Bounding the lifetime of sensor networks via optimal role assignments

By Manish Bhardwaj, Anantha P. Chandrakasan. Proceedings.Twenty-First Annual Joint Conference of the IEEE Computer and Communications Societies, 2002

593 citations recorded by the source corpus.

Subfields: Computer Networks and Communications

View Paper: https://www.semanticscholar.org/paper/f50c49ea600242a8484407cd8b1ac92fedc59e87

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In Computer Networks and Communications

Citations in the corpus

On the lifetime of wireless sensor networks (2009, background): “1) the time until the first sensor is drained of its energy [11]–[13], [15], [36], [42]–[44] 2) the time until the first cluster head is drained of its energy [18], [19] 3) the time there is at least a certain fraction β of surviving nodes in the network [16], [17], [42], [45]–[47] 4) the time until”
On the lifetime of wireless sensor networks (2005, background): “Summing (2) up over the M trials and dividing both sides by M , we obtain”
Topology control for wireless sensor networks (2003, background): “In [ 23 ], they further explicitly formulated the optimal role assignment as the maximal network flow problem, again in data harvest networks for which the BS is presumably being located already.”
Network coverage using low duty-cycled sensors: random & coordinated sleep algorithms (2004, methodology): “The following energy model from [14] is adopted.”
Joint mobility and routing for lifetime elongation in wireless sensor networks (2005, background): “We define the network lifetime as the time span from the sensor deployment to the first loss of coverage [20] (i.”
Design guidelines for wireless sensor networks: communication, clustering and aggregation (2004, background): “In [9], the authors provide bounds on the lifetime of a sensor network over all the collaborative data gathering strategies.”
Sensor deployment and target localization in distributed sensor networks (2004, methodology): “Since the energy consumption in DSNs increases signi.cantly during periods of activity, which may be triggered, for example, by a moving target [Bhardwaj and Chandrakasan 2002], we propose an energy-conserving method for target localization in cluster-based DSNs.”
Exploiting Mobility for Energy Efficient Data Collection in Wireless Sensor Networks (2006, background): “Optimizing for network life is much harder as it requires use of multi-path routing to eliminate hotspots [16] [22] [23].”
Optimal energy management policies for energy harvesting sensor nodes (2008, background): “Thus, the life time of a network is an important characteristic of a sensor network ([1]) and it is tied up with the life time of a node.”
A Survey of Network Lifetime Maximization Techniques in Wireless Sensor Networks (2017, background): “…optimal node placement solution subject to striking a trade-off between the total power dissipation and the NL. Additionally, Bhardwaj et al. [23], [24] focused their attention on the fundamental constraints of the information gathering and transmission to a base station, while deriving the upper…”
Analytical modeling and mitigation techniques for the energy hole problem in sensor networks (2007, background): “Some efforts have been directed to the fundamental lifetime limits in sensor networks [4], [5], [6], [7].”
Group Role Assignment via a Kuhn–Munkres Algorithm-Based Solution (2012, background): “Some related researches concern agent systems [10], [19], [21], [24]–[26], Web services [18], access control [1], [2], and sensor networks [5] concentrating on their special aspects.”
On maximum lifetime routing in Wireless Sensor Networks (2009, background): “, [4] define the network lifetime as the time until the first node depletes its battery, it may just as well be defined as the time until the data source cannot reach the data sink [5].”