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Abstract Analysis of pipe networks involves computing flow rates and pressure differences on pipe segments in the network, given the external inflow/outflow values. This analysis can be conducted using iterative methods, among which the algorithms of Hardy Cross and Newton-Raphson have historically been applied in practice. In this note, we address the mathematical analysis of the local convergence of these algorithms. The loop-based Newton–Raphson algorithm converges quadratically fast, and we provide estimates for its convergence radius to correct some estimates in the previous literature. In contrast, we show that the convergence of the Hardy Cross algorithm is only linear. This provides theoretical confirmation of experimental observations reported earlier in the literature. 

Abstract In the spanning tree congestion problem, given a connected graphG, the objective is to compute a spanning treeTinGthat minimizes its maximum edge congestion, where the congestion of an edgeeofTis the number of edges inGfor which the unique path inTbetween their endpoints traversese. The problem is known to be$$\mathbb{N}\mathbb{P}$$ $NP$-hard, but its approximability is still poorly understood, and it is not even known whether the optimum solution can be efficiently approximated with ratioo(n). In the decision version of this problem, denoted$${\varvec{K}-\textsf {STC}}$$ $K-\mathrm{STC}$, we need to determine ifGhas a spanning tree with congestion at mostK. It is known that$${\varvec{K}-\textsf {STC}}$$ $K-\mathrm{STC}$is$$\mathbb{N}\mathbb{P}$$ $NP$-complete for$$K\ge 8$$ $K\ge 8$, and this implies a lower bound of 1.125 on the approximation ratio of minimizing congestion. On the other hand,$${\varvec{3}-\textsf {STC}}$$ $3-\mathrm{STC}$can be solved in polynomial time, with the complexity status of this problem for$$K\in { \left\{ 4,5,6,7 \right\} }$$ $K\in \left(4,,,5,,,6,,,7\right)$remaining an open problem. We substantially improve the earlier hardness results by proving that$${\varvec{K}-\textsf {STC}}$$ $K-\mathrm{STC}$is$$\mathbb{N}\mathbb{P}$$ $NP$-complete for$$K\ge 5$$ $K\ge 5$. This leaves only the case$$K=4$$ $K=4$open, and improves the lower bound on the approximation ratio to 1.2. Motivated by evidence that minimizing congestion is hard even for graphs of small constant radius, we also consider$${\varvec{K}-\textsf {STC}}$$ $K-\mathrm{STC}$restricted to graphs of radius 2, and we prove that this variant is$$\mathbb{N}\mathbb{P}$$ $NP$-complete for all$$K\ge 6$$ $K\ge 6$. 

Abstract It is natural to generalize the online$$k$$ $k$-Server problem by allowing each request to specify not only a pointp, but also a subsetSof servers that may serve it. To date, only a few special cases of this problem have been studied. The objective of the work presented in this paper has been to more systematically explore this generalization in the case of uniform and star metrics. For uniform metrics, the problem is equivalent to a generalization of Paging in which each request specifies not only a pagep, but also a subsetSof cache slots, and is satisfied by having a copy ofpin some slot inS. We call this problemSlot-Heterogenous Paging. In realistic settings only certain subsets of cache slots or servers would appear in requests. Therefore we parameterize the problem by specifying a family$${\mathcal {S}}\subseteq 2^{[k]}$$ $S\subseteq 2^{\left[k\right]}$of requestable slot sets, and we establish bounds on the competitive ratio as a function of the cache sizekand family$${\mathcal {S}}$$ $S$:If all request sets are allowed ($${\mathcal {S}}=2^{[k]}\setminus \{\emptyset \}$$ $S=2^{\left[k\right]}\backslash \left\{\varnothing \right\}$), the optimal deterministic and randomized competitive ratios are exponentially worse than for standard Paging ($${\mathcal {S}}=\{[k]\}$$ $S=\left\{\right[k\left]\right\}$).As a function of$$|{\mathcal {S}}|$$ $\left|S\right|$andk, the optimal deterministic ratio is polynomial: at most$$O(k^2|{\mathcal {S}}|)$$ $O\left(k^2\right|S\left|\right)$and at least$$\Omega (\sqrt{|{\mathcal {S}}|})$$ $\Omega \left(\sqrt{\left|S\right|}\right)$.For any laminar family$${\mathcal {S}}$$ $S$of heighth, the optimal ratios areO(hk) (deterministic) and$$O(h^2\log k)$$ $O(h^{2}logk)$(randomized).The special case of laminar$${\mathcal {S}}$$ $S$that we callAll-or-One Pagingextends standard Paging by allowing each request to specify a specific slot to put the requested page in. The optimal deterministic ratio forweightedAll-or-One Paging is$$\Theta (k)$$ $\Theta \left(k\right)$. Offline All-or-One Paging is$$\mathbb{N}\mathbb{P}$$ $NP$-hard.Some results for the laminar case are shown via a reduction to the generalization of Paging in which each request specifies a set$$P$$ $P$ofpages, and is satisfied by fetching any page from$$P$$ $P$into the cache. The optimal ratios for the latter problem (with laminar family of heighth) are at mosthk(deterministic) and$$hH_k$$ $h{H}_k$(randomized). 

We consider the List Update problem where the cost of each swap is assumed to be 1. This is in contrast to the “standard” model, in which an algorithm is allowed to swap the requested item with previous items for free. We construct an online algorithm Full-Or-Partial-Move (Fpm), whose competitive ratio is at most 3.3904, improving over the previous best known bound of 4. 

Given a weighted, ordered query set\(Q\)and a partition of\(Q\)into classes, we study the problem of computing a minimum-cost decision tree that, given any query\(q\in Q\), uses equality tests and less-than tests to determine\(q\)'s class. Such a tree can be faster and smaller than a conventional search tree and smaller than a lookup table (both of which must identify\(q\), not just its class). We give the first polynomial-time algorithm for the problem. The algorithm extends naturally to the setting where each query has multiple allowed classes. 

Selective families of sets, or selectors, are combinatorial tools used to “isolate” individual members of sets from some set family. Given a set X and an element x ∈ X, to isolate x from X, at least one of the sets in the selector must intersect X on exactly x. We study (k,N)-permutation selectors which have the property that they can isolate each element of each k-element subset of {0, 1, ..., N − 1} in each possible order. These selectors can be used in protocols for ad-hoc radio networks to more efficiently disseminate informa- tion along multiple hops. In 2004, Gasieniec, Radzik and Xin gave a construc- tion of a (k, N )-permutation selector of size O(k2 log3 N ). This paper improves this by providing a probabilistic construction of a (k, N )-permutation selector of size O(k2 log N ). Remarkably, this matches the asymptotic bound for standard strong (k,N)-selectors, that isolate each element of each set of size k, but with no restriction on the order. We then show that the use of our (k, N )-permutation selector improves the best running time for gossiping in ad-hoc radio networks by a poly-logarithmic factor. 

We study search trees with 2-way comparisons (2WCST’s), which involve separate less-than and equal-to tests in their nodes, each test having two possible outcomes, yes and no. These trees have a much subtler structure than standard search trees with 3-way comparisons (3WCST’s) and are still not well understood, hampering progress towards designing an efficient algorithm for computing minimum-cost trees. One question that attracted attention in the past is whether there is an easy way to determine which type of comparison should be applied at any step of the search. Anderson, Kannan, Karloff and Ladner studied this in terms of the ratio between the maximum and total key weight, and defined two threshold values: λ− is the largest ratio that forces the less-than test, and λ+ is the smallest ratio that forces the equal-to test. They determined that λ− = 41 , but for the higher threshold they only showed that λ+ ∈ [ 3/7 , 4/9 ]. We give the tight bound for the higher threshold, by proving that in fact λ+ = 3/7 . 

In his 2018 paper, Herlihy introduced an atomic protocol for multi-party asset swaps across different blockchains. Practical implementation of this protocol is hampered by its intricacy and computational complexity, as it relies on elaborate smart contracts for asset transfers, and specifying the protocol’s steps on a given digraph requires solving an NP-hard problem of computing longest paths. Herlihy left open the question whether there is a simple and efficient protocol for cross-chain asset swaps in arbitrary digraphs. Addressing this, we study HTLC-based protocols, in which all asset transfers are implemented with standard hashed time-lock smart contracts (HTLCs). Our main contribution is a full characterization of swap digraphs that have such protocols, in terms of so-called reuniclus graphs. We give an atomic HTLC-based protocol for reuniclus graphs. Our protocol is simple and efficient. We then prove that non-reuniclus graphs do not have atomic HTLC-based swap protocols. 

We consider the classical single-source shortest path problem in directed weighted graphs. D. Eppstein proved recently an Ω(n³) lower bound for oblivious algorithms that use relaxation operations to update the tentative distances from the source vertex. We generalize this result by extending this Ω(n³) lower bound to adaptive algorithms that, in addition to relaxations, can perform queries involving some simple types of linear inequalities between edge weights and tentative distances. Our model captures as a special case the operations on tentative distances used by Dijkstra’s algorithm. 

We study search trees with 2-way comparisons (2WCST’s), which involve separate less-than and equal-to tests in their nodes, each test having two possible outcomes, yes and no. These trees have a much subtler structure than standard search trees with 3-way comparisons (3WCST’s) and are still not well understood, hampering progress towards designing an efficient algorithm for computing minimum-cost trees. One question that attracted attention in the past is whether there is an easy way to determine which type of comparison should be applied at any step of the search. Anderson, Kannan, Karloff and Ladner studied this in terms of the ratio between the maximum and total key weight, and defined two threshold values: λ− is the largest ratio that forces the less-than test, and λ+ −1 is the smallest ratio that forces the equal-to test. They determined that λ = 4 , but for the higher threshold they only showed that λ+ ∈ [ 37 , 49 ]. We give the tight +3 bound for the higher threshold, by proving that in fact λ = 7 .