Abstract: Implementation of a commercial application to a
grid infrastructure introduces new challenges in managing the
quality-of-service (QoS) requirements, most stem from the fact
that negotiation on QoS between the user and the service provider
should strictly be satisfied. An interesting commercial application
with a wide impact on a variety of fields, which can benefit from
the computational grid technologies, is three–dimensional (3-D)
rendering. In order to implement, however, 3-D rendering to a
grid infrastructure, we should develop appropriate scheduling
and resource allocation mechanisms so that the negotiated (QoS)
requirements are met. Efficient scheduling schemes require
modeling and prediction of rendering workload. In this paper
workload prediction is addressed based on a combined fuzzy
classification and neural network model. Initially, appropriate
descriptors are extracted to represent the synthetic world. The
descriptors are obtained by parsing RIB formatted files, which
provides a general structure for describing computer-generated
images. Fuzzy classification is used for organizing rendering
descriptor so that a reliable representation is accomplished which
increases the prediction accuracy. Neural network performs
workload prediction by modeling the nonlinear input-output
relationship between rendering descriptors and the respective
computational complexity. To increase prediction accuracy, a
constructive algorithm is adopted in this paper to train the neural
network so that network weights and size are simultaneously
estimated. Then, a grid scheduler scheme is proposed to estimate
the queuing order that the tasks should be executed and the
most appopriate processor assignment so that the demanded
QoS are satisfied as much as possible. A fair scheduling policy is
considered as the most appropriate. Experimental results on a real
grid infrastructure are presented to illustrate the efficiency of the
proposed workload prediction — scheduling algorithm compared
to other approaches presented in the literature.
Abstract: In this paper we consider the problem of web page usage prediction in a web site by modeling users¢ navigation history and web page content with weighted suffix trees. This user¢s navigation prediction can be exploited either in an on-line recommendation system in a web site or in a web page cache system. The method proposed has the advantage that it demands a constant amount of computational effort per one user¢s action and consumes a relatively small amount of extra memory space. These features make the method ideal for an on-line working environment. Finally, we have performed an evaluation of the proposed scheme with experiments on various web site log files and web pages and we have found that its quality performance is fairly well and in many cases an outperforming one.
Abstract: About this book
This state-of-the-art survey features papers that were selected after an open call following the International Dagstuhl Seminar on Algorithmic Methods for Railway Optimization held in Dagstuhl Castle, Germany, in June 2004. The second part of the volume constitutes the refereed proceedings of the 4th International Workshop on Algorithmic Methods and Models for Optimization of Railways held in Bergen, Norway, in September 2004.
The volume covers algorithmic methods for analyzing and solving problems arising in railway optimizations, with a special focus on the interplay between railway and other public transportation systems. Beside algorithmics and mathematical optimization, the relevance of formal models and the influence of applications on problem modeling are also considered. In addition, the papers address experimental studies and useful prototype implementations.
The 17 full papers presented here were carefully reviewed and selected from numerous submissions and are organized into topical sections covering network and line planning, timetabling and timetable information, rolling stock and crew scheduling, and real-time operations.
Abstract: An ever growing emphasis is put nowadays in developing personalized journey planning and renewable mobility services in smart cities. These services combine means of scheduled-based public transport and electric vehicles or bikes, using crowdsourcing techniques for collecting real-time traffic information and for assessing the recommended routes. The goal is to develop an information system that will allow the fast, real-time computation of best routes.
The main challenges in developing such an information system are both technological and algorithmic. The technological challenge concerns the collection, storage, management, and updating of a huge volume of transport data that are usually time-dependent, and the provision (through these data) of personalized renewable mobility services in smartphones. This challenge is typically confronted by creating a cloud infrastructure that on the one hand will support the storage, management, and updating of data, while on the other hand it will handle the necessary data feed to the smartphone applications for providing the users with the requested best routes.
The algorithmic challenge concerns the development of innovative algorithms for the efficient provision of journey planning services in smartphones, based on data they will receive from the cloud infrastructure. These services guarantee the computation of realistic and useful best routes, as well as the updating of the precomputed (route and timetable) information, in case of delays of scheduled public transport vehicles, so that the users can online update their routes to destination. The goal is to develop an algorithmic basis for supporting modern renewable mobility services (information systems), such as "mobility on demand'' (where the next leg of a journey is decided in real-time) and "door-to-door'' personalized mobility, in urban scheduled-based public transport environments. Scheduled-based public transport information systems should not only compute in real-time end-user queries requesting best routes, but also to update the timetable information in case of delays.
The core algorithmic issues of mobility and journey planning (regarding the computation of optimal routes under certain criteria) in scheduled-based public transport systems concern the efficient solution of the fundamental earlier arrival (EA) problem (compute a journey from station S to station T minimizing the overall traveling time required to complete the journey), the minimum number of
transfers (MNT) problem (compute a journey from station S to station T minimizing the number of times a passenger is required to change vehicle), and the efficient updating of timetable information system in case of vehicle delays. The EA and MNT problems have been extensively studied in the literature under two main approaches: the array-based modeling (where the timetable is represented as an array) and the graph-based modeling (where the timetable is represented as a graph). Experimental results have shown so far that the array-based approaches are faster in terms of query time than graph-based ones, as they are able to better exploit data locality and do not rely on priority queues. On the other hand, the array-based approaches have not been theoretically or experimentally studied as far as the efficient updating of timetable information, in case of delays, is concerned.
In this thesis, new graph-based models are being developed that solve efficiently the aforementioned fundamental algorithmic mobility problems in urban scheduled-based public transport information systems, along with a mobile application (journey planner) running on Android-based smartphones that includes a service for the evaluation of the recommended routes by the users. In particular:
(a) An extensive comparative evaluation was conducted on graph-based dynamic models that represent big data volumes regarding their suitability for representing timetable information. The study confirmed that the realistic time-expanded model is the most suitable for representing timetable information.
(b) Two new graph-based models have been developed for representing timetable information (in a timetable information system), the reduced time-expanded model and the dynamic timetable model (DTM), both of which are more space-efficient with respect to the realistic time-expanded model. For both of the new models, new efficient algorithms were developed for fast answering of EA and MNT queries, as well as for updating the timetable information representation in case of delays.
(c)An experimental evaluation was conducted with the new graph-based models and their associated query and update algorithms on a set of 14 real-world scheduled-based transportation systems, including the metropolitan areas of Berlin, Athens, London, Rome, and Madrid. The experimental results showed that the query algorithms of the reduced time-expanded model are superior to those of the DTM model, while the reverse is true regarding the update algorithms. In addition, the experimental study showed that the query algorithms of the new graph-based models compete favorably with those of the best array-based models.
(d) A mobile, cloud-based, journey planner (information system) was developed whose core algorithmic engine builds upon the new graph-based models. The mobile application is accompanied by a service that allows the users to assess the recommended journeys. The journey planner demonstrates the practicality of the new graph-based models and their associated query and update algorithms.
Abstract: We conduct an experimental study for a fundamental case of the timetabling problem in a public railway network under disruptions. Three bicriteria optimazation problems, modeling the robustness of the timetable towards delays, are experimentally evaluated against various waiting time rules at stations. Our results constitute the first proofs-of-concept for these models.
Abstract: We present a 40 Gb/s asynchronous self-routing network and node architecture that exploits bit
and packet level optical signal processing to perform synchronization, forwarding and
switching. Optical packets are self-routed on a hop-by-hop basis through the network by using
stacked optical tags, each representing a specific optical node. Each tag contains control signals
for configuring the switching matrix and forwarding each packet to the appropriate outgoing
link and onto the next hop. Physical layer simulations are performed, modeling each optical subsystem
of the node showing acceptable signal quality and Bit Error Rates. Resource reservationbased
signaling algorithms are theoretically modeled for the control plane capable of providing
high performance in terms of blocking probability and holding time.
Abstract: Here we survey various computational models for Wireless Sensor Networks (WSNs). The population protocol model (PP) considers networks of tiny mobile finite-state artifacts that can sense the environment and communicate in pairs to perform a computation. The mediated population protocol model (MPP) enhances the previous model by allowing the communication links to have a constant size buffer, providing more computational power. The graph decision MPP model (GDM) is a special case of MPP that focuses on the MPP's ability to decide graph properties of the network. Another direction towards enhancing the PP is followed by the PALOMA model in which the artifacts are no longer finite-state automata but Turing Machines of logarithmic memory in the population size. A different approach to modeling WSNs is the static synchronous sensor field model (SSSF) which describes devices communicating through a fixed communication graph and interacting with their environment via input and output data streams. In this survey, we present the computational capabilities of each model and provide directions for further research.
Abstract: When one engineers distributed algorithms, some special characteristics
arise that are different from conventional (sequential or parallel)
computing paradigms. These characteristics include: the need for either a
scalable real network environment or a platform supporting a simulated
distributed environment; the need to incorporate asynchrony, where arbitrarya
synchrony is hard, if not impossible, to implement; and the generation
of “difficult” input instances which is a particular challenge. In this
work, we identifys ome of the methodological issues required to address
the above characteristics in distributed algorithm engineering and illustrate
certain approaches to tackle them via case studies. Our discussion
begins byad dressing the need of a simulation environment and how asynchronyis
incorporated when experimenting with distributed algorithms.
We then proceed bys uggesting two methods for generating difficult input
instances for distributed experiments, namelya game-theoretic one and another
based on simulations of adversarial arguments or lower bound proofs.
We give examples of the experimental analysis of a pursuit-evasion protocol
and of a shared memorypro blem in order to demonstrate these ideas.
We then address a particularlyi nteresting case of conducting experiments
with algorithms for mobile computing and tackle the important issue of
motion of processes in this context. We discuss the two-tier principle as
well as a concurrent random walks approach on an explicit representation
of motions in ad-hoc mobile networks, which allow at least for averagecase
analysis and measurements and may give worst-case inputs in some
cases. Finally, we discuss a useful interplay between theory and practice
that arise in modeling attack propagation in networks.
Abstract: We consider two approaches that model timetable information in public transportation systems
as shortest-path problems in weighted graphs. In the time-expanded approach, every event at
a station, e.g., the departure of a train, is modeled as a node in the graph, while in the timedependent
approach the graph contains only one node per station. Both approaches have been
recently considered for (a simplified version of) the earliest arrival problem, but little is known
about their relative performance. Thus far, there are only theoretical arguments in favor of the
time-dependent approach. In this paper, we provide the first extensive experimental comparison of
the two approaches. Using several real-world data sets, we evaluate the performance of the basic
models and of several new extensions towards realistic modeling. Furthermore, new insights on
solving bicriteria optimization problems in both models are presented. The time-expanded approach
turns out to be more robust for modeling more complex scenarios, whereas the time-dependent
approach shows a clearly better performance.
Abstract: We consider two approaches that model timetable information in public transportation systems
as shortest-path problems in weighted graphs. In the time-expanded approach, every event at
a station, e.g., the departure of a train, is modeled as a node in the graph, while in the timedependent
approach the graph contains only one node per station. Both approaches have been
recently considered for (a simplified version of) the earliest arrival problem, but little is known
about their relative performance. Thus far, there are only theoretical arguments in favor of the
time-dependent approach. In this paper, we provide the first extensive experimental comparison of
the two approaches. Using several real-world data sets, we evaluate the performance of the basic
models and of several new extensions towards realistic modeling. Furthermore, new insights on
solving bicriteria optimization problems in both models are presented. The time-expanded approach
turns out to be more robust for modeling more complex scenarios, whereas the time-dependent
approach shows a clearly better performance.
Abstract: We present a set of three new time-dependent models with
increasing
exibility for realistic route planning in
flight networks. By
these means, we obtain small graph sizes while modeling airport procedures
in a realistic way. With these graphs, we are able to efficiently
compute a set of best connections with multiple criteria over a full day.
It even turns out that due to the very limited graph sizes it is feasible
to precompute full distance tables between all airports. As a result, best
connections can be retrieved in a few microseconds on real world data.
Abstract: We investigate the impact of multiple, mobile sinks on
efficient data collection in wireless sensor networks. To
improve performance, our protocol design focuses on minimizing
overlaps of sink trajectories and balancing the service load
among the sinks. To cope with high network dynamics, placement
irregularities and limited network knowledge we propose three different
protocols: a) a centralized one, that explicitly equalizes spatial coverage;
this protocol assumes strong modeling assumptions, and also serves as a kind
of performance lower bound in uniform networks of low dynamics b)
a distributed protocol based on mutual avoidance of sinks c) a clustering
protocol that distributively groups service areas towards balancing the load per sink.
Our simulation findings demonstrate significant gains in latency, while keeping the success
rate and the energy dissipation at very satisfactory levels even under
high network dynamics and deployment heterogeneity.
Abstract: Evolutionary dynamics have been traditionally studied in the context of homogeneous populations, mainly described by the Moran process [15]. Recently, this approach has been generalized in [13] by arranging individuals on the nodes of a network (in general, directed). In this setting, the existence of directed arcs enables the simulation of extreme phenomena, where the fixation probability of a randomly placed mutant (i.e. the probability that the offsprings of the mutant eventually spread over the whole population) is arbitrarily small or large. On the other hand, undirected networks (i.e. undirected graphs) seem to have a smoother behavior, and thus it is more challenging to find suppressors/amplifiers of selection, that is, graphs with smaller/greater fixation probability than the complete graph (i.e. the homogeneous population). In this paper we focus on undirected graphs. We present the first class of undirected graphs which act as suppressors of selection, by achieving a fixation probability that is at most one half of that of the complete graph, as the number of vertices increases. Moreover, we provide some generic upper and lower bounds for the fixation
probability of general undirected graphs. As our main contribution, we introduce the natural alternative of the model proposed in [13]. In our new evolutionary model, all individuals interact simultaneously and the result is a compromise between aggressive and non-aggressive individuals. That is, the behavior of the individuals in our new model and in the model of [13] can be interpreted as an “aggregation” vs. an “all-or-nothing” strategy, respectively. We prove that our new model of mutual influences admits a potential function, which guarantees the convergence of the system for any graph topology and any initial fitness vector of the individuals. Furthermore, we prove fast convergence to the stable state for the case of the complete graph, as well as we provide almost tight bounds on the limit fitness of the individuals. Apart from being important on its own, this new evolutionary model appears to be useful also in the abstract modeling of control mechanisms over invading populations in networks. We demonstrate this by introducing and analyzing two alternative control approaches, for which we bound the time needed to stabilize to the “healthy” state of the system.
Abstract: In this work we extend the population protocol model of Angluin et al., in
order to model more powerful networks of very small resource limited
artefacts (agents) that is possible to follow some unpredictable passive
movement. These agents communicate in pairs according to the commands of
an adversary scheduler. A directed (or undirected) communication graph
encodes the following information: each edge (u,\~{o}) denotes that during the
computation it is possible for an interaction between u and \~{o} to happen in
which u is the initiator and \~{o} the responder. The new characteristic of
the proposed mediated population protocol model is the existance of a
passive communication provider that we call mediator. The mediator is a
simple database with communication capabilities. Its main purpose is to
maintain the permissible interactions in communication classes, whose
number is constant and independent of the population size. For this reason
we assume that each agent has a unique identifier for whose existence the
agent itself is not informed and thus cannot store it in its working
memory. When two agents are about to interact they send their ids to the
mediator. The mediator searches for that ordered pair in its database and
if it exists in some communication class it sends back to the agents the
state corresponding to that class. If this interaction is not permitted to
the agents, or, in other words, if this specific pair does not exist in
the database, the agents are informed to abord the interaction. Note that
in this manner for the first time we obtain some control on the safety of
the network and moreover the mediator provides us at any time with the
network topology. Equivalently, we can model the mediator by communication
links that are capable of keeping states from a edge state set of constant
cardinality. This alternative way of thinking of the new model has many
advantages concerning the formal modeling and the design of protocols,
since it enables us to abstract away the implementation details of the
mediator. Moreover, we extend further the new model by allowing the edges
to keep readable only costs, whose values also belong to a constant size
set. We then allow the protocol rules for pairwise interactions to modify
the corresponding edge state by also taking into account the costs. Thus,
our protocol descriptions are still independent of the population size and
do not use agent ids, i.e. they preserve scalability, uniformity and
anonymity. The proposed Mediated Population Protocols (MPP) can stably
compute graph properties of the communication graph. We show this for the
properties of maximal matchings (in undirected communication graphs), also
for finding the transitive closure of directed graphs and for finding all
edges of small cost. We demonstrate that our mediated protocols are
stronger than the classical population protocols. First of all we notice
an obvious fact: the classical model is a special case of the new model,
that is, the new model can compute at least the same things with the
classical one. We then present a mediated protocol that stably computes
the product of two nonnegative integers in the case where G is complete
directed and connected. Such kind of predicates are not semilinear and it
has been proven that classical population protocols in complete graphs can
compute precisely the semilinear predicates, thus in this manner we show
that there is at least one predicate that our model computes and which the
classical model cannot compute. To show this fact, we state and prove a
general Theorem about the composition of two mediated population
protocols, where the first one has stabilizing inputs. We also show that
all predicates stably computable in our model are (non-uniformly) in the
class NSPACE(m), where m is the number of edges of the communication
graph. Finally, we define Randomized MPP and show that, any Peano
predicate accepted by a Randomized MPP, can be verified in deterministic
polynomial time.
Abstract: This Volume contains the 11 papers corresponding to poster and demo presentations
accepted to the 7th ACM/IEEE International Symposium on Modeling,
Analysis and Simulation ofWireless and Mobile Systems (MSWiM 04),
that is held October 4-6, 2004, in Venice, Italy.
MSWiM 2004 (http://www.cs.unibo.it/mswim2004/) is intended to provide
an international forum for original ideas, recent results and achievements on
issues and challenges related to mobile and wireless systems.
A Call for Posters was announced and widely disseminated, soliciting posters
that report on recent original results or on-going research in the area of wireless
and mobile networks. Prospective authors were encouraged to submit interesting
results on all aspects of modeling, analysis and simulation of mobile and
wireless networks and systems. The scope and topics of the Posters Session
were the same as those included in the MSWiM Call for Papers (see above).
Poster presentations were meant to provide authors with early feedback on
their research work and enable them to present their research and exchange
ideas during the Symposium.
All submissions to the call for posters as well as selected papers submitted
to MSWiM 04 were considered and reviewed. The review process resulted in
accepting the set of 11 papers included in this Volume. Accepted posters will
also be on display during the Symposium.
The set of papers in this Proceedings covers a wide range of important topics
in wireless and mobile computing, including channel allocation in wireless
networks, quality of service provisioning in IEEE 802.11 wireless LANs, IP
mobility support, energy conservation, routing in mobile adhoc networks, resource
sharing, wireless access to the WWW, sensor networks etc. The performance
evaluation techniques used include both analysis and simulation.
We hope that the poster papers included in this Volume will facilitate a fruitful
and lively discussion and exchange of interesting and creative ideas during
the Symposium.
We wish to thank the MSWiM Steering Committee Chair Azzedine Boukerche
and the Program Co-Chairs ofMSWiM 04 Carla-Fabiana Chiasserini and
Lorenzo Donatiello for their valuable help in the selection procedure. Also, the
MSWiM 04 Publicity Co-Chairs Luciano Bononi, Helen Karatza and Mirela
Sechi Moretti Annoni Notare for disseminating the Call for Posters.
We wish to warmly thank the Poster Proceedings Chair Ioannis Chatzigiannakis
for carefully doing an excellent job in preparing the Volume you now
hold in your hands.
Abstract: The 8th ACM/IEEE International Symposium on Modeling, Analysis and Simulation of Wireless and Mobile Systems Symposium (MSWiM 2005) solicits posters that report on recent original results or on-going research in the area of wireless and mobile networks.
Abstract: The 9th ACM/IEEE International Symposium on Modeling, Analysis and Simulation of Wireless and Mobile Systems Symposium (MSWiM 2006) solicits posters that report on recent original results or on-going research in the area of wireless and mobile networks.
Abstract: We give an overview of models and efficient algorithms for
optimally solving timetable information problems like “given a departure
and an arrival station as well as a departure time, which is the
connection that arrives as early as possible at the arrival station?” Two
main approaches that transform the problems into shortest path problems
are reviewed, including issues like the modeling of realistic details
(e.g., train transfers) and further optimization criteria (e.g., the number
of transfers). An important topic is also multi-criteria optimization,
where in general all attractive connections with respect to several criteria
shall be determined. Finally, we discuss the performance of the described
algorithms, which is crucial for their application in a real system.
Abstract: We give an overview of models and efficient algorithms for optimally solving timetable information problems like “given a departure and an arrival station as well as a departure time, which is the connection that arrives as early as possible at the arrival station?” Two main approaches that transform the problems into shortest path problems are reviewed, including issues like the modeling of realistic details (e.g., train transfers) and further optimization criteria (e.g., the number of transfers). An important topic is also multi-criteria optimization, where in general all attractive connections with respect to several criteria shall be determined. Finally, we discuss the performance of the described algorithms, which is crucial for their application in a real system.