer-to-peer-uihgtukd1k.pdf

eQuus: A Provably Robust and Locality-Aware Peer-to-Peer System

We present a novel clock synchronization algorithm and prove tight upper and lower bounds on the worst-case clock skew that may occur between any two participants in any given distributed system. More importantly, the worst-case clock skew between neighboring nodes is (asymptotically) at most a factor of two larger than the best possible bound. While previous results solely focused on the dependency of the skew bounds on the network diameter, we prove that our techniques are optimal also with respect to the maximum clock drift, the uncertainty in message delays, and the imposed bounds on the clock rates. The presented results all hold in a general model where both the clock drifts and the message delays may vary arbitrarily within pre-specified bounds.Furthermore, our algorithm exhibits a number of other highly desirable properties. First, the algorithm ensures that the clock values remain in an affine linear envelope of real time. A better worst-case bound on the accuracy with respect to real time cannot be achieved in the absence of an external timer. Second, the algorithm minimizes the number and size of messages that need to be exchanged in a given time period. Moreover, only a small number of bits must be stored locally for each neighbor. Finally, our algorithm can easily be adapted for a variety of other prominent synchronization models.

https://dl.acm.org/doi/pdf/10.1145/1667053.1667057

Tight bounds for clock synchronization

There is a growing demand for live, on-the-fly processing of increasingly large amounts of data. In order to ensure the timely and reliable processing of streaming data, a variety of distributed stream processing architectures and platforms have been developed, which handle the fundamental tasks of (dynamically) assigning processing tasks to the currently available physical resources and routing streaming data between these resources. However, while there are plenty of platforms offering such functionality, the theory behind it is not well understood. In particular, it is unclear how to best allocate the processing tasks to the given resources. In this paper, we establish a theoretical foundation by formally defining a task allocation problem for distributed stream processing, which we prove to be NP-hard. Furthermore, we propose an approximation algorithm for the class of series-parallel decomposable graphs, which captures a broad range of common stream processing applications. The algorithm achieves a constant-factor approximation under the assumptions that the number of resources scales at least logarithmically with the number of computational tasks and the computational cost of the tasks dominates the cost of communication.

Thomas Locher

Papers

Free Riding in BitTorrent is Cheap.

Push-to-pull peer-to-peer live streaming

eQuus: A Provably Robust and Locality-Aware Peer-to-Peer System

Tight bounds for clock synchronization

Task allocation for distributed stream processing