By George Kesidis, Jean Walrand
This publication matters peer-to-peer functions and mechanisms working on the web, fairly those who should not absolutely automatic and contain major human interplay. So, the area of curiosity is the intersection of disbursed structures and on-line social networking. often, easy versions are defined to explain the tips. starting with brief overviews of caching, graph conception and online game thought, we hide the elemental rules of dependent and unstructured seek. We then describe an easy framework for reputations and for iterated referrals and consensus. This framework is utilized to an issue of sybil identification administration. the basic outcome for iterated Byzantine consensus for a comparatively very important factor can also be given. eventually, a straight-forward epidemic version is used to explain the propagation of malware online and for BitTorrent-style file-sharing. This brief publication can be utilized as a initial orientation to this subject material. References are given for the scholar to papers with solid survey and instructional content material and to these with extra complex remedies of particular themes. For an teacher, this booklet is appropriate for a one-semester seminar direction. then again, it may be the framework for a semester's worthy of lectures the place the teacher may complement each one bankruptcy with extra lectures on comparable or extra complicated subject material. A uncomplicated historical past is needed within the components of computing device networking, chance concept, stochastic procedures, and queueing. desk of Contents: Networking review / Graphs / video games / seek in based networks / seek in unstructured networks / Transactions, reputations, and referrals / fake Referrals / Peer-to-peer dossier sharing / Consensus in dynamical trust platforms / Byzantine consensus / Epidemics
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Additional resources for An Introduction to Models of Online Peer-to-Peer Social Networking
Is locally convex at q ∗ . An equilibrium point q ∗ is Pareto dominant if each player’s net utility at q ∗ is not less than that at any other equilibrium. Nash equilibria are not necessarily Pareto. 2 SYMMETRIC ALTRUISM In this section, we assume players are aware of one another’s net utilities and are partially inclined to cooperate . , tactical mobile ad hoc networks 3 An open ball in [0, q max ]n of positive radius. 30 3. GAMES (MANETs), network nodes may engage in fully or partially cooperative behavior with respect to some of their peers.
Note that bidirectional links are not considered above due to self-interference at the transmitters/receivers. Typically, each-way communication of a bidirectional link will be separated by TDMA, FDMA, or CDMA/spread-spectrum means. , [114, 132]. 2) holds. 2. SYMMETRIC ALTRUISM 33 where pe is bit error probability. , when using DBPSK or GFSK modulation ), then we can approximate (SINR) ≈ exp(−n exp(−SINR)). Alternatively, Shannon’s expression for capacity log(1 + SINR) is often used to map SINR to service quality.
Ch. 11. 27 CHAPTER 3 Games In games, individual player’s (user’s) behavior will be modeled by a payoff (utility) function. Utility minus the cost of playing the game will be called net utility. Each player is assumed to have an action/play space of decisions. These actions are coupled through network dynamics. The utility of a given user will depend, at least in part, on all other user actions. Our games will involve iterative plays. A player’s objective will be to maximize their net utility. Game-theoretic models for telecommunication systems have recently been surveyed in .
An Introduction to Models of Online Peer-to-Peer Social Networking by George Kesidis, Jean Walrand