Social optimum in Social Groups with Give-and-Take criterion

TL;DR

This paper studies how to maximize data sharing in networked groups using a Give-and-Take rule to prevent free riding, proposing algorithms with provable performance bounds.

Contribution

It introduces a Give-and-Take exchange criterion for social groups and analyzes multiple algorithms for maximizing shared data under this rule.

Findings

A randomized algorithm achieves a 1/4 approximation ratio.

Four additional algorithms are proposed and analyzed.

Conditions for optimality of some algorithms are identified.

Abstract

We consider a "Social Group" of networked nodes, seeking a "universe" of segments. Each node has subset of the universe, and access to an expensive resource for downloading data. Alternatively, nodes can also acquire the universe by exchanging segments among themselves, at low cost, using a local network interface. While local exchanges ensure minimum cost, "free riders" in the group can exploit the system. To prohibit free riding, we propose the "Give-and-Take" criterion, where exchange is allowed if each node has segments unavailable with the other. Under this criterion, we consider the problem of maximizing the aggregate cardinality of the nodes' segment sets. First, we present a randomized algorithm, whose analysis yields a lower bound on the expected aggregate cardinality, as well as an approximation ratio of 1/4 under some conditions. Four other algorithms are presented and analyzed. We identify conditions under which some of these algorithms are optimal