80,212 research outputs found
Offline and online power aware resource allocation algorithms with migration and delay constraints
© . This manuscript version is made available under the CC-BY-NC-ND 4.0 license http://creativecommons.org/licenses/by-nc-nd/4.0/In order to handle advanced mobile broadband services and Internet of Things (IoT), future Internet and 5G networks are expected to leverage the use of network virtualization, be much faster, have greater capacities, provide lower latencies, and significantly be power efficient than current mobile technologies. Therefore, this paper proposes three power aware algorithms for offline, online, and migration applications, solving the resource allocation problem within the frameworks of network function virtualization (NFV) environments in fractions of a second. The proposed algorithms target minimizing the total costs and power consumptions in the physical network through sufficiently allocating the least physical resources to host the demands of the virtual network services, and put into saving mode all other not utilized physical components. Simulations and evaluations of the offline algorithm compared to the state-of-art resulted on lower total costs by 32%. In addition to that, the online algorithm was tested through four different experiments, and the results argued that the overall power consumption of the physical network was highly dependent on the demands’ lifetimes, and the strictness of the required end-to-end delay. Regarding migrations during online, the results concluded that the proposed algorithms would be most effective when applied for maintenance and emergency conditions.Peer ReviewedPreprin
Hierarchical Path Search with Partial Materialization of Costs for a Smart Wheelchair
In this paper, the off-line path planner module of a smart wheelchair aided navigation
system is described. Environmental information is structured into a hierarchical graph (H-graph) and
used either by the user interface or the path planner module. This information structure facilitates
efficient path search and easier information access and retrieval. Special path planning issues like
planning between floors of a building (vertical path planning) are also viewed. The H-graph proposed
is modelled by a tree. The hierarchy of abstractions contained in the tree has several levels of detail.
Each abstraction level is a graph whose nodes can represent other graphs in a deeper level of the
hierarchy. Path planning is performed using a path skeleton which is built from the deepest
abstraction levels of the hierarchy to the most upper levels and completed in the last step of the
algorithm. In order not to lose accuracy in the path skeleton generation and speed up the search, a set
of optimal subpaths are previously stored in some nodes of the H-graph (path costs are partially
materialized). Finally, some experimental results are showed and compared to traditional heuristic
search algorithms used in robot path planning.Comisión Interministerial de Ciencia y TecnologÃa TER96-2056-C02-0
Efficient Multi-Robot Coverage of a Known Environment
This paper addresses the complete area coverage problem of a known
environment by multiple-robots. Complete area coverage is the problem of moving
an end-effector over all available space while avoiding existing obstacles. In
such tasks, using multiple robots can increase the efficiency of the area
coverage in terms of minimizing the operational time and increase the
robustness in the face of robot attrition. Unfortunately, the problem of
finding an optimal solution for such an area coverage problem with multiple
robots is known to be NP-complete. In this paper we present two approximation
heuristics for solving the multi-robot coverage problem. The first solution
presented is a direct extension of an efficient single robot area coverage
algorithm, based on an exact cellular decomposition. The second algorithm is a
greedy approach that divides the area into equal regions and applies an
efficient single-robot coverage algorithm to each region. We present
experimental results for two algorithms. Results indicate that our approaches
provide good coverage distribution between robots and minimize the workload per
robot, meanwhile ensuring complete coverage of the area.Comment: In proceedings of IEEE/RSJ International Conference on Intelligent
Robots and Systems (IROS), 201
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