3,182 research outputs found
Time Versus Cost Tradeoffs for Deterministic Rendezvous in Networks
Two mobile agents, starting from different nodes of a network at possibly
different times, have to meet at the same node. This problem is known as
. Agents move in synchronous rounds. Each agent has a
distinct integer label from the set . Two main efficiency
measures of rendezvous are its (the number of rounds until the
meeting) and its (the total number of edge traversals). We
investigate tradeoffs between these two measures. A natural benchmark for both
time and cost of rendezvous in a network is the number of edge traversals
needed for visiting all nodes of the network, called the exploration time.
Hence we express the time and cost of rendezvous as functions of an upper bound
on the time of exploration (where and a corresponding exploration
procedure are known to both agents) and of the size of the label space. We
present two natural rendezvous algorithms. Algorithm has cost
(and, in fact, a version of this algorithm for the model where the
agents start simultaneously has cost exactly ) and time . Algorithm
has both time and cost . Our main contributions are
lower bounds showing that, perhaps surprisingly, these two algorithms capture
the tradeoffs between time and cost of rendezvous almost tightly. We show that
any deterministic rendezvous algorithm of cost asymptotically (i.e., of
cost ) must have time . On the other hand, we show that any
deterministic rendezvous algorithm with time complexity must have
cost
Deterministic Rendezvous at a Node of Agents with Arbitrary Velocities
We consider the task of rendezvous in networks modeled as undirected graphs.
Two mobile agents with different labels, starting at different nodes of an
anonymous graph, have to meet. This task has been considered in the literature
under two alternative scenarios: weak and strong. Under the weak scenario,
agents may meet either at a node or inside an edge. Under the strong scenario,
they have to meet at a node, and they do not even notice meetings inside an
edge. Rendezvous algorithms under the strong scenario are known for synchronous
agents. For asynchronous agents, rendezvous under the strong scenario is
impossible even in the two-node graph, and hence only algorithms under the weak
scenario were constructed. In this paper we show that rendezvous under the
strong scenario is possible for agents with restricted asynchrony: agents have
the same measure of time but the adversary can arbitrarily impose the speed of
traversing each edge by each of the agents. We construct a deterministic
rendezvous algorithm for such agents, working in time polynomial in the size of
the graph, in the length of the smaller label, and in the largest edge
traversal time.Comment: arXiv admin note: text overlap with arXiv:1704.0888
Asynchronous approach in the plane: A deterministic polynomial algorithm
In this paper we study the task of approach of two mobile agents having the
same limited range of vision and moving asynchronously in the plane. This task
consists in getting them in finite time within each other's range of vision.
The agents execute the same deterministic algorithm and are assumed to have a
compass showing the cardinal directions as well as a unit measure. On the other
hand, they do not share any global coordinates system (like GPS), cannot
communicate and have distinct labels. Each agent knows its label but does not
know the label of the other agent or the initial position of the other agent
relative to its own. The route of an agent is a sequence of segments that are
subsequently traversed in order to achieve approach. For each agent, the
computation of its route depends only on its algorithm and its label. An
adversary chooses the initial positions of both agents in the plane and
controls the way each of them moves along every segment of the routes, in
particular by arbitrarily varying the speeds of the agents. A deterministic
approach algorithm is a deterministic algorithm that always allows two agents
with any distinct labels to solve the task of approach regardless of the
choices and the behavior of the adversary. The cost of a complete execution of
an approach algorithm is the length of both parts of route travelled by the
agents until approach is completed. Let and be the initial
distance separating the agents and the length of the shortest label,
respectively. Assuming that and are unknown to both agents, does
there exist a deterministic approach algorithm always working at a cost that is
polynomial in and ? In this paper, we provide a positive answer to
the above question by designing such an algorithm
Rendezvous in Networks in Spite of Delay Faults
Two mobile agents, starting from different nodes of an unknown network, have
to meet at the same node. Agents move in synchronous rounds using a
deterministic algorithm. Each agent has a different label, which it can use in
the execution of the algorithm, but it does not know the label of the other
agent. Agents do not know any bound on the size of the network. In each round
an agent decides if it remains idle or if it wants to move to one of the
adjacent nodes. Agents are subject to delay faults: if an agent incurs a fault
in a given round, it remains in the current node, regardless of its decision.
If it planned to move and the fault happened, the agent is aware of it. We
consider three scenarios of fault distribution: random (independently in each
round and for each agent with constant probability 0 < p < 1), unbounded adver-
sarial (the adversary can delay an agent for an arbitrary finite number of
consecutive rounds) and bounded adversarial (the adversary can delay an agent
for at most c consecutive rounds, where c is unknown to the agents). The
quality measure of a rendezvous algorithm is its cost, which is the total
number of edge traversals. For random faults, we show an algorithm with cost
polynomial in the size n of the network and polylogarithmic in the larger label
L, which achieves rendezvous with very high probability in arbitrary networks.
By contrast, for unbounded adversarial faults we show that rendezvous is not
feasible, even in the class of rings. Under this scenario we give a rendezvous
algorithm with cost O(nl), where l is the smaller label, working in arbitrary
trees, and we show that \Omega(l) is the lower bound on rendezvous cost, even
for the two-node tree. For bounded adversarial faults, we give a rendezvous
algorithm working for arbitrary networks, with cost polynomial in n, and
logarithmic in the bound c and in the larger label L
Multi-rendezvous Spacecraft Trajectory Optimization with Beam P-ACO
The design of spacecraft trajectories for missions visiting multiple
celestial bodies is here framed as a multi-objective bilevel optimization
problem. A comparative study is performed to assess the performance of
different Beam Search algorithms at tackling the combinatorial problem of
finding the ideal sequence of bodies. Special focus is placed on the
development of a new hybridization between Beam Search and the Population-based
Ant Colony Optimization algorithm. An experimental evaluation shows all
algorithms achieving exceptional performance on a hard benchmark problem. It is
found that a properly tuned deterministic Beam Search always outperforms the
remaining variants. Beam P-ACO, however, demonstrates lower parameter
sensitivity, while offering superior worst-case performance. Being an anytime
algorithm, it is then found to be the preferable choice for certain practical
applications.Comment: Code available at https://github.com/lfsimoes/beam_paco__gtoc
Deterministic meeting of sniffing agents in the plane
Two mobile agents, starting at arbitrary, possibly different times from
arbitrary locations in the plane, have to meet. Agents are modeled as discs of
diameter 1, and meeting occurs when these discs touch. Agents have different
labels which are integers from the set of 0 to L-1. Each agent knows L and
knows its own label, but not the label of the other agent. Agents are equipped
with compasses and have synchronized clocks. They make a series of moves. Each
move specifies the direction and the duration of moving. This includes a null
move which consists in staying inert for some time, or forever. In a non-null
move agents travel at the same constant speed, normalized to 1. We assume that
agents have sensors enabling them to estimate the distance from the other agent
(defined as the distance between centers of discs), but not the direction
towards it. We consider two models of estimation. In both models an agent reads
its sensor at the moment of its appearance in the plane and then at the end of
each move. This reading (together with the previous ones) determines the
decision concerning the next move. In both models the reading of the sensor
tells the agent if the other agent is already present. Moreover, in the
monotone model, each agent can find out, for any two readings in moments t1 and
t2, whether the distance from the other agent at time t1 was smaller, equal or
larger than at time t2. In the weaker binary model, each agent can find out, at
any reading, whether it is at distance less than \r{ho} or at distance at least
\r{ho} from the other agent, for some real \r{ho} > 1 unknown to them. Such
distance estimation mechanism can be implemented, e.g., using chemical sensors.
Each agent emits some chemical substance (scent), and the sensor of the other
agent detects it, i.e., sniffs. The intensity of the scent decreases with the
distance.Comment: A preliminary version of this paper appeared in the Proc. 23rd
International Colloquium on Structural Information and Communication
Complexity (SIROCCO 2016), LNCS 998
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