Pinwheel Scheduling is a fundamental scheduling problem, in which each task \(i\) is associated with a positive integer deadline \(d_i\), and the objective is to schedule one task per time slot, ensuring each task perpetually appears at least once in every \(d_i\) time slots. Although conjectured to be PSPACE-complete, it remains open whether Pinwheel Scheduling is NP-hard (unless a compact input encoding is used) or even contained in NP.

The Subset Sum Ratio problem (SSR) asks, given a multiset $A$ of positive integers, to find two disjoint subsets of $A$ such that the largest-to-smallest ratio of their sums is minimized. In this paper we study the $k$-version of SSR, namely $k$-Subset Sum Ratio ($k$-SSR), which asks to minimize the largest-to-smallest ratio of sums of $k$ disjoint subsets of $A$. We develop an approximation scheme for $k$-SSR running in $O({n^{2k}}/{\varepsilon^{k-1}})$ time, where $n=|A|$ and $\varepsilon$ is the error parameter. To the best of our knowledge, this is the first FPTAS for $k$-SSR for fixed $k>2$. We also study the $k$-way Number Partitioning Ratio ($k$-PART) problem, which differs from $k$-SSR in that the $k$ subsets must constitute a partition of $A$; this problem in fact corresponds to the objective of minimizing the largest-to-smallest sum ratio in the family of Multiway Number Partitioning problems. We present a more involved FPTAS for $k$-PART, also achieving $O({n^{2k}}/{\varepsilon^{k-1}})$ time complexity. Notably, $k$-PART is also equivalent to the Minimum Envy-Ratio problem with identical valuation functions, which has been studied in the context of fair division of indivisible goods. Thus, for the case of identical valuations, our FPTAS represents a significant improvement over the $O(n^{4k^2+1}/\varepsilon^{2k^2})$ bound obtained by Nguyen and Rothe's FPTAS for Minimum Envy-Ratio with general additive valuations. Lastly, we propose a second FPTAS for $k$-SSR, which employs carefully designed calls to the first one; the new scheme has a time complexity of $\widetilde{O}(n/{\varepsilon^{3k-1}})$, thus being much faster when $n\gg 1/ \varepsilon$.

Non-convex minimization problems are universally considered hard, and even guaranteeing that a computed solution is locally minimizing is known to be NP-hard. In this general context, our paper focuses on the problem of finding stationary points that satisfy an approximate second-order optimality condition, which serves to exclude strict saddles and other non-minimizing stationary points. Our main result is that the problem of finding approximate second-order stationary points (SOSPs) is PLS-complete, i.e., of the same complexity as the problem of finding first-order stationary points (FOSPs), thus resolving an open question in the field. In particular, our results imply that, under the widely believed complexity conjecture that PLS $\neq$ FNP, finding approximate SOSPs in unconstrained domains is *easier* than in constrained domains, which is known to be NP-hard. This comes in stark contrast with earlier results which implied that, unless PLS = CLS, finding approximate FOSPs in unconstrained domains is *harder* than in constrained domains.

Abstract We present a new FPTAS for the Subset Sum Ratio problem, which, given a set of integers, asks for two disjoint subsets such that the ratio of their sums is as close to 1 as possible. Our scheme makes use of exact and approximate algorithms for Partition, and clearly showcases the close relationship between the two algorithmic problems. Depending on the relationship between the size of the input set n and the error margin $$\varepsilon $$ ε , we improve upon the best currently known algorithm of Melissinos and Pagourtzis [COCOON 2018] of complexity $$\mathcal {O} (n^4 / \varepsilon )$$ O ( n 4 / ε ) . In particular, the exponent of n in our proposed scheme may decrease down to 2, depending on the Partition algorithm used.

This work formalizes Publicly Auditable Conditional Blind Signatures (PACBS), a new cryptographic primitive that allows the verifiable issuance of blind signatures, the validity of which is contingent upon a predicate and decided by a designated verifier. In particular, when a user requests the signing of a message, blinded to protect her privacy, the signer embeds data in the signature that makes it valid if and only if a condition holds. A verifier, identified by a private key, can check the signature and learn the value of the predicate. Auditability mechanisms in the form of non-interactive zero-knowledge proofs are provided, so that a cheating signer cannot issue arbitrary signatures and a cheating verifier cannot ignore the embedded condition. The security properties of this new primitive are defined using cryptographic games. A proof-of-concept construction, based on the Okamoto–Schnorr blind signatures infused with a plaintext equivalence test is presented and its security is analyzed.

International audience

During the last few decades the problem of community detection in social networks has become an important and challenging computational task. Consequently, a number of algorithms have been proposed in the relevant literature, some of which seem to solve the problem quite efficiently. The huge amount of data, however, forces for further improved techniques that can handle large and complicated networks. In this paper, we consider the effect of assigning weights on edges of unweighted network graphs and estimate their importance in community detection. In particular, we propose a new edge weight function and study its effect when used as a preprocessing step for community detection algorithms. Experimental results on a benchmark of random networks confirm our intuition that assigning weights on edges can play an important role in improving the performance of such algorithms.

We consider the classical broadcast problem in ad-hoc (that is, unknown topology) directed radio networks with no collision detection, under the additional assumption that at most h transmissions (shots) are available per node. We focus on adaptive deterministic protocols for small values of h. We provide asymptotically matching lower and upper bounds for the cases h=2 and h=3. While for h=2 our bound is quadratic, similar to the bound obtained for oblivious protocols, for h=3 we prove a sub-quadratic bound of Theta(n^2 log log n / log n), where n is the number of nodes in the network. The latter is the first result showing an adaptive algorithm which is asymptotically faster than oblivious h-shot broadcast protocols, for which a tight quadratic bound is known for every constant h. Our upper bound for h=3 is constructive, making use of constructions of graphs with large girth. We also show an improved upper bound of O(n^(1+alpha/sqrt{h})) for h >= 4, where alpha is an absolute constant independent of h. Our upper bound for h >= 4 is non-constructive.

We address the problem of Reliable Message Transmission (RMT), in the general adversary model of Hirt and Maurer[2], which subsumes earlier models such as the global or local threshold adversaries. We employ the recently introduced Partial Knowledge Model[8], which captures any case of initial players' topology knowledge. Our main contribution is the determination of a necessary and sufficient condition for achieving RMT in the partial knowledge model with a general adversary. We propose the RMT-Partial Knowledge Algorithm (RMT-PKA), which solves RMT whenever this is possible, therefore it is a unique algorithm, as defined in[10]. To the best of our knowledge, this is the first unique protocol for RMT against general adversaries in the partial knowledge model.

We propose and investigate Selfish Path MultiColoring games as a natural model for noncooperative wavelength assignment in multifiber optical networks. In this setting, we view the wavelength assignment process as a strategic game in which each communication request selfishly chooses a wavelength in an effort to minimize the maximum congestion that it encounters on the chosen wavelength. We measure the cost of a certain wavelength assignment as the maximum, among all physical links, number of parallel fibers employed by this assignment. We start by settling questions related to the existence and computation of and convergence to pure Nash equilibria in these games. Our main contribution is a thorough analysis of the price of anarchy of such games, that is, the worst-case ratio between the cost of a Nash equilibrium and the optimal cost. We first provide upper bounds on the price of anarchy for games defined on general network topologies. Along the way, we obtain an upper bound of 2 for games defined on star networks. We next show that our bounds are tight even in the case of tree networks of maximum degree 3, leading to nonconstant price of anarchy for such topologies. In contrast, for network topologies of maximum degree 2, the quality of the solutions obtained by selfish wavelength assignment is much more satisfactory: We prove that the price of anarchy is bounded by 4 for a large class of practically interesting games defined on ring networks.

Abstract We are interested in the problem of satisfying a maximum‐profit subset of undirected communication requests in an optical ring that uses the Wavelength Division Multiplexing technology. We present four deterministic and purely combinatorial algorithms for this problem, and give theoretical guarantees for their worst‐case approximation ratios. Two of these algorithms are novel, whereas the rest are adaptation of earlier approaches. An experimental evaluation of the algorithms in terms of attained profit and execution time reveals that the theoretically best algorithm performs only marginally better than one of the new algorithms, while at the same time being several orders of magnitude slower. Furthermore, an extremely fast greedy heuristic with nonconstant approximation ratio performs reasonably well and may be favored over the other algorithms whenever it is crucial to minimize execution time. © 2011 Wiley Periodicals, Inc. NETWORKS, 2011

We study distributed broadcasting protocols with few trans- missions ('shots') in radio networks with unknown topology. In particular, we examine the case in which a bound κ is given and a node may transmit at most κ times during the broadcasting protocol. We focus on almost oblivious algo- rithms for κ-shot broadcasting, that is, algorithms where the nodes decide whether to transmit or not with very little consideration of the transmission history. In this context, we show a lower bound of Ω(n2/ κ) on the broadcasting time of any almost oblivious κ-shot broadcasting algorithm. We also present an almost oblivious protocol that matches the above lower bound for every κ ≤ √n.

Abstract Mining association rules in relational databases is a significant computational task with lots of applications. A fundamental ingredient of this task is the discovery of sets of attributes (itemsets) whose frequency in the data exceeds some threshold value. In this paper we describe two algorithms for completing the calculation of frequent sets using a tree structure for storing partial supports, called interim‐support (IS) tree. The first of our algorithms (T‐Tree‐First (TTF)) uses a novel tree pruning technique, based on the notion of (fixed‐prefix) potential inclusion, which is specially designed for trees that are implemented using only two pointers per node. This allows to implement the IS tree in a space‐efficient manner. The second algorithm (P‐Tree‐First (PTF)) explores the idea of storing the frequent itemsets in a second tree structure, called the total support tree (T‐tree); the main innovation lies in the use of multiple pointers per node, which provides rapid access to the nodes of the T‐tree and makes it possible to design a new, usually faster, method for updating them. Experimental comparison shows that these techniques result in considerable speedup for both algorithms compared with earlier approaches that also use IS trees (Principles of Data Mining and Knowledge Discovery, Proceedings of the 5th European Conference, PKDD, 2001, Freiburg, September 2001 (Lecture Notes in Artificial Intelligence, vol. 2168). Springer: Berlin, Heidelberg, 54–66; Journal of Knowledge‐Based Syst. 2000; 13:141–149). Further comparison between the two new algorithms, shows that the PTF is generally faster on instances with a large number of frequent itemsets, provided that they are relatively short, whereas TTF is more appropriate whenever there exist few or quite long frequent itemsets; in addition, TTF behaves well on instances in which the densities of the items of the database have a high variance. Copyright © 2008 John Wiley & Sons, Ltd.

In all-optical networks that use WDM technology it is often the case that several communication requests have to be blocked, due to bandwidth and technology limitations. Minimizing request blocking is therefore an important task calling for algorithmic techniques for efficient routing and wavelength assignment. Here we study the problem for rings under both the undirected and the directed settings, corresponding to symmetric and one-way communication respectively. The problem in graph-theoretic terms can be formulated as the maximum routing and path coloring problem. We present a chain-and-matching technique for routing requests and coloring the corresponding paths which gives constant approximations for both the undirected and the directed cases. For the undirected problem we obtain a 2/3-approximation algorithm; this corresponds to a considerable increase in the number of satisfied requests compared to the best known algorithm so far, due to Wan and Liu (1998), that achieves a 1 - 1/e ratio using iteratively a maximum edge-disjoint paths algorithm. For the directed case, we also introduce a balanced matching method which, combined with the chain-and-matching technique, gives a 7/11-approximation algorithm. This algorithm also improves upon the (1 $1/e)-approximation algorithm that can be obtained by extending the iterative method of Wan and Liu.

We investigate the relation between fine-grained and coarse-grained distributed computations of a class of problems related to the generic transitive closure problem (TC for short). We choose an intricate systolic algorithm for the TC problem, by Guibas, Kung and Thompson (GKT algorithm for short), as a starting point due to its particularly close relationship to matrix multiplication. The GKT algorithm reduces the TC problem to three successive parallel matrix multiplications. We extract the main ideas of this algorithm, namely different path decompositions related to min-paths and max-paths computations and devise a two-pass parallel algorithm, such that the second pass is purely a triangular matrix multiplication involving exactly $\frac13$ of the total number of elementary operations (multiplying two single elements of the matrix). This is helpful in coarse-grained parallel computations since matrix multiplication is well parallelizable. A novel approach is used and as a first result a more efficient and simpler two-pass fine-grained algorithm is designed. The second result is a non-trivial transformation of this fine-grained algorithm into a coarse-grained (and more practical) version. The full proof of correctness of the transformation, which is presented in the appendices, is quite complex and is the hardest result of the paper. Our algorithms are specially structured to directly show the correspondence between the main fine-grained and the main coarse-grained operations.