Jay Smith

433 total citations
30 papers, 298 citations indexed

About

Jay Smith is a scholar working on Computer Networks and Communications, Information Systems and Hardware and Architecture. According to data from OpenAlex, Jay Smith has authored 30 papers receiving a total of 298 indexed citations (citations by other indexed papers that have themselves been cited), including 24 papers in Computer Networks and Communications, 21 papers in Information Systems and 17 papers in Hardware and Architecture. Recurrent topics in Jay Smith's work include Distributed and Parallel Computing Systems (23 papers), Cloud Computing and Resource Management (20 papers) and Parallel Computing and Optimization Techniques (17 papers). Jay Smith is often cited by papers focused on Distributed and Parallel Computing Systems (23 papers), Cloud Computing and Resource Management (20 papers) and Parallel Computing and Optimization Techniques (17 papers). Jay Smith collaborates with scholars based in United States, Jordan and China. Jay Smith's co-authors include Howard Jay Siegel, Anthony A. Maciejewski, Edwin K. P. Chong, Bin Ye, Sudeep Pasricha, Adrián Ramírez, Puneet Prakash, Amin Alqudah, Jerry L. Potter and Andrew M. Sutton and has published in prestigious journals such as Future Generation Computer Systems, IEEE Transactions on Parallel and Distributed Systems and Journal of Parallel and Distributed Computing.

In The Last Decade

Jay Smith

29 papers receiving 279 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Jay Smith United States 11 244 184 139 31 15 30 298
Hans-Ulrich Heiß Germany 8 224 0.9× 100 0.5× 150 1.1× 5 0.2× 8 0.5× 33 276
E. Ilavarasan India 8 188 0.8× 180 1.0× 72 0.5× 11 0.4× 3 0.2× 38 293
Angela C. Sodan Canada 9 169 0.7× 109 0.6× 152 1.1× 3 0.1× 10 0.7× 38 252
Marshall T. Rose United States 8 202 0.8× 80 0.4× 34 0.2× 3 0.1× 6 0.4× 27 279
D. Brian Larkins United States 6 203 0.8× 114 0.6× 181 1.3× 4 0.1× 3 0.2× 19 292
Andrei Hutanu United States 9 170 0.7× 42 0.2× 56 0.4× 5 0.2× 5 0.3× 27 251
Eduardo César Spain 9 161 0.7× 115 0.6× 112 0.8× 2 0.1× 10 0.7× 41 237
Trevor P. Hopkins United Kingdom 6 125 0.5× 46 0.3× 89 0.6× 8 0.3× 8 0.5× 12 248
Frank Doelitzscher Germany 8 125 0.5× 204 1.1× 15 0.1× 6 0.2× 6 0.4× 9 259
Vlad Nae Austria 9 359 1.5× 299 1.6× 32 0.2× 9 0.3× 7 0.5× 18 389

Countries citing papers authored by Jay Smith

Since Specialization
Citations

This map shows the geographic impact of Jay Smith's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Jay Smith with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jay Smith more than expected).

Fields of papers citing papers by Jay Smith

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Jay Smith. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Jay Smith. The network helps show where Jay Smith may publish in the future.

Co-authorship network of co-authors of Jay Smith

This figure shows the co-authorship network connecting the top 25 collaborators of Jay Smith. A scholar is included among the top collaborators of Jay Smith based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Jay Smith. Jay Smith is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Salehi, Mohsen Amini, Jay Smith, Anthony A. Maciejewski, et al.. (2016). Stochastic-based robust dynamic resource allocation for independent tasks in a heterogeneous computing system. Journal of Parallel and Distributed Computing. 97. 96–111. 23 indexed citations
2.
Pasricha, Sudeep, Anthony A. Maciejewski, Howard Jay Siegel, et al.. (2014). Makespan and Energy Robust Stochastic Static Resource Allocation of a Bag-of-Tasks to a Heterogeneous Computing System. IEEE Transactions on Parallel and Distributed Systems. 26(10). 2791–2805. 15 indexed citations
3.
Smith, Jay, et al.. (2013). Robust static resource allocation of DAGs in a heterogeneous multicore system. Journal of Parallel and Distributed Computing. 73(12). 1705–1717. 10 indexed citations
4.
Briceño-Arias, Luis M., Jay Smith, Sudeep Pasricha, et al.. (2011). Stochastically robust static resource allocation for energy minimization with a makespan constraint in a heterogeneous computing environment. 3. 22–31. 10 indexed citations
5.
Maciejewski, Anthony A., et al.. (2011). Statistical measures for quantifying task and machine heterogeneities. The Journal of Supercomputing. 57(1). 34–50. 14 indexed citations
6.
Smith, Jay, et al.. (2010). Robust resource allocation of DAGs in a heterogeneous multicore system. 68. 1–11. 1 indexed citations
7.
Maciejewski, Anthony A., et al.. (2009). Task and Machine Heterogeneities: Higher Momenets Matter.. Parallel and Distributed Processing Techniques and Applications. 3–9. 3 indexed citations
8.
Smith, Jay, et al.. (2009). Robust resource allocation in a cluster based imaging system. Parallel Computing. 35(7). 389–400. 6 indexed citations
9.
Smith, Jay, Howard Jay Siegel, & Anthony A. Maciejewski. (2008). Iterative Techniques for Maximizing Stochastic Robustness of a Static Resource Allocation in Periodic Sensor Driven Clusters.. Parallel and Distributed Processing Techniques and Applications. 3–9. 2 indexed citations
10.
Smith, Jay, et al.. (2008). Stochastic robustness metric and its use for static resource allocations. Journal of Parallel and Distributed Computing. 68(8). 1157–1173. 47 indexed citations
11.
Smith, Jay, Howard Jay Siegel, & Anthony A. Maciejewski. (2008). A stochastic model for robust resource allocation in heterogeneous parallel and distributed computing systems. Proceedings - IEEE International Parallel and Distributed Processing Symposium. 1–5. 7 indexed citations
12.
Smith, Jay, et al.. (2007). Resource Allocation in a Cluster Based Imaging System.. Parallel and Distributed Processing Techniques and Applications. 3–9. 1 indexed citations
13.
Smith, Jay, et al.. (2007). Models and Heuristics for Robust Resource Allocation in Parallel and Distributed Computing Systems. Digital Collections of Colorado (Colorado State University). 1. 1–5. 3 indexed citations
14.
Smith, Jay, et al.. (2007). Dynamic resource allocation heuristics that manage tradeoff between makespan and robustness. The Journal of Supercomputing. 42(1). 33–58. 29 indexed citations
15.
Smith, Jay, et al.. (2006). Dynamic Resource Allocation Heuristics for Maximizing Robustness with an Overall Makespan Constraint in an Uncertain Environment.. Parallel and Distributed Processing Techniques and Applications. 24–30. 2 indexed citations
16.
Smith, Jay, et al.. (2006). Greedy Approaches to Static Stochastic Robust Resource Allocation for Periodic Sensor Driven Distributed Systems.. Parallel and Distributed Processing Techniques and Applications. 3–9. 6 indexed citations
17.
Fischer, Gerhard, Stefanie Lindstaedt, Jonathan Ostwald, Kurt Schneider, & Jay Smith. (1996). Informing system design through organizational learning. 52–59. 11 indexed citations
18.
Smith, Jay, et al.. (1994). Measure centripetal force for under $3. The Physics Teacher. 32(6). 380–381. 5 indexed citations
19.
Smith, Jay, et al.. (1985). The dynamics of successful feedback. Performance + Instruction. 24(8). 4–6. 7 indexed citations
20.
Smith, Jay, et al.. (1984). Instructor image, attitudes & technology usage. 23(5). 11–13. 2 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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