skip to main content
US FlagAn official website of the United States government
dot gov icon
Official websites use .gov
A .gov website belongs to an official government organization in the United States.
https lock icon
Secure .gov websites use HTTPS
A lock ( lock ) or https:// means you've safely connected to the .gov website. Share sensitive information only on official, secure websites.


Title: Stable and Efficient Piece-Selection in Multiple Swarm BitTorrent-like Peer-to-Peer Networks
Recent studies have suggested that the BitTorrent's rarest-first protocol, owing to its work-conserving nature, can become unstable in the presence of non-persistent users. Consequently, in any stable protocol, many peers are at some point endogenously forced to hold off their file-download activity. In this work, we propose a tunable piece-selection policy that minimizes this (undesirable) requisite by combining the (work-conserving) rarest-first protocol with only an appropriate share of the (non-work conserving) mode-suppression protocol. We refer to this policy as "Rarest-First with Probabilistic Mode-Suppression" or simply RFwPMS. We study RFwPMS under a stochastic model of the BitTorrent network that is general enough to capture multiple swarms of non-persistent users - each swarm having its own altruistic preferences that may or may not overlap with those of other swarms. Using a Lyapunov drift analysis, we show that RFwPMS is provably stable for all kinds of inter-swarm behaviors, and that the use of rarest-first instead of random-selection is indeed more justified. Our numerical results suggest that RFwPMS is scalable in the general multi-swarm setting and offers better performance than the existing stabilizing schemes like mode-suppression.  more » « less
Award ID(s):
2008130
PAR ID:
10253388
Author(s) / Creator(s):
; ;
Date Published:
Journal Name:
IEEE INFOCOM 2020 - IEEE Conference on Computer Communications
Page Range / eLocation ID:
1153 to 1162
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
More Like this
  1. null (Ed.)
    The ability of a P2P network to scale its throughput up in proportion to the arrival rate of peers has recently been shown to be crucially dependent on the chunk sharing policy employed. Some policies can result in low frequencies of a particular chunk, known as the missing chunk syndrome, which can dramatically reduce throughput and lead to instability of the system. For instance, commonly used policies that nominally ``boost'' the sharing of infrequent chunks such as the well-known rarest-first algorithm have been shown to be unstable. We take a complementary viewpoint, and instead consider a policy that simply prevents the sharing of the most frequent chunk(s), that we call mode-suppression. We also consider a more general version that suppresses the mode only if the mode frequency is larger than the lowest frequency by a fixed threshold. We prove the stability of mode-suppression using Lyapunov techniques, and use a Kingman bound argument to show that the total download time does not increase with peer arrival rate. We then design versions of mode-suppression that sample a small number of peers at each time, and construct noisy mode estimates by aggregating these samples over time. We show numerically that mode suppression stabilizes and outperforms all other recently proposed chunk sharing algorithms, and via integration into BitTorrent implementation operating over the ns-3 that it ensures stable, low sojourn time operation in a real-world setting. 
    more » « less
  2. null (Ed.)
    Decentralized computational swarms have been used to simulate the workings of insect colonies or hives, often utilizing a response threshold model which underlies agent interaction with dynamic environmental stimuli. Here, we propose a logistics resupply problem in which agents must select from multiple incoming scheduled tasks that generate competing resource demands for workers. This work diverges from previous attempts toward analyzing swarm behaviors by examining relative amounts of stress placed on a multi-agent system in conjunction with two mechanisms of response: variable threshold distribution, or duration level. Further, we demonstrate changes to the general swarm performance’s dependence on paired desynchronization type and schedule design, as the result of varied swarm conditions. 
    more » « less
  3. null (Ed.)
    In self-organizing multi-agent systems, inter-agent variation is known to improve swarm performance significantly. Response duration, the amount of time that an agent spends on a task, has been proposed as a form of inter-agent variation that may be beneficial. In the biological literature, variability in agent response duration in natural swarms for desynchronizing agent actions has been discussed for some time. This form of variation, however, is not well understood in artificial swarms. In this work, we explore inter-agent variation in response duration as a desynchronization technique. We find that variation in response duration does desynchronize agent behaviors and does improve swarm performance on a two-dimensional tracking problem in which the swarm must push a tracker, staying as close as possible to a moving target. By preventing agents from reacting identically to task stimuli and keeping some agents on task longer, response duration helps smooth the swarm’s path and allows it to better track the target into path features such as corners. 
    more » « less
  4. Due to the increasing complexity of robot swarm algorithms, ana- lyzing their performance theoretically is often very difficult. Instead, simulators are often used to benchmark the performance of robot swarm algorithms. However, we are not aware of simulators that take advantage of the naturally highly parallel nature of distributed robot swarms. This paper presents ParSwarm, a parallel C++ frame- work for simulating robot swarms at scale on multicore machines. We demonstrate the power of ParSwarm by implementing two applications, task allocation and density estimation, and running simulations on large numbers of agents. 
    more » « less
  5. In this paper we propose a landmark-based map localization system for robotic swarms. The proposed system leverages the capabilities of a distributed landmark identification algorithm developed for robotic swarms presented in [1]. The output of the landmark identification consists of a vector of probabilities that each individual robot is looking at a particular landmark in the environment. In this work, this vector is used individually by each component of the swarm to feed the measurement update of a particle filter to estimate the robot location. The system was tested in simulation to validate its performance. 
    more » « less