Hydrophilic polycarbonate chips for generation of oil-in-water (O/W) and water-in-oil-in-water (W/O/W) emulsions

Modification of the surfaces of polycarbonate (PC) with the use of a solution of tin (II) chloride renders them hydrophilic. The surface draping is stable against exposure to water and to alcohols. Exposure to alkanes reduces but does not diminish the effect. The method is compatible—in using the same solvent and temperature—with the hydrophobic modification of PC (Jankowski et al. in Lab Chip 11:1151–1156, 2011). The combination of these methods makes it possible to generate single and multiple monodisperse emulsions with the use of flow-focusing junctions in systems made in PC—a material that is suitable for fabrication of multilayer, high-throughput microfluidic devices.     

Hydrophilic polycarbonate chips for generation of oil-in-water (O/W) and water-in-oil-in-water (W/O/W) emulsions

Modification of the surfaces of polycarbonate (PC) with the use of a solution of tin (II) chloride renders them hydrophilic. The surface draping is stable against exposure to water and to alcohols. Exposure to alkanes reduces but does not diminish the effect. The method is compatible—in using the same solvent and temperature—with the hydrophobic modification of PC Jankowski et al. ( Lab Chip 11:748–752, 2011). The combination of these methods makes it possible to generate single and multiple monodisperse emulsions with the use of flow-focusing junctions in systems made in PC—material that is suitable for fabrication of multilayer, high throughput microfluidic devices.     

Makespan minimization of multi-slot just-in-time scheduling on single and parallel machines

The paper addresses the problem of multi-slot just-in-time scheduling. Unlike the existing literature on this subject, it studies a more general criterion—the minimization of the schedule makespan rather than the minimization of the number of slots used by schedule. It gives an O(nlog ² n)-time optimization algorithm for the single machine problem. For arbitrary number of m>1 identical parallel machines it presents an O(nlog n)-time optimization algorithm for the case when the processing time of each job does not exceed its due date. For the general case on m>1 machines, it proposes a polynomial time constant factor approximation algorithm.     

Maximum throughput of multiple access channels in adversarial environments

We consider deterministic distributed broadcasting on multiple access channels in the framework of adversarial queuing. Packets are injected dynamically by an adversary that is constrained by the injection rate and the number of packets that may be injected simultaneously; the latter we call burstiness. A protocol is stable when the number of packets in queues at the stations stays bounded. The maximum injection rate that a protocol can handle in a stable manner is called the throughput of the protocol. We consider adversaries of injection rate 1, that is, of one packet per round, to address the question if the maximum throughput 1 can be achieved, and if so then with what quality of service. We develop a protocol that achieves throughput 1 for any number of stations against leaky-bucket adversaries. The protocol has O(n²+\textburstiness){\mathcal{O}(n^2+\text{burstiness})} packets queued simultaneously at any time, where n is the number of stations; this upper bound is proved to be best possible. A protocol is called fair when each packet is eventually broadcast. We show that no protocol can be both stable and fair for a system of at least two stations against leaky-bucket adversaries. We study in detail small systems of exactly two and three stations against window adversaries to exhibit differences in quality of broadcast among classes of protocols. A protocol is said to have fair latency if the waiting time of packets is O(\textburstiness){\mathcal{O}(\text{burstiness})}. For two stations, we show that fair latency can be achieved by a full sensing protocol, while there is no stable acknowledgment based protocol. For three stations, we show that fair latency can be achieved by a general protocol, while no full sensing protocol can be stable. Finally, we show that protocols that either are fair or do not have the queue sizes affect the order of transmissions cannot be stable in systems of at least four stations against window adversaries.     

Randomized mutual exclusion on a multiple access channel

In this paper we consider the mutual exclusion problem on a multiple access channel. Mutual exclusion is one of the fundamental problems in distributed computing. In the classic version of this problem, n processes execute a concurrent program that occasionally triggers some of them to use shared resources, such as memory, communication channel, device, etc. The goal is to design a distributed algorithm to control entries and exits to/from the shared resource (also called a critical section), in such a way that at any time, there is at most one process accessing it. In our considerations, the shared resource is the shared communication channel itself (multiple access channel), and the main challenge arises because the channel is also the only mean of communication between these processes. We consider both the classic and a slightly weaker version of mutual exclusion, called \(\varepsilon \)-mutual-exclusion, where for each period of a process staying in the critical section the probability that there is some other process in the critical section is at most \(\varepsilon \). We show that there are channel settings, where the classic mutual exclusion is not feasible even for randomized algorithms, while the \(\varepsilon \)-mutual-exclusion is. In more relaxed channel settings, we prove an exponential gap between the makespan complexity of the classic mutual exclusion problem and its weaker \(\varepsilon \)-exclusion version. We also show how to guarantee fairness of mutual exclusion algorithms, i.e., that each process that wants to enter the critical section will eventually succeed.     

Atomic RMI: A Distributed Transactional Memory Framework

This paper presents Atomic RMI, a distributed transactional memory framework that supports the control flow model of execution. Atomic RMI extends Java RMI with distributed transactions that can run on many Java virtual machines located on different network nodes. Our system employs SVA, a fully-pessimistic concurrency control algorithm that provides exclusive access to shared objects and supports rollback and fault tolerance. SVA is capable of achieving a relatively high level of parallelism by interweaving transactions that access the same objects and by making transactions that do not share objects independent of one another. It also allows any operations within transactions, including irrevocable ones, like system calls, and provides an unobtrusive API. Our evaluation shows that in most cases Atomic RMI performs better than fine grained mutual-exclusion and read/write locking mechanisms. Atomic RMI also performs better than an optimistic transactional memory in environments with high contention and a high ratio of write operations, while being competitive otherwise.     

Erotetic Search Scenarios and Three-Valued Logic

Our aim is to model the behaviour of a cognitive agent trying to solve a complex problem by dividing it into sub-problems, but failing to solve some of these sub-problems. We use the powerful framework of erotetic search scenarios (ESS) combined with Kleene’s strong three-valued logic. ESS, defined on the grounds of Inferential Erotetic Logic, has appeared to be a useful logical tool for modelling cognitive goal-directed processes. Using the logical tools of ESS and the three-valued logic, we will show how an agent could solve the initial problem despite the fact that the sub-problems remain unsolved. Thus our model not only indicates missing information but also specifies the contexts in which the problem-solving process may end in success despite the lack of information. We will also show that this model of problem solving may find use in an analysis of natural language dialogues.     

Optimal Deterministic Broadcasting in Known Topology Radio Networks

We consider deterministic broadcasting in radio networks whose nodes have full topological information about the network. The aim is to design a polynomial algorithm, which, given a graph G with source s, produces a fast broadcast scheme in the radio network represented by G. The problem of finding a fastest broadcast scheme for a given graph is NP-hard, hence it is only possible to get an approximation algorithm. We give a deterministic polynomial algorithm which produces a broadcast scheme of length , for every n-node graph of diameter D, thus improving a result of Gąsieniec et al. (PODC 2005) [17] and solving a problem stated there. Unless the inclusion NP BPTIME( holds, the length of a polynomially constructible deterministic broadcast scheme is optimal.A preliminary version of this paper (with a weaker result) appeared in the Proc. 7th International Workshop on Approximation Algorithms for Combinatorial Optimization Problems (APPROX’2004), August 2004, Harvard University, Cambridge, USA, LNCS 3122, 171–182. Research of the second author supported in part by NSERC discovery grant and by the Research Chair in Distributed Computing of the Université du Québec en Outaouais. Part of this work was done during the second author’s visit at the Max-Planck-Institut für Informatik.     

Robust gossiping with an application to consensus

We study deterministic gossiping in synchronous systems with dynamic crash failures. Each processor is initialized with an input value called rumor. In the standard gossip problem, the goal of every processor is to learn all the rumors. When processors may crash, then this goal needs to be revised, since it is possible, at a point in an execution, that certain rumors are known only to processors that have already crashed. We define gossiping to be completed, for a system with crashes, when every processor knows either the rumor of processor v or that v has already crashed, for any processor v. We design gossiping algorithms that are efficient with respect to both time and communication. Let t<n be the number of failures, where n is the number of processors. If , then one of our algorithms completes gossiping in O(log²t) time and with O(npolylogn) messages. We develop an algorithm that performs gossiping with O(n^1.77) messages and in O(log²n) time, in any execution in which at least one processor remains non-faulty. We show a trade-off between time and communication in gossiping algorithms: if the number of messages is at most O(npolylogn), then the time has to be at least . By way of application, we show that if n−t=Ω(n), then consensus can be solved in O(t) time and with O(nlog²t) messages.