2024-03-28T11:49:14Zhttps://deepblue.lib.umich.edu/dspace-oai/requestoai:deepblue.lib.umich.edu:2027.42/458362021-10-05T22:04:25Zcom_2027.42_13913col_2027.42_21621col_2027.42_142370
Finite approximations to a zero-sum game with incomplete information
Mamer, John W.
Schilling, Kenneth E.
Department of Mathematics, University of Michigan-Flint, USA
Anderson Graduate School of Management, University of California, Los Angeles
Flint
In this paper, we investigate a scheme for approximating a two-person zero-sum game G of incomplete information by means of a natural system G mn of its finite subgames. The main question is: For large m and n , is an optimal strategy for G mn necessarily an ε -optimal strategy for G ?
2006-09-11T16:31:39Z
2006-09-11T16:31:39Z
1990-03
Article
Mamer, J. W.; Schilling, K. E.; (1990). "Finite approximations to a zero-sum game with incomplete information." International Journal of Game Theory 19(1): 101-106. <http://hdl.handle.net/2027.42/45836>
1432-1270
0020-7276
https://hdl.handle.net/2027.42/45836
http://dx.doi.org/10.1007/BF01753710
International Journal of Game Theory
en_US
Physica-Verlag; Springer Science+Business Media
oai:deepblue.lib.umich.edu:2027.42/285772019-03-18T18:26:19Zcom_2027.42_13913col_2027.42_21621col_2027.42_142370
The growth of m-constraint random knapsacks
Schilling, Kenneth E.
Department of Mathematics, University of Michigan - Flint, Flint, MI 48503, USA
The author computes the asymptotic value of a particular m-constraint, n-variable 0-1 random integer programming problem as n increases, m remaining fixed. This solves a problem of Frieze and Clarke (1984).
2006-04-10T13:44:18Z
2006-04-10T13:44:18Z
1990-05-04
Article
Schilling, Kenneth E. (1990/05/04)."The growth of m-constraint random knapsacks." European Journal of Operational Research 46(1): 109-112. <http://hdl.handle.net/2027.42/28577>
http://www.sciencedirect.com/science/article/B6VCT-48VW7K9-BV/2/ef30413ea29587ed133133a9dc035244
http://hdl.handle.net/2027.42/28577
http://dx.doi.org/10.1016/0377-2217(90)90303-S
European Journal of Operational Research
en_US
IndexNoFollow
Elsevier
oai:deepblue.lib.umich.edu:2027.42/702552023-07-18T13:04:58Zcom_2027.42_13913col_2027.42_142370col_2027.42_21621
Low‐temperature conductivity of epitaxial ZnSe in the impurity band regime
Vaziri, M.
Department of Physics & Engineering Science, The University of Michigan–Flint, Flint, Michigan 48502
Low‐temperature conductivity of several samples of ZnSe grown by molecular‐beam epitaxy has been measured. The data indicate that for samples with carrier concentration below or near Nc, metal insulator transition, the conductivity obeys σ=σ0 exp[−(T0/T)s] at low temperatures with s=1/2. This behavior is a characteristic of variable‐range hopping conduction in the presence of a Coulomb gap. © 1994 American Institute of Physics.
2010-05-06T21:52:31Z
2010-05-06T21:52:31Z
1994-11-14
Article
Vaziri, M. (1994). "Low‐temperature conductivity of epitaxial ZnSe in the impurity band regime." Applied Physics Letters 65(20): 2568-2570. <http://hdl.handle.net/2027.42/70255>
https://hdl.handle.net/2027.42/70255
10.1063/1.112641
Applied Physics Letters
N. F. Mott, J. Non-Cryst. Solids 1, 1 (1968).
A. L. Efros and B. I. Shklovskii, J. Phys. C 8, L49 (1975).
A. L. Afros and B. I. Shklovskii, in Electron-Electron Interactions in Disordered System, edited by A. L. Afros and M. Pollak (North-Holland, Amsterdam, 1985), p. 435.
B. I. Shklovskii and A. L. Efros, in Electronic Properties of Doped Semiconductors, edited by M. Cardona (Springer, Berlin, 1984), p. 208.
Reference 4, p. 81.
T. Marshall and J. Gaines, Appl. Phys. Lett. 56, 2669 (1990).
M. Vaziri, R. Reifenbeger, R. L. Gunshor, L. A. Kolodziejski, S. Venkatesan, and R. F. Pierret, J. Vac. Sci. Technol. B 7, 253 (1989).
H. E. Ruda, J. Appl. Phys. 59, 1220 (1986).
D. Walsh, K. Mazuruk, M. Benzaquen, and P. Weissfloch, Semicond. Sci. Technol. 3, 116 (1988).
F. Tremblay, M. Pepper, D. Ritchie, D. C. Peacock, J. E. F. Frost, and G. A. Jones, Phys. Rev. B 39, 8059 (1989).
Y. Zhang, P. Dai, M. Levy, and M. P. Sarachik, Phys. Rev. Lett. 64, 2687 (1990).
© The American Institute of Physics
The American Institute of Physics
oai:deepblue.lib.umich.edu:2027.42/284092019-03-18T18:24:02Zcom_2027.42_13913col_2027.42_21621col_2027.42_142370
On the growth of random knapsacks
Mamer, John W.
Schilling, Kenneth E.
Department of Mathematics, University of Michigan, Flint, MI, USA
Anderson Graduate School of Management, University of California, Los Angeles, CA, USA
We consider the problem of optimally filling a knapsack of fixed capacity by choosing from among a collection of n objects of randomly determined weight and value. Under very mild conditions on the common joint distribution of weight and value, we determine the asymptotic value of the optimal knapsack, for large n.
2006-04-10T13:37:37Z
2006-04-10T13:37:37Z
1990-09
Article
Mamer, John W., Schilling, Kenneth E. (1990/09)."On the growth of random knapsacks." Discrete Applied Mathematics 28(3): 223-230. <http://hdl.handle.net/2027.42/28409>
http://www.sciencedirect.com/science/article/B6TYW-45D9TGG-M/2/eaf5d2a049a235d7838b1790f5d0c4b7
http://hdl.handle.net/2027.42/28409
http://dx.doi.org/10.1016/0166-218X(90)90004-V
Discrete Applied Mathematics
en_US
IndexNoFollow
Elsevier
oai:deepblue.lib.umich.edu:2027.42/315512019-03-18T18:58:51Zcom_2027.42_13913col_2027.42_21621col_2027.42_142370
Local limiting behavior of the zeros of approximating polynomials
Simkani, M.
The University of Michigan-Flint, Department of Mathematics, Flint, MI 48502-2186, USA
Let f be a piecewise analytic (but not analytic) function in Ck[a, b], k [ges] 0, and let p*n be the sequence of polynomials of best uniform approximation to f on [a, b]. It is well known that every point of [a, b] is a limit point of the zeros of the p*n. Let xgE [a, b], and suppose that f is analytic at x and f(x) [not equal to] 0. The main purpose of this paper is to show that there exists a constant [gamma] (which depends only on x) such that there is no zero of p*n within the circle of radius ([gamma]/n) log n centered at x, for all sufficiently large values of n.
2006-04-10T18:07:22Z
2006-04-10T18:07:22Z
1994-06
Article
Simkani, M. (1994/06)."Local limiting behavior of the zeros of approximating polynomials." Applied Numerical Mathematics 14(4): 451-456. <http://hdl.handle.net/2027.42/31551>
http://www.sciencedirect.com/science/article/B6TYD-45DHS45-9/2/0139f0d221ab4979eccc4a3ca627f9db
http://hdl.handle.net/2027.42/31551
http://dx.doi.org/10.1016/0168-9274(94)00005-0
Applied Numerical Mathematics
en_US
IndexNoFollow
Elsevier
oai:deepblue.lib.umich.edu:2027.42/1116432023-07-18T12:56:05Zcom_2027.42_13913col_2027.42_142370col_2027.42_21621
Secure Data Collection in Constrained Tree-Based Smart Grid Environments
Uludag, Suleyman
Jin, Haiming
Lui, King-Shan
Nahrstedt, Klara
CSEP, UM-Flint
Department of Electrical and Electronic Engineering, The University of Hong Kong
Department of Computer Science, University of Illinois at Urbana-Champaign, IL, USA
Flint
approximation theory;computational complexity;integer programming;linear programming;power system measurement;power system security;smart power grids;trees (mathematics);NP-hard problem;approximation algorithm;communication protocol;integer linear programming problem;multiple measurement devices;secure data collection;tree-based smart grid environments;Approximation algorithms;Approximation methods;Cryptography;DH-HEMTs;Data collection;Topology
To facilitate more efficient control, massive amounts of sensors or measurement devices will be deployed in the Smart Grid. Data collection then becomes non-trivial. In this paper, we study the scenario where a data collector is responsible for collecting data from multiple measurement devices, but only some of them can communicate with the data collector directly. Others have to rely on other devices to relay the data. We first develop a communication protocol so that the data reported by each device is protected again honest-but-curious data collector and devices. To reduce the time to collect data from all devices within a certain security level, we formulate our approach as an integer linear programming problem. As the problem is NP-hard, obtaining the optimal solution in a large network is not very feasible. We thus develop an approximation algorithm to solve the problem. We test the performance of our algorithm using real topologies. The results show that our algorithm successfully identifies good solutions within reasonable amount of time.
2015-05-18T06:36:20Z
2015-05-18T06:36:20Z
2014-11
Article
https://hdl.handle.net/2027.42/111643
IEEE International Conference on Smart Grid Communications (SmartGridComm 2014)
orcid.org/0000-0002-7207-6683
Uludag, Suleyman; 0000-0002-7207-6683
en_US
IEEE
oai:deepblue.lib.umich.edu:2027.42/924332023-07-18T13:02:40Zcom_2027.42_13913col_2027.42_142370
A taxonomy and evaluation for developing 802.11‐based wireless mesh network testbeds
Uludag, Suleyman
Imboden, Tom
Akkaya, Kemal
2012-08-09T14:56:39Z
2013-10-01T17:06:32Z
2012-08
Article
Uludag, Suleyman; Imboden, Tom; Akkaya, Kemal (2012). "A taxonomy and evaluation for developing 802.11‐based wireless mesh network testbeds." International Journal of Communication Systems 25(8): 963-990. <http://hdl.handle.net/2027.42/92433>
1074-5351
1099-1131
https://hdl.handle.net/2027.42/92433
10.1002/dac.1299
International Journal of Communication Systems
Amir Y, Danilov C, Musaloiu‐Elefteri R, Rivera N. The smesh wireless mesh network. Technical Memorandum CNDS‐2009‐3, Johns Hopkins University, Boeing Phantom Works, April 2009.
Robinson J, Papagiannaki K, Diot C, Guo X, Krishnamurthy L. Experimenting with a multi‐radio mesh networking testbed. Proceedings of the First Workshop on Wireless Network Measurements (WiNMee 2005), Trentino, Italy, 2005. (Available from: http://www.winmee.org/2005/papers/WiNMee_Robinson.pdf ) [accessed on February 20, 2011].
Shrivastava V, Rayanchu S, Yoonj J, Banerjee S. 802.11n under the microscope. In IMC '08: Proceedings of the 8th ACM SIGCOMM conference on Internet measurement. ACM: New York, NY, USA, 2008; 105 – 110. DOI: 10.1145/1452520.1452533.
Pelechrinis K, Broustis I, Salonidis T, Krishnamurthy SV, Mohapatra P. Design and deployment considerations for high performance mimo testbeds. In WICON '08: Proceedings of the 4th Annual International Conference on Wireless Internet. ICST (Institute for Computer Sciences, Social‐Informatics and Telecommunications Engineering): ICST, Brussels, Belgium, Belgium, 2008; 1 – 9.
Ramachandran K, Belding‐Royer E, AImeroth K. Damon: a distributed architecture for monitoring multi‐hop mobile networks. Sensor and Ad Hoc Communications and Networks, 2004. IEEE SECON 2004. 2004 First Annual IEEE Communications Society Conference on, 2004; 601 – 609. DOI: 10.1109/SAHCN.2004.1381963.
Capone A, Cesana M, Napoli S, Pollastro A. Mobimesh: a complete solution for wireless mesh networking. Mobile Adhoc and Sensor Systems, 2007. MASS 2007. IEEE Internatonal Conference on, 2007; 1 – 3. DOI: 10.1109/MOBHOC.2007.4428698.
Riggio R, Scalabrino N, Miorandi D, Chlamtac I. Janus: A framework for distributed management of wireless mesh networks. Testbeds and Research Infrastructure for the Development of Networks and Communities, 2007. TridentCom 2007. 3rd International Conference on, 2007; 1 – 7. DOI: 10.1109/TRIDENTCOM.2007.4444703.
Aseeja V, Zheng R. Meshman: A management framework for wireless mesh networks. Integrated Network Management, 2009. IM '09. IFIP/IEEE International Symposium on, 2009; 226 – 233. DOI: 10.1109/INM.2009.5188814.
Duarte J, Passos D, Valle R, Oliveira E, Muchaluat‐Saade D, Albuquerque C. Management issues on wireless mesh networks. Network Operations and Management Symposium, 2007. LANOMS 2007. Latin American, 2007; 8 – 19. DOI: 10.1109/LANOMS.2007.4362455.
Judd G, Steenkiste P. Repeatable and realistic wireless experimentation through physical emulation. SIGCOMM Comput. Commun. Rev. January 2004; 34: 63 – 68. DOI: 10.1145/972374.972386.
Bialkowski K, Portmann M. Design of testbed for wireless mesh networks. Antennas and Propagation Society International Symposium (APSURSI), 2010 IEEE, 2010; 1 – 4. DOI: 10.1109/APS.2010.5562247.
Kiess W, Tarp A, Mauve M. On the Topological Repeatability of Experiments with Wireless Multihop Networks. MSWiM 2008: Proceedings of the 11th ACM/IEEE International Conference on Modeling, Analysis and Simulation of Wireless and Mobile Systems, 2008.
De P, Raniwala A, Sharma S, Chiueh T. Design considerations for a multihop wireless network testbed. Communications Magazine, IEEE oct 2005; 43 ( 10 ): 102 – 109. DOI: 10.1109/MCOM.2005.1522132.
Burchfield R, Nourbakhsh E, Dix J, Sahu K, Venkatesan S, Prakash R. Rf in the jungle: Effect of environment assumptions on wireless experiment repeatability. Communications, 2009. ICC '09. IEEE International Conference on, 2009; 1 – 6. DOI: 10.1109/ICC.2009.5199421.
Tcpdump/libpcap public repository. (Available from: http://www.tcpdump.org ) [accessed on February 20, 2011].
Wireshark. (Available from: http://www.wireshark.org ) [accessed on February 20, 2011].
De P, Raniwala A, Sharma S, Chiueh T. Mint: a miniaturized network testbed for mobile wireless research. In INFOCOM 2005, Vol. 4, 2005; 2731 – 2742. DOI: 10.1109/INFCOM.2005.1498556.
Crossbow Mica Motes. (Available from: http://www.xbow.com ) [accessed on February 20, 2011].
Levis P, Lee N, Welsh M, Culler D. Tossim: accurate and scalable simulation of entire tinyos applications. In Proceedings of the 1st international conference on Embedded networked sensor systems, SenSys '03. ACM: New York, NY, USA, 2003; 126 – 137.
Kawadia V, Kumar P. A cautionary perspective on cross‐layer design. Wireless Communications, IEEE Feb 2005; 12 ( 1 ): 3 – 11. DOI: 10.1109/MWC.2005.1404568.
Bruno R, Conti M, Gregori E. Mesh networks: commodity multihop ad hoc networks. Communications Magazine, IEEE March 2005; 43 ( 3 ): 123 – 131. DOI: 10.1109/MCOM.2005.1404606.
Akyildiz I, Wang X. A survey on wireless mesh networks. Communications Magazine, IEEE Sept 2005; 43 ( 9 ): S23 – S30. DOI: 10.1109/MCOM.2005.1509968.
Hossain E, Leung KK (eds). Wireless Mesh Networks: Architectures and Protocols. Springer‐Verlag New York, Inc.: Secaucus, NJ, USA, 2010.
Zhang Y, Luo J, Hu H (eds). Wireless Mesh Networks: Architectures, Protocols and Standards. Auerbach Publications: Boca Raton, FL, 2007.
Misra S, Misra SC, Woungang I. Guide to Wireless Mesh Networks. Springer Publishing Company, Incorporated, 2009.
Akyildiz I, Wang X. Wireless Mesh Networks (Advanced Texts in Communications and Networking). John Wiley & Sons: West Sussex, UK, 2009.
Methley S. Essentials of Wireless Mesh Networks. Cambridge University Press: Cambridge, UK, 2009.
Aggelou G. Wireless Mesh Networking. McGraw‐Hill Professional: Portland, OR, 2008.
The Network Simulator NS‐2. (Available from: http://www.isi.edu/nsnam/ns/ ) [accessed on February 20, 2011].
The ns‐3 network simulator2. (Available from: http://www.nsnam.org/ ) [accessed on February 20, 2011].
Qualnet Simulator. (Available from: www.scalable‐networks.com ) [accessed on February 20, 2011].
Zeng X, Bagrodia R, Gerla M. Glomosim: A library for parallel simulation of large‐scale wireless networks. Workshop on Parallel and Distributed Simulation, 1998.
OPNET Simulator. (Available from: http://www.opnet.com ) [accessed on February 20, 2011].
Sobeih A, Hou JC. Simulation framework for sensor networks in jsim. Technical Report UIUCDCS‐R‐2003‐2386, Nov. 2003.
Newport C, Kotz D, Yuan Y, Gray RS, Liu J, Elliott C. Experimental evaluation of wireless simulation assumptions. SIMULATION: Transactions of The Society for Modeling and Simulation International September 2007; 83 ( 9 ): 643 – 661.
Kashyap A, Ganguly S, Das SR. Measurement‐based approaches for accurate simulation of 802.11‐based wireless networks. In Proceedings of the 11th International Symposium on Modeling, Analysis and Simulation of Wireless and Mobile Systems, MSWiM '08. ACM: New York, NY, USA, 2008; 54 – 59. DOI: 10.1145/1454503.1454516.
Kashyap A. Measurement‐based modeling of interference in wi‐fi networks: techniques and applications. PhD Thesis, Stony Brook, NY, USA, 2008. AAI3386251.
Stojmenovic I. Simulations in wireless sensor and ad hoc networks: matching and advancing models, metrics, and solutions. Communications Magazine, IEEE December 2008; 46 ( 12 ): 102 – 107. DOI: 10.1109/MCOM.2008.4689215.
Ben Hamida E, Chelius G, Gorce JM. Impact of the Physical Layer Modeling on the Accuracy and Scalability of Wireless Network Simulation. Simulation 09 2009; 85: 574 – 588. DOI: 10.1177/0037549709106633.
Güneş M, Wenig M, Zimmermann A. Realistic mobility and propagation framework for manet simulations. In NETWORKING 2007. Ad Hoc and Sensor Networks, Wireless Networks, Next Generation Internet, Lecture Notes in Computer Science, Vol. 4479, Akyildiz I, Sivakumar R, Ekici E, Oliveira J, McNair J (eds). Springer Berlin: Heidelberg, 2007; 97 – 107.
Durmaz Incel O, Jansen P. Characterization of multi‐channel interference. Modeling and Optimization in Mobile, Ad Hoc, and Wireless Networks and Workshops, 2008. WiOPT 2008. 6th International Symposium on, 2008; 429 – 435. DOI: 10.1109/WIOPT.2008.4586102.
Herms A, Lukas G, Ivanov S. Realism in design and evaluation of wireless routing protocols. Proceedings of First International Workshop on Mobile Services and Personalized Environments (MSPE06), 2006.
Takai M, Martin J, Bagrodia R. Effects of wireless physical layer modeling in mobile ad hoc networks. In Proceedings of the 2nd ACM international symposium on Mobile ad hoc networking & computing, MobiHoc '01. ACM: New York, NY, USA, 2001; 87 – 94, DOI: 10.1145/501426.501429.
Conti M, Giordano S. Multihop ad hoc networking: The theory. Communications Magazine, IEEE April 2007; 45 ( 4 ): 78 – 86. DOI: 10.1109/MCOM.2007.343616.
Tropos networks. (Available from: http://www.tropos.com ) [accessed on February 20, 2011].
Open‐mesh. (Available from: http://www.open‐mesh.com ) [accessed on February 20, 2011].
Gupta P, Kumar PR. The capacity of wireless networks. IEEE Transactions on Information Theory 2000; 46 ( 2 ): 388 – 404.
Li J, Blake C, De Couto DS, Lee HI, Morris R. Capacity of ad hoc wireless networks. In Proceedings of the 7th Annual International Conference on Mobile Computing and Networking, MobiCom '01. ACM: New York, NY, USA, 2001; 61 – 69. DOI: 10.1145/381677.381684.
Public Safety Statement of Requirements (SoR). April 2006. (Available from: http://www.safecomprogram.gov/ ) [accessed on February 20, 2011].
Miller LE. NIST Wireless Communication Technologies Group, Public Safety Comunications Bibliography accessed 2008. (Available from: http://w3.antd.nist.gov/wctg/manet/safetybib.html ) [accessed on February 20, 2011].
Portmann M, Pirzada AA. Wireless mesh networks for public safety and crisis management applications. IEEE Internet Computing 2008; 12 ( 1 ): 18 – 25. DOI: 10.1109/MIC.2008.25.
Balachandran K, Budka KC, Chu TP, Doumi TL, Kang JH. Mobile responder communication networks for public safety. Communications Magazine, IEEE Jan 2006; 44 ( 1 ): 56 – 64. DOI: 10.1109/MCOM.2006.1580933.
RoofNet B. Berlin roofnet ‐ sarwiki. (Available from: http://sarwiki.informatik.hu‐berlin.de/BerlinRoofNet ) [accessed on February 20, 2011].
FCC Second Report and Order and Further Notice of Proposed Rulemaking in the matter of the 4.9 GHz Band Transferred from Federal Use. (Available from: http://wireless.fcc.gov/releases/fcc0247.pdf ) [accessed on February 20, 2011].
Flickenger R. Building Wireless Community Community Networks. O'Reilly & Associates, Inc: Sebastopol, CA, USA, 2003.
Biswas S, Tatchikou R, Dion F. Vehicle‐to‐vehicle wireless communication protocols for enhancing highway traffic safety. Communications Magazine, IEEE Jan 2006; 44 ( 1 ): 74 – 82. DOI: 10.1109/MCOM.2006.1580935.
The zigbee alliance. (Available from: http://www.zigbee.org/ ) [accessed on February 20, 2011].
The wimax forum. (Available from: http://www.wimaxforum.org/ ) [accessed on February 20, 2011].
Scalabrino N, De Pellegrini F, Riggio R, Maestrini A, Costa C, Chlamtac I. Measuring the quality of voip traffic on a wimax testbed. Testbeds and Research Infrastructure for the Development of Networks and Communities, 2007. TridentCom 2007. 3rd International Conference on, 2007; 1 – 10. DOI: 10.1109/TRIDENTCOM.2007.4444719.
Mignanti S, Castellano M, Spada M, Simoes P, Tamea G, Cimmino A, Neves PM, Marchetti I, Andreotti F, Landi G, et al. Weird testbeds with fixed and mobile wimax technology for user applications, telemedicine and monitoring of impervious areas. In Proceedings of the 4th International Conference on Testbeds and research infrastructures for the development of networks & communities, TridentCom '08. ICST (Institute for Computer Sciences, Social‐Informatics and Telecommunications Engineering): ICST, Brussels, Belgium, Belgium, 2008; 18:1 – 18:10. (Available from: http://portal.acm.org/citation.cfm?id=1390576.1390598 ) [accessed on February 20, 2011].
Westall J, Martin J. Performance characteristics of an operational wimax network. Mobile Computing, IEEE Transactions on December 2010; PP ( 99 ): 1. DOI: 10.1109/TMC.2010.226.
The status of IEEE 802.11s standard. (Available from: http://grouper.ieee.org/groups/802/11/Reports/tgs_update.htm ) [accessed on February 20, 2011].
Wang X, Lim AO. Ieee 802.11s wireless mesh networks: Framework and challenges. Ad Hoc Networks 2008; 6 ( 6 ): 970 – 984. DOI: 10.1016/j.adhoc.2007.09.003.
Lin Y‐D, Tsao S‐L, Chang S‐L, Cheng S‐Y, Ku C‐Y. Design issues experimental studies of wireless lan mesh. Wireless Communications, IEEE April 2010; 17 ( 2 ): 32 – 40. DOI: 10.1109/MWC.2010.5450658.
Camp J, Knightly E. The ieee 802.11s extended service set mesh networking standard. Communications Magazine, IEEE August 2008; 46 ( 8 ): 120 – 126. DOI: 10.1109/MCOM.2008.4597114.
Garroppo RG, Giordano S, Tavanti L. Implementation frameworks for ieee 802.11s systems. Computer Communications 2010; 33 ( 3 ): 336 – 349. DOI: 10.1016/j.comcom.2009.10.001. (Available form: http://www.sciencedirect.com/science/article/B6TYP‐4XFGJCS‐2/2/7a5080efe52a20994131b4c7232368e2 ) [accessed on February 20, 2011].
Bahr M. Update on the Hybrid Wireless Mesh Protocol of IEEE 802.11s. Mobile Adhoc and Sensor Systems, 2007. MASS 2007. IEEE Internatonal Conference on, 2007; 1 – 6. DOI: 10.1109/MOBHOC.2007.4428721.
Ieee draft standard for information technology–telecommunications and information exchange between systems–local and metropolitan area networks–specific requirements part 11: Wireless lan medium access control (mac) and physical layer (phy) specifications amendment 10: Mesh networking. IEEE Unapproved Draft Std P802.11s/D4.0, Dec 2009, December 2009, DOI: 10.1109/IEEESTD.2009.5399265.
Ad M, Royer EM, Perkins CE, Das SR. Ad hoc on‐demand distance vector (aodv) routing 1999. (Available from: http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.47.2139 ) [accessed on February 20, 2011].
Johnson DB, Maltz DA, Hu YC. The dynamic source routing protocol for mobile ad hoc networks (dsr). Technical Report, IETF MANET Working Group. February 2007 (Availabel from: http://tools.ietf.org/html/rfc4728 ) [accessed on February 20, 2011].
Clausen T, Jacquet P. Optimized Link State Routing Protocol (OLSR). RFC 3626 (Experimental), October 2003. (Available from: http://www.ietf.org/rfc/rfc3626.txt ) [accessed on February 20, 2011].
Campista MEM, Esposito PM, Moraes IM, Costa LHMK, Duarte OCMB, Passos DG, de Albuquerque CVN, Saade DCM, Rubinstein MG. Routing metrics, protocols for wireless mesh networks. Network, IEEE jan‐feb 2008; 22 ( 1 ): 6 – 12. DOI: 10.1109/MNET.2008.4435897.
Yang Y, Wang J, Kravets R. Designing routing metrics for mesh networks. Proceedings of the IEEE Workshop on Wireless Mesh Networks (WiMesh). IEEE Press, 2005.
. Koksal CE. Quality‐aware routing metrics in wireless mesh networks. In Wireless Mesh Networks, Hossain E, Leung K (eds). Springer: US, 2007; 227 – 243.
Parissidis G, Karaliopoulos M, Baumann R, Spyropoulos T, Plattner B. Routing metrics for wireless mesh networks. In Guide to Wireless Mesh Networks, Misra S, Misra SC, Woungang I (eds). Computer Communications and Networks, Springer: London, 2009; 199 – 230.
Yang Y, Wang J. Design guidelines for routing metrics in multihop wireless networks. INFOCOM 2008. The 27th Conference on Computer Communications. IEEE, 2008; 1615 – 1623. DOI: 10.1109/INFOCOM.2008.222.
De Couto DSJ, Aguayo D, Bicket J, Morris R. A high‐throughput path metric for multi‐hop wireless routing. In MobiCom '03: Proceedings of the 9th annual international conference on Mobile computing and networking. ACM: New York, NY, USA, 2003; 134 – 146. DOI: 10.1145/938985.939000.
Draves R, Padhye J, Zill B. Routing in multi‐radio, multi‐hop wireless mesh networks. In MobiCom '04: Proceedings of the 10th annual international conference on Mobile computing and networking. ACM: New York, NY, USA, 2004; 114 – 128. DOI: 10.1145/1023720.1023732.
Yang Y, Wang J, Kravets R. Interference‐aware load balancing for multihop wireless networks. Technical Report, University of Illinois at Urbana‐Champaign, 2005. (Available from: http://www.cs.uiuc.edu/research/techreports.php?report=UIUCDCS‐R‐2005‐2526 ) [accessed on February 20, 2011].
OpenWrt. Openwrt. (Available from: http://www.openwrt.org/ ) [accessed on February 20, 2011].
Meraki I. Meraki. (Available from: http://www.meraki.com/ ) [accessed on February 20, 2011].
Inc L. locustworld. (Availble from: http://locustworld.com/ ) [accessed on February 20, 2011].
Microsoft. Self organizing wireless mesh networks. (Available from: http://research.microsoft.com/en‐us/projects/mesh/ ) [accessed on February 20, 2011].
Chavoutier V, Maniezzo D, Palazzi CE, Gerla M. Multimedia over wireless mesh networks: Results from a real testbed evaluation. Proceedings of Mediteranean Ad hoc Networking Workshop, 2007.
Hyacinth: An ieee 802.11‐based multi‐channel wireless mesh network. URL http://www.ecsl.cs.sunysb.edu/multichannel/ [accessed on February 20, 2011].
Raniwala A, Gopalan K, Chiueh T. Centralized channel assignment and routing algorithms for multi‐channel wireless mesh networks. ACM SIGMOBILE Mobile Computing and Communications Review 2004; 8 ( 2 ): 50 – 65. DOI: 10.1145/997122.997130.
Skalli H, Ghosh S, Das S, Lenzini L, Conti M. Channel assignment strategies for multiradio wireless mesh networks: Issues and solutions. Communications Magazine, IEEE November 2007; 45 ( 11 ): 86 – 95. DOI: 10.1109/MCOM.2007.4378326.
Draves R, Padhye J, Zill B. Routing in multi‐radio, multi‐hop wireless mesh networks. In MobiCom '04: Proceedings of the 10th annual international conference on Mobile computing and networking. ACM: New York, NY, USA, 2004; 114 – 128. DOI: 10.1145/1023720.1023732.
Marina MK, Das SR. A topology control approach for utilizing multiple channels in multi‐radio wireless mesh networks. Vol. 1, 3‐7 Oct 2005; 381 – 390. DOI: 10.1109/ICBN.2005.1589641.
Subramanian AP, Gupta H, Das SR, Cao J. Minimum interference channel assignment in multiradio wireless mesh networks. IEEE Transactions on Mobile Computing 2008; 7 ( 12 ): 1459 – 1473. DOI: 10.1109/TMC.2008.70.
Subramanian AP, Gupta H, Das SR. Minimum interference channel assignment in multi‐radio wireless mesh networks. Sensor, Mesh and Ad Hoc Communications and Networks, 2007. SECON '07. 4th Annual IEEE Communications Society Conference on, June 2007; 481 – 490. DOI: 10.1109/SAHCN.2007.4292860.
Mohsenian‐Rad AH, Wong VWS. Joint logical topology design, interface, assignment, channel allocation, and routing for multi‐channel wireless mesh networks. Wireless Communications, IEEE Transactions on December 2007; 6 ( 12 ): 4432 – 4440. DOI: 10.1109/TWC.2007.060312.
Rad AHM, Wong VWS. Wsn16‐4: Logical topology design and interface assignment for multi‐channel wireless mesh networks. Global Telecommunications Conference, 2006. GLOBECOM '06. IEEE, Nov 2006; 1 – 6. DOI: 10.1109/GLOCOM.2006.985.
Cho S, kwon Kim C. Interference‐Aware Multi‐Channel Assignment in Multi‐Radio Wireless Mesh Networks. IEICE Transactions 2008; 91‐B ( 5 ): 1436 – 1445.
So J, Vaidya NH. Multi‐channel mac for ad hoc networks: handling multi‐channel hidden terminals using a single transceiver. In MobiHoc '04: Proceedings of the 5th ACM international symposium on Mobile ad hoc networking and computing. ACM: New York, NY, USA, 2004; 222 – 233. DOI: 10.1145/989459.989487.
Bahl P, Chandra R, Dunagan J. Ssch: slotted seeded channel hopping for capacity improvement in ieee 802.11 ad‐hoc wireless networks. In MobiCom '04: Proceedings of the 10th annual international conference on Mobile computing and networking. ACM: New York, NY, USA, 2004; 216 – 230. DOI: 10.1145/1023720.1023742.
Raniwala A, Chiueh T. Evaluation of a wireless enterprise backbone network architecture. High Performance Interconnects, 2004. Proceedings. 12th Annual IEEE Symposium on, Aug 2004; 98 – 104. DOI: 10.1109/CONECT.2004.1375211.
Raniwala A, Chiueh T. Architecture and algorithms for an ieee 802.11‐based multi‐channel wmn. IEEE INFOCOM '05, Mar 2005. DOI: 10.1109/INFCOM.2005.1498497.
Kyasanur P, Vaidya NH. Routing and interface assignment in multi‐channel multi‐interface wireless networks. In Wireless Communications and Networking Conference, 2005 IEEE, Vol. 4, 13‐17 March 2005; 2051 – 2056. DOI: 10.1109/WCNC.2005.1424834.
Kyasanur P, Vaidya NH. Routing and link‐layer protocols for multi‐channel multi‐interface ad hoc wireless networks. ACM SIGMOBILE Mobile Computing and Communications Review 2006; 10 ( 1 ): 31 – 43. DOI: 10.1145/1119759.1119762.
Ramachandran KN, Belding EM, Almeroth KC, Buddhikot MM. Interference‐aware channel assignment in multi‐radio wireless mesh networks. IEEE INFOCOM '06, Apr 2006; 1 – 12. DOI: 10.1109/INFOCOM.2006.177.
Plummer A, Wu T, Biswas S. A cognitive spectrum assignment protocol using distributed conflict graph construction. IEEE MILCOM, 2007; 1 – 7.
MIT‐RoofNet. roofnet[mit roofnet]. (Available from: http://pdos.csail.mit.edu/roofnet/doku.php ) [accessed on February 20, 2011].
Camp J, Robinson J, Steger C, Knightly E. Measurement driven deployment of a two‐tier urban mesh access network. In MobiSys '06: Proceedings of the 4th international conference on Mobile systems, applications and services. ACM: New York, NY, USA, 2006; 96 – 109. DOI: 10.1145/1134680.1134691.
Lan Kc, Wang Z, Hassan M, Moors T, Berriman R, Libman L, Ott M, Landfeldt B, Zaidi Z. Experiences in deploying a wireless mesh network testbed for traffic control. ACM SIGCOMM Computer Communication Review 2007; 37 ( 5 ): 17 – 28. DOI: 10.1145/1290168.1290171.
Purdue university wireless mesh testbed. (Available from: https://engineering.purdue.edu/MESH ) [accessed on February 20, 2011].
Wu D, Gupta D, Liese S, Mohapatra P. Qurinet: quail ridge natural reserve wireless mesh network. In WiNTECH '06: Proceedings of the 1st international workshop on Wireless network testbeds, experimental evaluation & characterization. ACM: New York, NY, USA, 2006; 109 – 110. DOI: 10.1145/1160987.1161015.
Ishmael J, Bury S, Pezaros D, Race N. Deploying rural community wireless mesh networks. Internet Computing, IEEE July‐Aug 2008; 12 ( 4 ): 22 – 29. DOI: 10.1109/MIC.2008.76.
Allen W, Martin A, Rangarajan A. Designing and deploying a rural ad‐hoc community mesh network testbed. Local Computer Networks, 2005. 30th Anniversary. The IEEE Conference on, 2005; 4 pp.–743, DOI: 10.1109/LCN.2005.51.
Tsarmpopoulos N, Kalavros I, Lalis S. A low‐cost and simple‐to‐deploy peer‐to‐peer wireless network based on open source linux routers. In TRIDENTCOM '05: Proceedings of the First International Conference on Testbeds and Research Infrastructures for the DEvelopment of NeTworks and COMmunities. IEEE Computer Society: Washington, DC, USA, 2005; 92 – 97. DOI: 10.1109/TRIDNT.2005.3.
RuralNet. Ruralnet (digital gangetic plains: Dgp) 802.11‐based low‐cost networking for rural india. (Available from: http://www.cse.iitk.ac.in/users/braman/dgp.html ) [accessed on February 20, 2011].
CUWiN. Cuwin — community wireless. (Available from: http://www.cuwireless.net/ ) [accessed on February 20, 2011].
Serrano P, de la Oliva A, Bernardos CJ, Soto I, Banchs A, Azcorra A. A carmen mesh experience: deployment and results. World of Wireless, Mobile and Multimedia Networks & Workshops, 2009. WoWMoM 2009. IEEE International Symposium on a, 2009; 1 – 6. DOI: 10.1109/WOWMOM.2009.5282418.
Passos D, Teixeira DV, Muchaluat‐saade DC, Magalhes LCS, Albuquerque CVN. Mesh network performance measurements. In 5th International Information and Telecommunication Technologies Symposium, 2006, 2006.
Mase K, Owada Y, Okada H, Imai T. A testbed‐based approach to develop layer 3 wireless mesh network protocols. In TridentCom '08: Proceedings of the 4th International Conference on Testbeds and research infrastructures for the development of networks & communities. ICST (Institute for Computer Sciences, Social‐Informatics and Telecommunications Engineering): ICST, Brussels, Belgium, Belgium, 2008; 1 – 6.
Iqbal M, Wang X, Wertheim D, Zhou X. Swanmesh: A multicast enabled dual‐radio wireless mesh network for emergency and disaster recovery services. Journal of Communications 2009; 4 ( 5 ): 298 – 306.
Capone A, Cesana M, Napoli S, Pollastro A. Mobimesh: a complete solution for wireless mesh networking. Mobile Adhoc and Sensor Systems, 2007. MASS 2007. IEEE Internatonal Conference on, 2007; 1 – 3. DOI: 10.1109/MOBHOC.2007.4428698.
Lee J, Lee SJ, Kim W, Jo D, Kwon T, Choi Y. Rss‐based carrier sensing and interference estimation in 802.11 wireless networks. Sensor, Mesh and Ad Hoc Communications and Networks, 2007. SECON '07. 4th Annual IEEE Communications Society Conference on, 2007; 491 – 500. DOI: 10.1109/SAHCN.2007.4292861.
Lundgren H, Ramachandran K, Belding‐Royer E, Almeroth K, Benny M, Hewatt A, Touma A, Jardosh A. Experiences from the design, deployment, and usage of the ucsb meshnet testbed. Wireless Communications, IEEE April 2006; 13 ( 2 ): 18 – 29, DOI: 10.1109/MWC.2006.1632477.
UMIC‐Meshnet. What is umic‐mesh.net? (Available from: http://www.umic‐mesh.net/home/ ) [accessed onFebruary 20, 2011].
SMesh. Smesh. (Available from: http://www.smesh.org/ ) [accessed on February 20, 2011].
Leipzig wireless mesh testbed. (Available from: http://rvs.informatik.uni‐leipzig.de/en/forschung/testbed.php ) [accessed on February 20, 2011].
Kim KH, Shin KG. Self‐healing multi‐radio wireless mesh networks. In MobiCom '07: Proceedings of the 13th annual ACM international conference on Mobile computing and networking. ACM: New York, NY, USA, 2007; 326 – 329. DOI: 10.1145/1287853.1287896.
Raniwala A, Chiueh T. Architecture and algorithms for an ieee 802.11‐based multi‐channel wireless mesh network. In INFOCOM 2005. 24th Annual Joint Conference of the IEEE Computer and Communications Societies. Proceedings IEEE, Vol. 3, 2005; 2223 – 2234. DOI: 10.1109/INFCOM.2005.1498497.
Edmonds C, Joiner D, Springer S, Stephen K, Hamdaoui B. Cognitive wireless mesh network testbed. Wireless Communications and Mobile Computing Conference, 2008. IWCMC '08. International, 2008; 373 – 376. DOI: 10.1109/IWCMC.2008.65.
Iannone L, Kabassanov K, Fdida S. The meshdvnet wireless mesh network test‐bed. In WiNTECH '06: Proceedings of the 1st international workshop on Wireless network testbeds, experimental evaluation & characterization. ACM: New York, NY, USA, 2006; 107 – 108, DOI: 10.1145/1160987.1161014.
” cnri wireless mesh testbed ”. (Available from: http://www.cnri.dit.ie/research.mesh.testbed.html/ ) [accessed on February 20, 2011].
Orbit. (Available from: http://www.orbit‐lab.org/ ) [accessed on February 20, 2011].
Rice university warp ‐ wireless open‐access research platform. (Available from: http://warp.rice.edu/ ) [accessed on February 20, 2011].
Wireless mesh network at carleton university. (Available from: http://kunz‐pc.sce.carleton.ca/MESH/index.htm ) [accessed on February 20, 2011].
Su Y, Gross T. Validation of a miniaturized wireless network testbed. In WiNTECH '08: Proceedings of the third ACM international workshop on Wireless network testbeds, experimental evaluation and characterization. ACM: New York, NY, USA, 2008; 25 – 32, DOI: 10.1145/1410077.1410084.
The pre‐ieee 802.11s wireless mesh network testbed at auburn university. (Available from: http://www.eng.auburn.edu/users/abidmoh/ ) [accessed on February 20, 2011].
De P, Raniwala A, Krishnan R, Tatavarthi K, Modi J, Syed NA, Sharma S, Chiueh T. Mint‐m: an autonomous mobile wireless experimentation platform. In MobiSys '06: Proceedings of the 4th international conference on Mobile systems, applications and services. ACM: New York, NY, USA, 2006; 124 – 137. DOI: 10.1145/1134680.1134694.
IndexNoFollow
John Wiley & Sons, Ltd
oai:deepblue.lib.umich.edu:2027.42/318252019-03-18T19:01:53Zcom_2027.42_13913col_2027.42_21621col_2027.42_142370
Random knapsacks with many constraints
Schilling, Kenneth E.
Department of Mathematics, University of Michigan-Flint, Flint, MI 48503, USA
We provide new results on asymptotic values for the random knapsack problem. For a very general model in which the parameters are determined by a rather arbitrary joint distribution, we compute the rate of growth as the number of objects increases, the number of constraints being fixed. For a particular model, we find strong bounds on the asymptotic value as the numbers of objects and constraints increase together.
2006-04-10T18:23:21Z
2006-04-10T18:23:21Z
1994-01-26
Article
Schilling, Kenneth (1994/01/26)."Random knapsacks with many constraints." Discrete Applied Mathematics 48(2): 163-174. <http://hdl.handle.net/2027.42/31825>
http://www.sciencedirect.com/science/article/B6TYW-45GVXJK-2N/2/13bfd0423ccffccb93f931c590c9c8a0
http://hdl.handle.net/2027.42/31825
http://dx.doi.org/10.1016/0166-218X(92)00125-6
Discrete Applied Mathematics
en_US
IndexNoFollow
Elsevier
oai:deepblue.lib.umich.edu:2027.42/1355892019-03-18T15:32:13Zcom_2027.42_13913col_2027.42_21621col_2027.42_142370
Class number formulas via 2‐isogenies of elliptic curves
McLeman, Cam
Rasmussen, Christopher
Department of Mathematics, University of Michigan‐Flint, 303 E. Kearsley Street, Flint, MI 48502, USA mclemanc@umflint.edu
Department of Mathematics and Computer Science, Wesleyan University, 265 Church Street, Middletown, CT 06459, USA
2017-01-10T19:09:54Z
2017-01-10T19:09:54Z
2012-12
Article
McLeman, Cam; Rasmussen, Christopher (2012). "Class number formulas via 2‐isogenies of elliptic curves." Bulletin of the London Mathematical Society 44(6): 1221-1236.
0024-6093
1469-2120
http://hdl.handle.net/2027.42/135589
10.1112/blms/bds049
Bulletin of the London Mathematical Society
IndexNoFollow
Oxford University Press
Wiley Periodicals, Inc.
oai:deepblue.lib.umich.edu:2027.42/1423832021-08-01T22:37:09Zcom_2027.42_13913col_2027.42_21621col_2027.42_142370
p-Tower Groups over Quadratic Imaginary Number Fields
McLeman, Cameron
UM - Flint
Flint
class field towers, class field theory, algebraic number theory
The modern theory of class field towers has its origins in the study of the p-class field tower over a quadratic imaginary number field, so it is fitting that this problem be the first in the discipline to be nearing a solution. We survey the state of the subject and present a new cohomological condition for a quadratic imaginary number field to have an infinite p-class field tower (for p odd). Under an additional hypothesis, we refine this to a necessary and sufficient condition and describe an algorithm for evaluating this condition for a given quadratic imaginary number field.
2018-02-19T16:57:16Z
2018-02-19T16:57:16Z
2008-10-01
Article
Mathematical Annals of Quebec, no. 2, 199--209
https://hdl.handle.net/2027.42/142383
Mathematical Annals of Quebec
en_US
oai:deepblue.lib.umich.edu:2027.42/458882021-08-02T00:27:58Zcom_2027.42_13913col_2027.42_21621col_2027.42_142370
A robust design in hardfacing using a plasma transfer arc
Tu, Shu-Yi
Jean, Ming-Der
Wang, Jen-Ting
Wu, Chun-Sen
Department of Mathematics, University of Michigan at Flint, Flint, MI, 48502, USA
Department of Mathematics, Computer Science, and Statistics, State University of New York College at Oneonta, USA
Welding Technology Section, Metal Industries Research & Development Centre, Kaohsiung, Taiwan
Department of Electrical Engineering, Yung-Ta Institute of Technology & Commerce, 316 Chunshan Rd, Lin-Lo, Ping-Tung, Taiwan, 909
Flint
This paper presents the use of the Taguchi-regression method in developing the optimal plasma transferred arc welding (PTAW) process for obtaining high hardfacing quality characteristics. An “optimal” process means that the best performance characteristic would be produced while the least number of process parameters are involved. In the experimental tests, the surface hardening process is conducted using Cobalt-based and Nickel-based powdery metal materials together with L 18 orthogonal arrays. The dependent variable, wear, obeys the-smaller-the-better quality characteristic, and the performance statistics, the signal-to-noise ratios (SNRs), are obtainable.
2006-09-11T16:35:20Z
2006-09-11T16:35:20Z
2006-02
Article
Tu, Shu-Yi; Jean, Ming-Der; Wang, Jen-Ting; Wu, Chun-Sen; (2006). "A robust design in hardfacing using a plasma transfer arc." The International Journal of Advanced Manufacturing Technology 27 (9-10): 889-896. <http://hdl.handle.net/2027.42/45888>
1433-3015
0268-3768
https://hdl.handle.net/2027.42/45888
http://dx.doi.org/10.1007/s00170-004-2265-6
The International Journal of Advanced Manufacturing Technology
en_US
Springer-Verlag
oai:deepblue.lib.umich.edu:2027.42/1766952023-07-18T12:53:51Zcom_2027.42_13913col_2027.42_142370
Evaluation of LoRa Mesh Networks for Disaster Response
Poke, Brenton
Suleyman Uludag, Ph.D
Stephen Turner, Ph.D.
Computer Science, Engineering and Physics, Department of
Flint
LoRa
IoT
Wireless Networks
Emergency Response
Mesh Networking
Natural and man-made disasters are becoming more prevalent and increasing in danger as climate change continues unabated and resources get scarce. Whether it be flood or terrorism, disasters displace people and it remains difficult to reach those in need when the disaster does strike. For years, mobile phone networks have been integral in responding to emergencies, but they rely on costly infrastructure that is prone to outages or outright attack. We propose a long-range, low-power mesh network infrastructure based on a new, still-developing networking protocol and embedded software implementation that seeks to fill the need of disaster communications telemetry gathering for a fraction of the cost of mobile phone networking infrastructure such as 4G LTE or 5G. While the protocol is simple, it was found to have an inadequate implementation at this stage. Error rates were high and bugs were found in implementation that led to an abnormal amount of time spent processing corrupted data, though power consumption was encouraging in spite of these conditions. We examine the strengths and weaknesses of this new protocol and suggest improvements to harden the implementation.
2023-05-25T18:27:51Z
2023-05-25T18:27:51Z
2023-04-28
Thesis
https://hdl.handle.net/2027.42/176695
https://dx.doi.org/10.7302/7544
en_US
oai:deepblue.lib.umich.edu:2027.42/700652023-07-18T13:03:53Zcom_2027.42_13913col_2027.42_142370col_2027.42_21621col_2027.42_78391
Surface reconstructions of In-enriched InGaAs alloys
Millunchick, Joanna Mirecki
Riposan, Alexandru
Dall, B. J.
Pearson, Chris A.
Orr, B. G.
Department of Materials Science and Engineering, University of Michigan, Ann Arbor, Michigan 48109
Department of Computer Science, Engineering Science and Physics, University of Michigan-Flint, Flint, Michigan 48502
The Harrison M. Randall Laboratory, University of Michigan, Ann Arbor, Michigan 48109
The atomic structure of In0.81Ga0.19As/InPIn0.81Ga0.19As/InP alloy layers was examined using in situ scanning tunneling microscopy. The (2×3) reconstruction observed during growth by reflection high-energy electron diffraction represents a combination of surface structures, including a β2(2×4) commonly observed on GaAs(001) and InAs(001) surfaces, and a disordered (4×3) that is unique to alloy systems. The proposed (4×3) structure is comprised of both anion and cation dimers. Empty and filled states images show that the features reverse contrast with sample bias, in agreement with the model. © 2003 American Institute of Physics.
2010-05-06T21:34:45Z
2010-05-06T21:34:45Z
2003-08-18
Article
Millunchick, J. Mirecki; Riposan, A.; Dall, B. J.; Pearson, Chris; Orr, B. G. (2003). "Surface reconstructions of In-enriched InGaAs alloys." Applied Physics Letters 83(7): 1361-1363. <http://hdl.handle.net/2027.42/70065>
https://hdl.handle.net/2027.42/70065
10.1063/1.1602557
Applied Physics Letters
B. Shin, A. Lin, K. Lappo, R. S. Goldman, M. C. Hanna, S. Francoeur, A. G. Norman, and A. Mascarenhas, Appl. Phys. Lett. APPLAB80, 3292 (2002).
S. L. Zuo, E. T. Yu, A. A. Allerman, and R. M. Biefeld, J. Vac. Sci. Technol. B JVTBD917, 1781 (1999).
E. T. Yu, S. L. Zuo, W. G. Bi, C. W. Tu, A. A. Allerman, and R. M. Biefeld, J. Vac. Sci. Technol. A JVTAD617, 2246 (1999).
B. Z. Nosho, W. H. Weinberg, W. Barvosa-Carter, B. R. Bennett, B. V. Shanabrook, and L. J. Whitman, Appl. Phys. Lett. APPLAB74, 1704 (1999).
S. Froyen and A. Zunger, Phys. Rev. B PRBMDO53, 4570 (1996).
V. Bresslerhill, M. Wassermeier, K. Pond, R. Maboudian, G. A. D. Briggs, P. M. Petroff, and W. H. Weinberg, J. Vac. Sci. Technol. B JVTBD910, 1881 (1992).
W. Barvosa-Carter, R. S. Ross, C. Ratsch, F. Grosse, J. H. G. Owen, and J. J. Zinck, Surf. Sci. SUSCAS499, L129 (2002).
V. P. LaBella, Z. Ding, D. W. Bullock, C. Emery, and P. M. Thibado, J. Vac. Sci. Technol. A JVTAD618, 1492 (2000).
A. S. Bracker, M. J. Yang, B. R. Bennett, J. C. Culbertson, and W. J. Moore, J. Cryst. Growth JCRGAE220, 384 (2000).
S. Ohkouchi and A. Gomyo, Appl. Surf. Sci. ASUSEE132, 447 (1998).
M. Gendry, G. Grenet, Y. Robach, P. Krapf, L. Porte, and G. Hollinger, Phys. Rev. B PRBMDO56, 9271 (1997).
L. Porte, P. Krapf, Y. Robach, M. Phaner, M. Gendry, and G. Hollinger, Surf. Sci. SUSCAS352, 60 (1996).
L. Li, B. K. Han, R. F. Hicks, H. Yoon, and M. S. Goorsky, Ultramicroscopy ULTRD673, 229 (1998).
J. G. Belk, C. F. McConville, J. L. Sudijono, T. S. Jones, and B. A. Joyce, Surf. Sci. SUSCAS387, 213 (1997).
V. Bresslerhill, A. Lorke, S. Varma, P. M. Petroff, K. Pond, and W. H. Weinberg, Phys. Rev. B PRBMDO50, 8479 (1994).
M. Sauvagesimkin, Y. Garreau, R. Pinchaux, M. B. Veron, J. P. Landesman, and J. Nagle, Phys. Rev. Lett. PRLTAO75, 3485 (1995).
J. M. Moison, C. Guille, F. Houzay, F. Barthe, and M. Vanrompay, Phys. Rev. B PRBMDO40, 6149 (1989).
J. M. Moison, C. Guille, and M. Bensoussan, Phys. Rev. Lett. PRLTAO58, 2555 (1987).
C. F. Mcconville, T. S. Jones, F. M. Leibsle, S. M. Driver, T. C. Q. Noakes, M. O. Schweitzer, and N. V. Richardson, Phys. Rev. B PRBMDO50, 14965 (1994).
J. M. Millunchick, A. Riposan, B. J. Dall, C. A. Pearson, and B. G. Orr (unpublished).
A. Zunger and S. Mahajan, Atomic Ordering and Phase Separation in Epitaxial III-V Alloys, in Handbook on Semiconductors, edited by S. Mahajan (Elsevier Science, New York, 1994), p. 1399.
A. Ohtake, J. Nakamura, S. Tsukamoto, N. Koguchi, and A. Natori, Phys. Rev. Lett. PRLTAO89, 206102 (2002).
J. E. Guyer and P. W. Voorhees, J. Cryst. Growth JCRGAE187, 150 (1998).
© The American Institute of Physics
The American Institute of Physics
oai:deepblue.lib.umich.edu:2027.42/1116422023-07-18T12:57:18Zcom_2027.42_13913col_2027.42_142370col_2027.42_21621
Secure and Scalable Data Collection With Time Minimization in the Smart Grid
Uludag, Suleyman
Lui, King-Shan
Ren, Wenyu
Nahrstedt, Klara
CSEP, UM-Flint
Department of Electrical and Electronic Engineering, University of Hong Kong
Department of Computer Science, University of Illinois at Urbana-Champaign
Flint
Data collection with time minimization in the smart grid
scalable data collection in the smart grid
secure data collection in the smart grid
Deployment of data generation devices such as sensors and smart meters have been accelerating toward the vision of smart grid. The volume of data to be collected increases tremendously. Secure, efficient, and scalable data collection becomes a challenging task. In this paper, we present a secure and scalable data communications protocol for smart grid data collection. Under a hierarchical architecture, relay nodes [also known as data collectors (DCs)] collect and convey the data securely from measurement devices to the power operator. While the DCs can verify the integrity, they are not given access to the content, which may pave the way for third party providers to deliver value-added services or even the data collection itself. We further present optimization solutions for minimizing the total data collection time.
2015-05-15T14:27:18Z
2015-05-15T14:27:18Z
2016-01
Article
1949-3053
https://hdl.handle.net/2027.42/111642
IEEE Transactions on Smart Grid
orcid.org/0000-0002-7207-6683
Uludag, Suleyman; 0000-0002-7207-6683
en_US
oai:deepblue.lib.umich.edu:2027.42/1046232023-12-07T14:38:01Zcom_2027.42_13913col_2027.42_142370
Absolute differential electron-impact cross sections of atomic hydrogen: Elastic and n = 2 excitation scattering.
Grafe, Alan George
Shyn, Tong W.
Zorn, Jens C.
Physics, Atomic
By means of a modulated crossed-beam technique, we have measured electron energy-loss spectra for atomic hydrogen. The scattering angles of the measurements were from 12 through 156$\sp\circ$, in 12$\sp\circ$ increments. A variety of electron impact energies in the range 15 through 200 eV were employed. The results of our measurements are differential cross sections for elastic scattering and for excitation of the n = 2 state. Using these, we have computed integrated cross sections for the elastic and $n=2$ excitation scattering processes and momentum-transfer cross sections for the elastic scattering process. The elastic scattering cross sections show agreement with previous measurements for scattering angles less than 90$\sp\circ$, but it is found that the present results exhibit a stronger backward scattering than the previous measurements and theoretical calculations by up to a factor of 3. The $n=2$ excitation scattering cross sections show agreement with the previous measurements of other researchers and with theoretical calculations. The significance of the agreement of the $n=2$ excitation cross sections despite the disagreement of the elastic cross sections is discussed.
2014-02-24T16:22:41Z
2014-02-24T16:22:41Z
1995
Thesis
(UMI)AAI9542847
http://gateway.proquest.com/openurl?url_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:dissertation&res_dat=xri:pqm&rft_dat=xri:pqdiss:9542847
https://hdl.handle.net/2027.42/104623
oai:deepblue.lib.umich.edu:2027.42/1116442023-07-18T12:54:46Zcom_2027.42_13913col_2027.42_142370col_2027.42_21621
Techniques, Taxonomy, and Challenges of Privacy Protection in the Smart Grid
Uludag, Suleyman
Zeadally, Sherali
Badra, Mohamad
CSEP, UM-Flint
College of Communication and Information, University of Kentucky, Lexington, KY, USA
Zayed University, Abu Dhabi 144534
Flint
Smart Grid Privacy
As the ease with which any data are collected and transmitted increases,
more privacy concerns arise leading to an increasing need to protect and preserve
it. Much of the recent high-profile coverage of data mishandling and public mis-
leadings about various aspects of privacy exasperates the severity. The Smart Grid
(SG) is no exception with its key characteristics aimed at supporting bi-directional
information flow between the consumer of electricity and the utility provider. What
makes the SG privacy even more challenging and intriguing is the fact that the very
success of the initiative depends on the expanded data generation, sharing, and pro-
cessing. In particular, the deployment of smart meters whereby energy consumption
information can easily be collected leads to major public hesitations about the tech-
nology. Thus, to successfully transition from the traditional Power Grid to the SG
of the future, public concerns about their privacy must be explicitly addressed and
fears must be allayed. Along these lines, this chapter introduces some of the privacy
issues and problems in the domain of the SG, develops a unique taxonomy of some
of the recently proposed privacy protecting solutions as well as some if the future
privacy challenges that must be addressed in the future.
2015-05-18T07:06:57Z
2015-05-18T07:06:57Z
2015-05-18
Book Chapter
978-3-319-08469-5
1617-7975
https://hdl.handle.net/2027.42/111644
Privacy in a Digital, Networked World Technologies, Implications and Solutions
orcid.org/0000-0002-7207-6683
Uludag, Suleyman; 0000-0002-7207-6683
en_US
Springer International Publishing