Data MULEs: modeling and analysis of a three-tier architecture for sparse sensor networks

By Rahul C. Shah, Sumit Kumar Roy, Sushant Jain, Waylon Brunette. Ad hoc networks, 2003

805 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/d485817e4199bc1cf27ac971b209795f27f54d87

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Citations in the corpus

DV-CAST: A distributed vehicular broadcast protocol for vehicular ad hoc networks (2010, background): “Data mules are proposed to function as mobile messengers that collect data from sensors and deliver to a virtual backbone in sensor networks [1].”
Routing in Sparse Vehicular Ad Hoc Wireless Networks (2007, background): “A number of routing protocols specifically designed to cope with routing in sparsely connected Mobile Ad hoc Networks that fall into the generic framework of Delay Tolerant Networks are as follows: DataMules [16] are mobile messengers which promote the network connectivity in a sensor network by pro”
Mobile Edge Computing via a UAV-Mounted Cloudlet: Optimization of Bit Allocation and Path Planning (2016, unknown): “J. Kang is with the Department of Electrical Engineering, Korea Advanced Institute of Science and Technology (KAIST), 291, Daehak-ro, Yuseong-gu, Daejeon 34141, Korea (e-mail: jhkang@ee.kaist.ac.kr).”
Efficient Routing in Intermittently Connected Mobile Networks: The Multiple-Copy Case (2008, background): “Without this number spraying performance could be as bad as that of Direct Transmissions or Epidemic routing in different scenarios.”
Robots for Environmental Monitoring: Significant Advancements and Applications (2012, methodology): “Different types of searching algorithms have been proposed to address this task: some following an estimated gradient [74], others biologically inspired [75], and others adapting methods of stochastic search, such as particle swarm optimization [76].”
Modeling Time-Variant User Mobility in Wireless Mobile Networks (2007, background): “…on mobility assisted-routing in the literature assume either a complete knowledge of future mobility and encounters[2] or an i.i.d. mobility pattern[7] with each individual node following simple mobility models, such as a random walk[3], [4], [5], mainly for the sake of theoretical tractability.”
Performance analysis of mobility-assisted routing (2006, methodology): “The random walk model is, to the best of our knowledge, the only exception [30, 35, 36].”
Single-copy routing in intermittently connected mobile networks (2004, background): “In [16] a number of mobile nodes, modeled as performing independent random walks, serve as DataMules that carry data from static sensors to base stations, in a sparse sensor network.”
An Energy-Efficient Mobile-Sink Path Selection Strategy for Wireless Sensor Networks (2014, background): “An example is the use of animals as mobile-sink nodes to assist in data collection from sensor nodes scattered on a large farm [16].”
Wireless sensor networks: applications and challenges of ubiquitous sensing (2005, background): “An interesting solution is the use of ubiquitous mobile agents that randomly move around to gather data bridging sensor nodes and access points, whimsically named data MULEs (Mobile Ubiquitous LAN Extensions) in [ C28 ].”
Spray and Focus: Efficient Mobility-Assisted Routing for Heterogeneous and Correlated Mobility (2007, background): “On the other hand, routing schemes that only route one copy per message to considerably reduce resource waste (these are called " single-copy " schemes [15], [16]), can often be orders of magnitude slower and are inherently less reliable.”
Knowledge-based opportunistic forwarding in vehicular wireless ad hoc networks (2005, methodology): “NOTALK is similar to the strategy used in the Data Mule project [4].”