Conference Paper

Self-optimizing Peer-to-Peer Networks with Selfish Processes

Univ. of Iowa, Iowa City
DOI: 10.1109/SASO.2007.51 Conference: Self-Adaptive and Self-Organizing Systems, 2007. SASO '07. First International Conference on
Source: DBLP

ABSTRACT

Request patterns in peer-to-peer networks are not uniform, and the cost of communication depends on the traffic flows among peers. This paper illustrates how processes in an overlay network can use the information about traffic flow pattern and spontaneously adjust the topology to minimize their communication costs. Four different self-optimization protocols are presented. The selfish protocols allow peers to modify their routing tables to suit their individual needs, and are easy to implement, but the improvements are limited. Compared to this, the altruistic protocols that allow peers to adjust the routing tables based on the needs of other processes, promise a better performance. Since selfish peers may not comply, a penalty mechanism is proposed to discourage selfishness.

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Available from: Sukumar Ghosh, Apr 09, 2014
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    • "We define such a state as a Nash equilibrium for the system. For convenience, we enumerate the differences between the problems addressed in the current paper and those addressed in [3] and [4] "
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    ABSTRACT: The objective of this paper is three-fold. First, we specify what it means for a fixed point of a stabilizing distributed system to be a Nash equilibrium. Second, we present methods that can be used to verify whether or not a given fixed point of a given stabilizing distributed system is a Nash equilibrium. Third, we argue that in a stabilizing distributed system, whose fixed points are all Nash equilibria, no process has an incentive to perturb its local state, after the system reaches one fixed point, in order to force the system to reach another fixed point where the perturbing process achieves a better gain. If the fixed points of a stabilizing distributed system are all Nash equilibria, then we refer to the system as perturbation-proof. Otherwise, we refer to the system as perturbation-prone. We identify four natural classes of perturbation-(proof/prone) systems. We present system examples for three of these classes of systems, and show that the fourth class is empty.
    Full-text · Article · Jul 2011 · Theoretical Computer Science
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    • "We define such a state as a Nash equilibrium for the system. For convenience, we enumerate the differences between the problems addressed in the current paper and those addressed in [3] and [4] "
    [Show abstract] [Hide abstract]
    ABSTRACT: The objective of this paper is three-fold. First, we specify what it means for a fixed point of a stabilizing distributed system to be a Nash equilibrium. Second, we present methods that can be used to verify whether or not a given fixed point of a given stabilizing distributed system is a Nash equilibrium. Third, we argue that in a stabilizing distributed system, whose fixed points are all Nash equilibria, no process has an incentive to perturb its local state, after the system reaches one fixed point, in order to force the system to reach another fixed point where the perturbing process achieves a better gain. If the fixed points of a stabilizing distributed system are all Nash equilibria, then we refer to the system as perturbation-proof. Otherwise, we refer to the system as perturbation-prone. We identify four natural classes of perturbation-(proof/prone) systems. We present system examples for three of these classes of systems, and show that the fourth class is empty.
    Full-text · Chapter · Nov 2009
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    • "One of them is approached from the user's point of view. Each individual user wants all the data needed within the shortest possible time (Bhattacharya and Ghosh 2007). The other type is approached from the point of view of a network service provider (such as an internet service provider (ISP)), who owns the network but does not control individual peers. "
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    ABSTRACT: Temporally expressive planning, an important class of temporal planning, has attracted much attention lately. Temporally expressive planning is dicult; few exist- ing planners can solve them, as they have highly con- current actions. We propose an optimal approach to temporally expressive planning based on a SAT formu- lation of the problem, finding solutions with the short- est time spans. Our experiments on several temporally expressive domains showed that our planner is able to optimally solve many instances in a reasonable amount of time, comparing favorably to existing temporally ex- pressive planners. Our second result is a temporally expressive planning problem formulation of the Peer-to-Peer (P2P) network communications. In addition to demonstrating a bet- ter performance of our new method than the only ex- isting temporally expressive planners on several tem- porally expressive problem domains, we apply our new planner to find optimal communication schedules for P2P networks. Our results will be potentially useful for designing ecient communication protocols in P2P networks.
    Preview · Conference Paper · Jan 2009
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