14,396 research outputs found
Architectural Considerations for a Self-Configuring Routing Scheme for Spontaneous Networks
Decoupling the permanent identifier of a node from the node's
topology-dependent address is a promising approach toward completely scalable
self-organizing networks. A group of proposals that have adopted such an
approach use the same structure to: address nodes, perform routing, and
implement location service. In this way, the consistency of the routing
protocol relies on the coherent sharing of the addressing space among all nodes
in the network. Such proposals use a logical tree-like structure where routes
in this space correspond to routes in the physical level. The advantage of
tree-like spaces is that it allows for simple address assignment and
management. Nevertheless, it has low route selection flexibility, which results
in low routing performance and poor resilience to failures. In this paper, we
propose to increase the number of paths using incomplete hypercubes. The design
of more complex structures, like multi-dimensional Cartesian spaces, improves
the resilience and routing performance due to the flexibility in route
selection. We present a framework for using hypercubes to implement indirect
routing. This framework allows to give a solution adapted to the dynamics of
the network, providing a proactive and reactive routing protocols, our major
contributions. We show that, contrary to traditional approaches, our proposal
supports more dynamic networks and is more robust to node failures
Distributed Service Discovery for Heterogeneous Wireless Sensor Networks
Service discovery in heterogeneous Wireless Sensor Networks is a challenging research objective, due to the inherent limitations of sensor nodes and their extensive and dense deployment. The protocols proposed for ad hoc networks are too heavy for sensor environments. This paper presents a resourceaware solution for the service discovery problem, which exploits the heterogeneous nature of the sensor network and alleviates the high-density problem from the flood-based approaches. The idea is to organize nodes into clusters, based on the available resources and the dynamics of nodes. The clusterhead nodes act as a distributed directory of service registrations. Service discovery messages are exchanged among the nodes in the distributed directory. The simulation results show the performance of the service discovery protocol in heterogeneous dense
environments
Improving Routing Efficiency through Intermediate Target Based Geographic Routing
The greedy strategy of geographical routing may cause the local minimum
problem when there is a hole in the routing area. It depends on other
strategies such as perimeter routing to find a detour path, which can be long
and result in inefficiency of the routing protocol. In this paper, we propose a
new approach called Intermediate Target based Geographic Routing (ITGR) to
solve the long detour path problem. The basic idea is to use previous
experience to determine the destination areas that are shaded by the holes. The
novelty of the approach is that a single forwarding path can be used to
determine a shaded area that may cover many destination nodes. We design an
efficient method for the source to find out whether a destination node belongs
to a shaded area. The source then selects an intermediate node as the tentative
target and greedily forwards packets to it, which in turn forwards the packet
to the final destination by greedy routing. ITGR can combine multiple shaded
areas to improve the efficiency of representation and routing. We perform
simulations and demonstrate that ITGR significantly reduces the routing path
length, compared with existing geographic routing protocols
Graphical model-based approaches to target tracking in sensor networks: an overview of some recent work and challenges
Sensor Networks have provided a technology base for distributed target tracking applications among others. Conventional centralized approaches to the problem lack scalability in such a scenario where a large number of sensors provide measurements simultaneously under a possibly non-collaborating environment. Therefore research efforts have focused on scalable, robust, and distributed algorithms for the inference tasks related to target tracking, i.e. localization, data association, and track maintenance. Graphical models provide a rigorous tool for development of such algorithms by modeling the information structure of a given task and providing distributed solutions through message passing algorithms. However, the limited communication capabilities and energy resources of sensor networks pose the additional difculty of considering the tradeoff between the communication cost and the accuracy of the result. Also the network structure and the information structure are different aspects of the problem and a mapping between the physical entities and the information structure is needed. In this paper we discuss available formalisms based on graphical models for target tracking in sensor networks with a focus on the aforementioned issues. We point out additional constraints that must be asserted in order to achieve further insight and more effective solutions
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