Congestion Model Research Articles

Quantum Distributed Complexity of Set Disjointness on a Line

Given \( x,y\in \lbrace 0,1\rbrace ^n \) , Set Disjointness consists in deciding whether \( x_i=y_i=1 \) for some index \( i \in [n] \) . We study the problem of computing this function in a distributed computing scenario in which the inputs \( x \) and \( y \) are given to the processors at the two extremities of a path of length \( d \) . Each vertex of the path has a quantum processor that can communicate with each of its neighbours by exchanging \( \operatorname{O}(\log n) \) qubits per round. We are interested in the number of rounds required for computing Set Disjointness with constant probability bounded away from \( 1/2 \) . We call this problem “Set Disjointness on a Line”. Set Disjointness on a Line was introduced by Le Gall and Magniez [ 14 ] for proving lower bounds on the quantum distributed complexity of computing the diameter of an arbitrary network in the CONGEST model. However, they were only able to provide a lower bound when the local memory used by the processors on the intermediate vertices of the path is severely limited. More precisely, their bound applies only when the local memory of each intermediate processor consists of \( \operatorname{O}(\log n) \) qubits. In this work, we prove an unconditional lower bound of \( \widetilde{\Omega }\big (\sqrt [3]{n d^2}+\sqrt {n} \, \big) \) rounds for Set Disjointness on a Line with \( d + 1 \) processors. This is the first non-trivial lower bound when there is no restriction on the memory used by the processors. The result gives us a new lower bound of \( \widetilde{\Omega } \big (\sqrt [3]{n\delta ^2}+\sqrt {n} \, \big) \) on the number of rounds required for computing the diameter \( \delta \) of any \( n \) -node network with quantum messages of size \( \operatorname{O}(\log n) \) in the CONGEST model. We draw a connection between the distributed computing scenario above and a new model of query complexity. In this model, an algorithm computing a bi-variate function \( f \) (such as Set Disjointness) has access to the inputs \( x \) and \( y \) through two separate oracles \( {\mathcal {O}}_x \) and \( {\mathcal {O}}_y \) , respectively. The restriction is that the algorithm is required to alternately make \( d \) queries to \( {\mathcal {O}}_x \) and \( d \) queries to \( {\mathcal {O}}_y \) , with input-independent computation in between queries. The model reflects a “switching delay” of \( d \) queries between a “round” of queries to \( x \) and the following “round” of queries to \( y \) . The information-theoretic technique we use for deriving the round lower bound for Set Disjointness on a Line also applies to the number of rounds in this query model. We provide an algorithm for Set Disjointness in this query model with round complexity that matches the round lower bound stated above, up to a polylogarithmic factor. This presents a barrier for obtaining a better round lower bound for Set Disjointness on the Line. At the same time, it hints at the possibility of better communication protocols for the problem.

A Subquadratic-Time Distributed Algorithm for Exact Maximum Matching

For a graph G=(V,E), finding a set of disjoint edges that do not share any vertices is called a matching problem, and finding the maximum matching is a fundamental problem in the theory of distributed graph algorithms. Although local algorithms for the approximate maximum matching problem have been widely studied, exact algorithms has not been much studied. In fact, no exact maximum matching algorithm that is faster than the trivial upper bound of O(n^2) rounds is known for the general instance. In this paper, we propose a randomized O(s_{max}^{3/2}+log n)-round algorithm in the CONGEST model, where s_{\max} is the size of maximum matching. This is the first exact maximum matching algorithm in o(n^2) rounds for general instances in the CONGEST model. The key technical ingredient of our result is a distributed algorithms of finding an augmenting path in O(s_{\max}) rounds, which is based on a novel technique of constructing a sparse certificate of augmenting paths, which is a subgraph of the input graph preserving at least one augmenting path. To establish a highly parallel construction of sparse certificates, we also propose a new characterization of sparse certificates, which might also be of independent interest.

Resilient by design: Informing pandemic-safe building redesign with computational models of resident congestion

This paper describes a computational design-support tool created in response to safe-distancing measures enforced during the COVID-19 pandemic. The tool was developed for a specific use case: understanding congestion in crowded migrant worker dormitories that experienced high rates of COVID-19 transmission in 2020. Building from agent-based and network-based computational simulations, the tool presents a hybrid method for simulating building resident movements based on known or pre-determined schedules and likely itineraries. This hybrid method affords the design tool a novel approach to simultaneous exploration of spatial and temporal design scenarios. The paper demonstrates the use of the tool on an anonymised case study of a high-density migrant worker dormitory, comparing results from a baseline configuration against design variations that modify dormitory physical configuration and schedule. Comparisons between the design scenarios provide evidence for reflections on pandemic-resilient design and operation strategies for dormitories. A conclusions section considers the extent to which the model and case study results are applicable to other dense institutional buildings and describes the paper’s contributions to general understanding of configurational and operational aspects of resilience in the built environment.

Hybrid state analysis with improved firefly optimized linear congestion models of WSNs for DDOS & CRA attacks.

A decentralized form represents a wireless network that facilitates the computers to direct communication without any router. The mobility of individual nodes is necessary within the restricted radio spectrum where contact is often possible on an Adhoc basis. The routing protocol must face the critical situation in these networks forwarding exploration between communicating nodes may create the latency problem in the future. The assault is one of the issues has direct impact network efficiency by disseminating false messages or altering routing detail. Hence, an enhanced routing approach proposes to defend against such challenges. The efficiency of the designated model of wireless devices relies on various output parameters to ensure the requirements. The high energy efficient algorithms: LEACH with FUZZY LOGIC, GENETIC, and FIREFLY are the most effective in optimizing scenarios. The firefly algorithm applies in a model of hybrid state logic with energy parameters: data percentage, transmission rate, and real-time application where the architecture methodology needs to incorporate the design requirements for the attacks within the specified network environment, which can affect energy and packet distribution under various system parametric circumstances. These representations can determine with the statistical linear congestion model in a wireless sensor network mixed state environment.

Hemosiderin Accumulation in Liver Decreases Iron Availability in Tachycardia-Induced Porcine Congestive Heart Failure Model.

Despite advances in the management of iron deficiency in heart failure (HF), the mechanisms underlying the effects of treatment remain to be established. Iron distribution and metabolism in HF pathogenesis need to be clarified. We used a porcine tachycardia-induced cardiomyopathy model to find out how HF development influences hepatic and myocardial iron storing, focusing on ferritin, the main iron storage protein. We found that cumulative liver congestion (due to the decrease of heart function) overwhelms its capacity to recycle iron from erythrocytes. As a consequence, iron is trapped in the liver as poorly mobilized hemosiderin. What is more, the ferritin-bound Fe3+ (reflecting bioavailable iron stores), and assembled ferritin (reflecting ability to store iron) are decreased in HF progression in the liver. We demonstrate that while HF pigs show iron deficiency indices, erythropoiesis is enhanced. Renin–angiotensin–aldosterone system activation and hepatic hepcidin suppression might indicate stress erythropoiesisinduced in HF. Furthermore, assembled ferritin increases but ferritin-bound Fe3+ is reduced in myocardium, indicating that a failing heart increases the iron storage reserve but iron deficiency leads to a drop in myocardial iron stores. Together, HF in pigs leads to down-regulated iron bioavailability and reduced hepatic iron storage making iron unavailable for systemic/cardiac needs.

Distributed distance-r covering problems on sparse high-girth graphs

We prove that the distance-r dominating set, distance-r connected dominating set, distance-r vertex cover, and distance-r connected vertex cover problems admit constant factor approximations in the CONGEST model of distributed computing in a constant number of rounds on classes of sparse high-girth graphs. In this paper, sparse means bounded expansion, and high-girth means girth at least 4r+2. Our algorithm is quite simple; however, the proof of its approximation guarantee is non-trivial. To complement the algorithmic results, we show tightness of our approximation by providing a loosely matching lower bound on rings.Our result is the first to show the existence of constant-factor approximations in a constant number of rounds in non-trivial classes of graphs for distance-r covering problems.

How incidents impact congestion on roadways: A queuing network approach

Motivated by the need for transportation infrastructure and incident management planning, we study traffic density under non-recurrent congestion. This paper provides an analytical solution approximating the stationary distribution of traffic density in roadways where deterioration of service occurs unpredictably. The proposed solution generalizes a queuing model discussed in the literature to long segments that are not space-homogeneous. We compare single and tandem queuing approaches to segments of different lengths and verify whether each model is appropriate. A single-queue approach works sufficiently well in segments with similar traffic behavior across space. In contrast, a tandem-queue approach more appropriately describes the density behavior for long segments with sections having distinct traffic characteristics. These models have a comparable fit to the ones generated using a lognormal distribution. However, they also have interpretable parameters, directly connecting the distribution of congestion to the dynamics of roadway behavior. The proposed models are general, adaptable, and tractable, thus being instrumental in infrastructure and incident management. • Traffic congestion model for highways that may experience unexpected slowdowns. • Intuitive analytical solution with a clear relation between incidents and congestion. • A discussion of situations where tandem queues work better than single queues. • The proposed models are similar to lognormal in fit but have explainable parameters.

ASTRO: Reducing COVID-19 Exposure through Contact Prediction and Avoidance

The fight against the COVID-19 pandemic has highlighted the importance and benefits of recommending paths that reduce the exposure to and the spread of the SARS-CoV-2 coronavirus by avoiding crowded indoor or outdoor areas. Existing path discovery techniques are inadequate for coping with such dynamic and heterogeneous (indoor and outdoor) environments—they typically find an optimal path assuming a homogeneous and/or static graph, and hence they cannot be used to support contact avoidance. In this article, we pose the need for Mobile Contact Avoidance Navigation and propose ASTRO ( A ccessible S patio- T emporal R oute O ptimization), a novel graph-based path discovering algorithm that can reduce the risk of COVID-19 exposure by taking into consideration the congestion in indoor spaces. ASTRO operates in an A * manner to find the most promising path for safe movement within and across multiple buildings without constructing the full graph. For its path finding, ASTRO requires predicting congestion in corridors and hallways. Consequently, we propose a new grid-based partitioning scheme combined with a hash-based two-level structure to store congestion models, called CM-Structure , which enables on-the-fly forecasting of congestion in corridors and hallways. We demonstrate the effectiveness of ASTRO and the accuracy of CM-Structure ’s congestion models empirically with realistic datasets, showing up to one order of magnitude reduction in COVID-19 exposure.

Sphingosine-1-phosphate promotes tumor development and liver fibrosis in mouse model of congestive hepatopathy.

Chronic liver congestion reflecting right-sided heart failure (RHF), Budd-Chiari syndrome, or Fontan-associated liver disease (FALD) is involved in liver fibrosis and HCC. However, molecular mechanisms of fibrosis and HCC in chronic liver congestion remain poorly understood. Here, we first demonstrated that chronic liver congestion promoted HCC and metastatic liver tumor growth using murine model of chronic liver congestion by partial inferior vena cava ligation (pIVCL). As the initial step triggering HCC promotion and fibrosis, gut-derived lipopolysaccharide (LPS) appeared to induce LSECs capillarization in mice and in vitro. LSEC capillarization was also confirmed in patients with FALD. Mitogenic factor, sphingosine-1-phosphate (S1P), was increased in congestive liver and expression of sphingosine kinase 1, a major synthetase of S1P, was increased in capillarized LSECs after pIVCL. Inhibition of S1P receptor (S1PR) 1 (Ex26) and S1PR2 (JTE013) mitigated HCC development and liver fibrosis, respectively. Antimicrobial treatment lowered portal blood LPS concentration, LSEC capillarization, and liver S1P concentration accompanied by reduction of HCC development and fibrosis in the congestive liver. In conclusion, chronic liver congestion promotes HCC development and liver fibrosis by S1P production from LPS-induced capillarized LSECs. Careful treatment of both RHF and liver cancer might be necessary for patients with RHF with primary or metastatic liver cancer.

Latency, capacity, and distributed minimum spanning trees

We study the cost of distributed MST construction in the setting where each edge has a latency and a capacity, along with the weight. Edge latencies capture the delay on the links of the communication network, while capacity captures their throughput (in this case, the rate at which messages can be sent). Depending on how the edge latencies relate to the edge weights, we provide several tight bounds on the time and messages required to construct an MST. When edge weights exactly correspond with the latencies, we show that, perhaps interestingly, the bottleneck parameter in determining the running time of an algorithm is the total weight W of the MST (rather than the total number of nodes n, as in the standard CONGEST model). That is, we show a tight bound of Θ˜(D+W/c) rounds, where D refers to the latency diameter of the graph, W refers to the total weight of the constructed MST and edges have capacity c. The proposed algorithm sends O˜(m+W) messages, where m, the total number of edges in the network graph under consideration, is a known lower bound on message complexity for MST construction. We also show that Ω(W) is a lower bound for fast MST constructions. When the edge latencies and the corresponding edge weights are unrelated, and either can take arbitrary values, we show that (unlike the sub-linear time algorithms in the standard CONGEST model, on small diameter graphs), the best time complexity that can be achieved is Θ˜(D+n/c). However, if we restrict all edges to have equal latency ℓ and capacity c while having possibly different weights (weights could deviate arbitrarily from ℓ), we give an algorithm that constructs an MST in O˜(D+nℓ/c) time. In each case, we provide nearly matching upper and lower bounds.

Locally-iterative Distributed (Δ + 1)-coloring and Applications

We consider graph coloring and related problems in the distributed message-passing model. Locally-iterative algorithms are especially important in this setting. These are algorithms in which each vertex decides about its next color only as a function of the current colors in its 1-hop-neighborhood . In STOC’93 Szegedy and Vishwanathan showed that any locally-iterative Δ + 1-coloring algorithm requires Ω (Δ log Δ + log * n ) rounds, unless there exists “a very special type of coloring that can be very efficiently reduced” [ 44 ]. No such special coloring has been found since then. This led researchers to believe that Szegedy-Vishwanathan barrier is an inherent limitation for locally-iterative algorithms and to explore other approaches to the coloring problem [ 2 , 3 , 19 , 32 ]. The latter gave rise to faster algorithms, but their heavy machinery that is of non-locally-iterative nature made them far less suitable to various settings. In this article, we obtain the aforementioned special type of coloring. Specifically, we devise a locally-iterative Δ + 1-coloring algorithm with running time O (Δ + log * n ), i.e., below Szegedy-Vishwanathan barrier. This demonstrates that this barrier is not an inherent limitation for locally-iterative algorithms. As a result, we also achieve significant improvements for dynamic, self-stabilizing, and bandwidth-restricted settings. This includes the following results: We obtain self-stabilizing distributed algorithms for Δ + 1-vertex-coloring, (2Δ - 1)-edge-coloring, maximal independent set, and maximal matching with O (Δ + log * n ) time. This significantly improves previously known results that have O(n) or larger running times [ 23 ]. We devise a (2Δ - 1)-edge-coloring algorithm in the CONGEST model with O (Δ + log * n ) time and O (Δ)-edge-coloring in the Bit-Round model with O (Δ + log n ) time. The factors of log * n and log n are unavoidable in the CONGEST and Bit-Round models, respectively. Previously known algorithms had superlinear dependency on Δ for (2Δ - 1)-edge-coloring in these models. We obtain an arbdefective coloring algorithm with running time O (√ Δ + log * n ). Such a coloring is not necessarily proper, but has certain helpful properties. We employ it to compute a proper (1 + ε)Δ-coloring within O (√ Δ + log * n ) time and Δ + 1-coloring within O (√ Δ log Δ log * Δ + log * n ) time. This improves the recent state-of-the-art bounds of Barenboim from PODC’15 [ 2 ] and Fraigniaud et al. from FOCS’16 [ 19 ] by polylogarithmic factors. Our algorithms are applicable to the SET-LOCAL model [ 25 ] (also known as the weak LOCAL model). In this model a relatively strong lower bound of Ω (Δ 1/3 ) is known for Δ + 1-coloring. However, most of the coloring algorithms do not work in this model. (In Reference [ 25 ] only Linial’s O (Δ 2 )-time algorithm and Kuhn-Wattenhofer O (Δ log Δ)-time algorithms are shown to work in it.) We obtain the first linear-in-Δ Δ + 1-coloring algorithms that work also in this model.

Single-source shortest paths in the CONGEST model with improved bounds

Single-source shortest paths in the CONGEST model with improved bounds

Rate aware congestion control mechanism for wireless sensor networks

The sensor nodes in wireless sensor networks (WSNs). inherit low processing, shorter range and low power features with the miniature size to offer wireless transmission. Therefore, in order to fulfil the long-time data sensing need, several Quality of Service (QoS) parameters such as: lesser delay, higher throughput and packet delivery ratio (PDR) with minimum overhead must to be improved. In recent years extensive research efforts have been made to ameliorate these parameters to achieve optimum QoS. However, the rate adaptation and congestion control in WSNs are still least explored areas. The traffic congestion in WSNs is the main reason that results in higher delay and low throughput. In this paper, a new rate aware congestion control (RACC) mechanism has been proposed which defines three levels of congestion based on which the data rate, throughput, overhead and the delay. RACC at the transport layer, improves congestion by source rate regulation at the specific hotspot areas. Further, RACC has been applied to different modulation schemes like: 16 QAM (Quadrature Amplitude Modulation), BPSK (Binary Phase Shift Keying) and QPSK (Quadrature Phase Shift Keying) to test the optimum modulation scheme for the proposed approach. The testing is done to ensure the that the data can be sent to the longer distant sensors using appropriate modulation technique suitable for the congestion model (RACC). The simulation outcomes in NS2 tool confirms the improvement of RACC over existing techniques (Delay-aware congestion control protocol (DACC) and Joint energy replenishment and load balancing (J-ERLB)) in WSNs. The overall improvement for RACC over existing techniques follows an improvement percentage 17% for throughput parameter, for packet delivery ratio, it is 8.35%, while for normalized routing overhead it shows 0.56% and for MAC Overhead, average end to end delay, and average remaining energy it shows 0.64%, 2.04% and 59.28% improvement respectively.

The scenario of reducing congestion and resolving parking issues in Makassar City, Indonesia

This study aims to analyze congestion and parking points to construct a behavioral model of congestion, parking, and traffic performance, as well as develop scenarios for projecting the congestion reduction in Makassar City, Indonesia. Three stages were conducted in the study, namely the use of surveys for collecting data on the parking and congestion levels, and the public’s perceptions in developing a behavioral model towards the relationship between parking and congestion. Furthermore, a resolving scenario and projection model for reducing the level of congestion in 2020 to 2050 were compiled. In the first phase, a survey of 67 roads consisting of 78 segments in Makassar was employed to measure the parking and congestion levels. The variables observed were the number of congestion points, vehicle volume, city road capacity, degree of saturation, speed, travel time, and delay. Furthermore, the second stage surveyed the community's perception of the relationship between congestion and parking by distributing questionnaires to 250 respondents. These respondents were selected by incidental sampling in 8 points representing the subdistricts in Makassar. The last stage involved focused group discussions with city managers to formulate resolving scenarios. Base on the scenarios, the projection of the congestion reduction was estimated. The results indicated that the severe congestion incidents, which reduce the travel services in the city, occurred due to crossroads, T junctions, U-turns, parking, and complex occasions. Also, the behavioral model indicated the assessment level and showed that resolving parking issues tend to have more impact in reducing congestion. Therefore, focus group discussions recommend short, medium, and long-term solutions. In addition, projections over 30 years suggest remarkable improvement when resolving parking issues and traffic management are considered in congestion reduction strategies.

Improved distributed approximation for Steiner tree in the CONGEST model

In this paper we present two deterministic distributed algorithms for the Steiner tree (ST) problem in the CONGEST model. The first algorithm computes a 2(1−1/ℓ)-approximate ST using O(S+nlog⁎⁡n) rounds and O(mS+n3/2) messages for a graph of n nodes and m edges, where S is the shortest path diameter of the graph and ℓ is the number of leaf nodes in the optimal ST. It improves the round complexity of the best distributed ST algorithm known so far, which is O˜(S+min{St,n})[34], where t is the number of terminal nodes. The second algorithm improves the message complexity of the first one by dropping the additive term of O(n3/2) at the expense of a logarithmic multiplicative factor in the round complexity. We also show that for graphs with S=O(log⁡n), a 2(1−1/ℓ)-approximate ST can be deterministically computed using O˜(n) rounds and O˜(m) messages and these complexities almost coincide with the results of some of the singularly-optimal minimum spanning tree (MST) algorithms proposed in [15,22,37].

Органопротекция предстательной железы в условиях варикозного расширения вен малого таза

INTRODUCTION Chronic prostatitis is the most common urological disease. The morphological outcome of chronic inflammation is sclerosis, leading to the loss of functional active tissue. Venous congestion of the small pelvis can act as a trigger factor in the development of prostate sclerosis. Venotonics in combination with antioxidants may be considered for organoprotection of the prostate in pelvic varicose veins. PURPOSE to evaluate the protective effect of an antioxidant, venotonic and their combination on the process of formation of connective tissue in the prostate gland against the background of pelvic varicose veins in a chronic experiment. MATERIALS AND METHODS The experiment was carried out on a proven model of chronic venous congestion of the small pelvis and was carried out on 64 sexually mature rabbits weighing 2.6-3.2 kg. 5 groups have been identified. In the first group (n=15), an assessment of the effect of isolated antioxidant (resveratrol) was carried out. In the second group (n=15), an assessment of the effect of isolated venotonic (diosmin) was studied. In the third group (n=15), the effect of a combination of an antioxidant (resveratrol) and venotonic (diosmin) was evaluated. An aqueous solution of the preparations was injected daily for 180 days. In the fourth group (n=15), changes in the prostate were assessed against the background of venous congestion without exposure. In the fifth group (n=4), animals performed to provide data on normal anatomy. The animals were taken out of the experiment at 30, 90, 180 days. Prostate tissue was collected for histological examination and morphometry. In prostate samples, the concentration of hydroxyproline, a marker of connective tissue development, was investigated. RESULTS the isolated administration of resveratrol, as well as diosmin, does not sufficiently compensate for the changes in the hemodynamics of the small pelvis and the toxic effect of metabolic products. With morphometry on day 180, the proportion of glandular tissue in the gland / fibrosis ratio was significantly higher, and fibrosis was lower in Group 3 (79.36 / 9.08 (p<0.01) than in Group 1 (63.1 / 22.74) and Group 2 (65.52 / 21.0) .Quantitative study of hydroxyproline showed lower concentrations in the samples of Group 3 18.44 mg% (p<0.01), relative to Groups 1 and 2 (39.7 and 34.44 mg%) There were no statistically significant differences in the studied parameters between Groups 1 and 2. CONCLUSION the use of a combination of diosmin and resveratrol against the background of chronic venous hyperemia allowed, in the course of the presented experiment, to reduce the lesion volume and the growth of fibrous tissue in the prostate gland. The approach itself requires further study.

Complexity of Eccentricities and All-Pairs Shortest Paths in the Quantum CONGEST Model

Computing the distance parameters of a network, including the diameter, radius, eccentricities and the all-pairs shortest paths (APSP) is a central problem in distributed computing. This paper investigates the distance parameters in the quantum CONGEST models and establishes almost linear lower bounds on eccentricities and APSP, which match the classical upper bounds. Our results imply that there is not quantum speedup for these two problems. In contrast with the diameter and radius, exchanging quantum messages is able to save the communication when the networks have low diameters [F. L. Gall and F. Magniez, Sublinear-time quantum computation of the diameter in CONGEST networks, in Proc. 2018 ACM Symp. Principles of Distributed Computing (PODC), (2018), pp. 337–346; F. Magniez and A. Nayak, arXiv:2002.11795 ]. We obtain the lower bounds via a reduction from the two-way quantum communication complexity of the set intersection [A. A. Razborov, Izv. Math. 159 (2003)].

Low-congestion shortcut and graph parameters

Distributed graph algorithms in the standard CONGEST model often exhibit the time-complexity lower bound of {tilde{Omega }}(sqrt{n} + D) rounds for several global problems, where n denotes the number of nodes and D the diameter of the input graph. Because such a lower bound is derived from special “hard-core” instances, it does not necessarily apply to specific popular graph classes such as planar graphs. The concept of low-congestion shortcuts was initiated by Ghaffari and Haeupler [SODA2016] for addressing the design of CONGEST algorithms running fast in restricted network topologies. In particular, given a graph class {mathcal {C}}, an f-round algorithm for constructing shortcuts of quality q for any instance in {mathcal {C}} results in {tilde{O}}(q + f)-round algorithms for solving several fundamental graph problems such as minimum spanning tree and minimum cut, for {mathcal {C}}. The main interest on this line is to identify the graph classes allowing the shortcuts that are efficient in the sense of breaking {tilde{O}}(sqrt{n}+D)-round general lower bounds. In this study, we consider the relationship between the quality of low-congestion shortcuts and the following four major graph parameters: doubling dimension, chordality, diameter, and clique-width. The key ingredient of the upper-bound side is a novel shortcut construction technique known as short-hop extension, which might be of independent interest.

Mitigating traffic congestion induced by Transportation Network Companies: a policy analysis

This paper analyzes and evaluates several policies aiming to mitigate the congestion effect a Transportation Network Company (TNC) brings to bear on an idealized city that contains a dense central core surrounded by a larger periphery. The TNC offers both solo and pooling e-hail services to the users of public transport. We develop a spatial market equilibrium model over two building blocks: an aggregate congestion model describing the traffic impact of TNC operations on all travelers in the city, including private motorists, and a matching model estimating the TNC's level of service based on the interactions between riders and TNC drivers. Based on the equilibrium model, we formulate and propose solution algorithms to the optimal pricing problem, in which the TNC seeks to optimize its profit or social welfare subject to the extra costs and/or constraints imposed by the congestion mitigation policies. Three congestion mitigation policies are implemented in this study: (i) a trip-based policy that charges a congestion fee on each solo trip starting or ending in the city center; (ii) a cordon-based policy that charges TNC vehicles entering the city center with zero or one passenger; and (iii) a cruising cap policy that requires the TNC to maintain the fleet utilization ratio in the city center above a threshold. Based on a case study of Chicago, we find TNC operations may have a significant congestion effect. Failing to anticipate this effect in the pricing problem leads to sub-optimal decisions that worsen traffic congestion and hurt the TNC's profitability. Of the three policies, the trip-based policy delivers the best performance. It reduces traffic congestion modestly, keeps the TNC's level of service almost intact, and improves overall social welfare substantially. The cruising cap policy benefits private motorists, thanks to the extra congestion relief it brings about. However, because other stakeholders together suffer a much greater loss, its net impact on social welfare is negative. Paradoxically, the policy could worsen the very traffic conditions in the city center that it is designed to improve.

Input-Dynamic Distributed Algorithms for Communication Networks

Consider a distributed task where the communication network is fixed but the local inputs given to the nodes of the distributed system may change over time. In this work, we explore the following question: if some of the local inputs change, can an existing solution be updated efficiently, in a dynamic and distributed manner? To address this question, we define the batch dynamic CONGEST model in which we are given a bandwidth-limited communication network and a dynamic edge labelling defines the problem input. The task is to maintain a solution to a graph problem on the labelled graph under batch changes. We investigate, when a batch of alpha edge label changes arrive, - how much time as a function of alpha we need to update an existing solution, and - how much information the nodes have to keep in local memory between batches in order to update the solution quickly. Our work lays the foundations for the theory of input-dynamic distributed network algorithms. We give a general picture of the complexity landscape in this model, design both universal algorithms and algorithms for concrete problems, and present a general framework for lower bounds. The diverse time complexity of our model spans from constant time, through time polynomial in alpha, and to alpha time, which we show to be enough for any task.