Minimum energy mobile wireless networks

Rodoplu, Volkan; Meng, Tao

doi:10.1109/icc.1998.683107

Cited by 494 publications

(650 citation statements)

References 5 publications

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“…Most of the previous research efforts [7,8] used constructions from the field of computational geometry with an overall objective of preserving energy-efficient paths. These implications have been disproved by latest findings that emphasize more on generating interference-minimal topology [9] [10].…”

Section: Related Workmentioning

confidence: 99%

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Mobility-Aware Distributed Topology Control for Mobile Multi-hop Wireless Networks

Mir

Shrestha

Cho

et al. 2006

Information Networking. Advances in Data Communications and Wireless Networks

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Abstract. In recent years mobile multi-hop wireless networks have received significant attention and one of the major research concerns in this area is topology control. While topology control problem in ad hoc networks is NP-complete, several heuristic and approximation based solutions have been presented. However, few efforts have focused on the issue of topology control with mobility. In this paper, we introduce a new topology control scheme in the presence of mobile nodes. The proposed scheme predicts future proximity of neighboring nodes and applies power control such that the network connectivity is maintained while reducing energy consumption. Simulation results show that the optimal power selection based on location prediction gives better performance in terms of energy and connectivity.

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Section: Related Workmentioning

confidence: 99%

“…In [8], each node in the network computes a strongly connected topology based on local neighborhood and channel propagation model information. Most of the previous research efforts [7,8] used constructions from the field of computational geometry with an overall objective of preserving energy-efficient paths.…”

Section: Related Workmentioning

confidence: 99%

Mobility-Aware Distributed Topology Control for Mobile Multi-hop Wireless Networks

Mir

Shrestha

Cho

et al. 2006

Information Networking. Advances in Data Communications and Wireless Networks

View full text Add to dashboard Cite

show abstract

“…Based on a path-loss model, nodes can locally determine to which neighbour they should forward the message to minimise the total energy consumption. The algorithm proposed in [6] is optimal but requires extensive assumptions, such as the availability of location information and a specific path-loss model.…”

Section: Introductionmentioning

confidence: 99%

“…[2] and the references therein). Rodoplu and Meng [6] present a distributed algorithm for this problem that is based on the concept of relay regions: each node is aware of its own geographic location and the location of its neighbours. Based on a path-loss model, nodes can locally determine to which neighbour they should forward the message to minimise the total energy consumption.…”

Section: Introductionmentioning

confidence: 99%

Distributed Computation of Maximum Lifetime Spanning Subgraphs in Sensor Networks

Haanpää¹,

Schumacher²,

Thaler³

et al. 2007

Mobile Ad-Hoc and Sensor Networks

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Abstract. We present a simple and efficient distributed method for determining the transmission power assignment that maximises the lifetime of a data-gathering wireless sensor network with stationary nodes and static power assignments. Our algorithm determines the transmission power level inducing the maximum-lifetime spanning subgraph of a network by means of a distributed breadth-first search for minmax-power communication paths, i.e. paths that connect a given reference node to each of the other nodes so that the maximum transmission power required on any link of the path is minimised. The performance of the resulting Maximum Lifetime Spanner (MLS) protocol is validated in a number of simulated networking scenarios. In particular, we study the performance of the protocol in terms of the number of required control messages, and compare it to the performance of a recently proposed Distributed Min-Max Tree (DMMT) algorithm. For all network scenarios we consider, MLS outperforms DMMT significantly. We also discuss bringing down the message complexity of our algorithm by initialising it with the Relative Neighbourhood Graph (RNG) of a transmission graph rather than the full graph, and present an efficient distributed method for reducing a given transmission graph to its RNG.

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“…There have been considerable efforts to solve the routing problem in wireless sensor networks [3], [5], [6], [10], [11], [12], [13], [14]. However, these protocols do not consider the heterogeneity of WSAN.…”

Section: Introductionmentioning

confidence: 99%

Real-Time Coordination and Routing in Wireless Sensor and Actor Networks

Shah

Bozyiğit

Akan

et al. 2006

Next Generation Teletraffic and Wired/Wireless Advanced Networking

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Abstract. In Wireless Sensor Actor Networks (WSAN), sensor nodes perform the sensing task and actor nodes take action based on the sensed phenomena in the field. To ensure efficient and accurate operations of WSAN, new communication protocols are imperative to provide sensoractor coordination in order to achieve energy-efficient and reliable communication. Moreover, the protocols must honor the application-specific real-time delay bounds for the effectiveness of the actors in WSAN.In this paper, we propose a new real-time coordination and routing (RCR) framework for WSAN. It addresses the issues of coordination among sensors and actors and honors the delay bound for routing in distributed manner. RCR configures sensors to form hierarchical clusters and provides delay-constrained energy aware routing (DEAR) mechanism. It uses only cluster-heads to coordinate with sink/actors in order to save the precious energy resources. The DEAR algorithm integrates the forwardtracking and backtracking routing approaches to establish paths from source nodes to sink/actors. In the presence of the sink in WSAN, it implements the centralized version of DEAR (C-DEAR) to coordinate with the actors through the sink. In the absence of sink or ignoring its presence, there is a distributed DEAR (D-DEAR) to provide coordination among sensors and actors. Cluster-heads then select the path among multiple alternative paths to deliver the packets to the actors within the given delay bound in an efficient way. Simulation experiments prove that RCR achieves the goal to honor the realistic application-specific delay bound.

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Minimum energy mobile wireless networks

Cited by 494 publications

References 5 publications

Mobility-Aware Distributed Topology Control for Mobile Multi-hop Wireless Networks

Mobility-Aware Distributed Topology Control for Mobile Multi-hop Wireless Networks

Distributed Computation of Maximum Lifetime Spanning Subgraphs in Sensor Networks

Real-Time Coordination and Routing in Wireless Sensor and Actor Networks

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