9,157 research outputs found
Metric Dimension for Gabriel Unit Disk Graphs is NP-Complete
We show that finding a minimal number of landmark nodes for a unique virtual
addressing by hop-distances in wireless ad-hoc sensor networks is NP-complete
even if the networks are unit disk graphs that contain only Gabriel edges. This
problem is equivalent to Metric Dimension for Gabriel unit disk graphs. The
Gabriel edges of a unit disc graph induce a planar O(\sqrt{n}) distance and an
optimal energy spanner. This is one of the most interesting restrictions of
Metric Dimension in the context of wireless multi-hop networks.Comment: A brief announcement of this result has been published in the
proceedings of ALGOSENSORS 201
Supporting Cyber-Physical Systems with Wireless Sensor Networks: An Outlook of Software and Services
Sensing, communication, computation and control technologies are the essential building blocks of a cyber-physical system (CPS). Wireless sensor networks (WSNs) are a way to support CPS as they provide fine-grained spatial-temporal sensing, communication and computation at a low premium of cost and power. In this article, we explore the fundamental concepts guiding the design and implementation of WSNs. We report the latest developments in WSN software and services for meeting existing requirements and newer demands; particularly in the areas of: operating system, simulator and emulator, programming abstraction, virtualization, IP-based communication and security, time and location, and network monitoring and management. We also reflect on the ongoing
efforts in providing dependable assurances for WSN-driven CPS. Finally, we report on its applicability with a case-study on smart buildings
SimpleTrack:Adaptive Trajectory Compression with Deterministic Projection Matrix for Mobile Sensor Networks
Some mobile sensor network applications require the sensor nodes to transfer
their trajectories to a data sink. This paper proposes an adaptive trajectory
(lossy) compression algorithm based on compressive sensing. The algorithm has
two innovative elements. First, we propose a method to compute a deterministic
projection matrix from a learnt dictionary. Second, we propose a method for the
mobile nodes to adaptively predict the number of projections needed based on
the speed of the mobile nodes. Extensive evaluation of the proposed algorithm
using 6 datasets shows that our proposed algorithm can achieve sub-metre
accuracy. In addition, our method of computing projection matrices outperforms
two existing methods. Finally, comparison of our algorithm against a
state-of-the-art trajectory compression algorithm show that our algorithm can
reduce the error by 10-60 cm for the same compression ratio
Energy efficient routing towards a mobile sink using virtual coordinates in a wireless sensor network
The existence of a coordinate system can often improve the routing in a wireless sensor network. While most coordinate systems correspond to the geometrical or geographical coordinates, in recent years researchers had proposed the use of virtual coordinates. Virtual coordinates depend only on the topology of the network as defined by the connectivity of the nodes, without requiring geographical information. The work in this thesis extends the use of virtual coordinates to scenarios where the wireless sensor network has a mobile sink. One reason to use a mobile sink is to distribute the energy consumption more evenly among the sensor nodes and thus extend the life-time of the network. We developed two algorithms, MS-DVCR and CU-DVCR which perform routing towards a mobile sink using virtual coordinates. In contrast to the baseline virtual coordinate routing MS-DVCR limits routing updates triggered by the sink movement to a local area around the sink. In contrast, CU-DVCR limits the route updates to a circular area on the boundary of the local area. We describe the design justification and the implementation of these algorithms. Using a set of experimental studies, we show that MS-DVCR and CU-DVCR achieve a lower energy consumption compared to the baseline virtual coordinate routing without any noticeable impact on routing performance. In addition, CU-DVCR provides a lower energy consumption than MS-DVCR for the case of a fast moving sink
Reducing Congestion Effects by Multipath Routing in Wireless Networks
We propose a solution to improve fairness and increasethroughput in wireless networks with location information.Our approach consists of a multipath routing protocol, BiasedGeographical Routing (BGR), and two congestion controlalgorithms, In-Network Packet Scatter (IPS) and End-to-EndPacket Scatter (EPS), which leverage BGR to avoid the congestedareas of the network. BGR achieves good performancewhile incurring a communication overhead of just 1 byte perdata packet, and has a computational complexity similar togreedy geographic routing. IPS alleviates transient congestion bysplitting traffic immediately before the congested areas. In contrast,EPS alleviates long term congestion by splitting the flow atthe source, and performing rate control. EPS selects the pathsdynamically, and uses a less aggressive congestion controlmechanism on non-greedy paths to improve energy efficiency.Simulation and experimental results show that our solutionachieves its objectives. Extensive ns-2 simulations show that oursolution improves both fairness and throughput as compared tosingle path greedy routing. Our solution reduces the variance ofthroughput across all flows by 35%, reduction which is mainlyachieved by increasing throughput of long-range flows witharound 70%. Furthermore, overall network throughput increasesby approximately 10%. Experimental results on a 50-node testbed are consistent with our simulation results, suggestingthat BGR is effective in practice
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