Sequential Sharing Rules for River Sharing Problems

We analyse the redistribution of a resource among agents who have claims to the resource and who are ordered linearly. A well known example of this particular situation is the river sharing problem. We exploit the linear order of agents to transform the river sharing problem to a sequence of two-agent river sharing problems. These reduced problems are mathematically equivalent to bankruptcy problems and can therefore be solved using any bankruptcy rule. Our proposed class of solutions, that we call sequential sharing rules, solves the river sharing problem. Our approach extends the bankruptcy literature to settings with a sequential structure of both the agents and the resource to be shared. In the paper, we first characterise a class of sequential sharing rules. Subsequently, we apply sequential sharing rules based on four classical bankruptcy rules, assess their properties, and compare them to four alternative solutions to the river sharing problem.River Sharing Problem, Sequential Sharing Rule, Bankruptcy Problem, Water Allocation

Strategy-proof Sharing

We consider the problem of sharing a divisible good, where agents prefer more to less. First, we prove that a sharing rule satisfies strategy proofness if and only if it has the quasi-constancy property: no one changes her own share by changing her announcements. Next, by constructing a system of linear equations in a manner that is consistent with quasi-constancy, we provide a way to find every strategy-proof sharing rule. Finally, we identify a necessary and sufficient condition for the existence of non-constant, strategy-proof sharing rules, by examining the relationship between the constancy of strategy-proof sharing rules and the dimension of the solution space of the linear system.Strategy-proofness, Bossiness, Non-constancy, Quasi-constancy.

Spare capacity allocation using shared backup path protection for dual link failures

This paper extends the spare capacity allocation (SCA) problem from single link failure [1] to dual link failures on mesh-like IP or WDM networks. The SCA problem pre-plans traffic flows with mutually disjoint one working and two backup paths using the shared backup path protection (SBPP) scheme. The aggregated spare provision matrix (SPM) is used to capture the spare capacity sharing for dual link failures. Comparing to a previous work by He and Somani [2], this method has better scalability and flexibility. The SCA problem is formulated in a non-linear integer programming model and partitioned into two sequential linear sub-models: one finds all primary backup paths first, and the other finds all secondary backup paths next. The results on five networks show that the network redundancy using dedicated 1+1+1 is in the range of 313-400%. It drops to 96-181% in 1:1:1 without loss of dual-link resiliency, but with the trade-off of using the complicated share capacity sharing among backup paths. The hybrid 1+1:1 provides intermediate redundancy ratio at 187-310% with a moderate complexity. We also compare the passive/active approaches which consider spare capacity sharing after/during the backup path routing process. The active sharing approaches always achieve lower redundancy values than the passive ones. These reduction percentages are about 12% for 1+1:1 and 25% for 1:1:1 respectively

Log-Concave Duality in Estimation and Control

In this paper we generalize the estimation-control duality that exists in the linear-quadratic-Gaussian setting. We extend this duality to maximum a posteriori estimation of the system's state, where the measurement and dynamical system noise are independent log-concave random variables. More generally, we show that a problem which induces a convex penalty on noise terms will have a dual control problem. We provide conditions for strong duality to hold, and then prove relaxed conditions for the piecewise linear-quadratic case. The results have applications in estimation problems with nonsmooth densities, such as log-concave maximum likelihood densities. We conclude with an example reconstructing optimal estimates from solutions to the dual control problem, which has implications for sharing solution methods between the two types of problems