Comparative analysis of wireless ATM channel access protocols supporting multimedia traffic View Full Text


Ontology type: schema:ScholarlyArticle     


Article Info

DATE

1998-09

AUTHORS

Jyh‐Cheng Chen, Krishna M. Sivalingam, Raj Acharya

ABSTRACT

Extension of multimedia services and applications offered by ATM networks to wireless and mobile users has captured a lot of recent research attention. Research prototyping of wireless ATM networks is currently underway at many leading research and academic institutions. Various architectures have been proposed depending on the intended application domain. Successful implementation of wireless connectivity to ATM services is significantly dependent on the medium access control (MAC) protocol, which has to provide support for multimedia traffic and for quality‐of‐service (QoS) guarantees. The objective of this paper is to investigate the comparative performance of a set of access protocols, proposed earlier in the literature, with more realistic source traffic models. Data traffic is modeled with self‐similar (fractal) behavior. Voice traffic is modeled by a slow speech activity detector (SAD). Video traffic is modeled as a H.261 video teleconference, where the number of ATM cells per video frame is described by a gamma distribution and a first‐order discrete autoregressive process model. A comparison of the protocols based on simulation data is presented. The goal of the paper is to identify appropriate techniques for effectively and efficiently supporting multimedia traffic and QoS. Simulation results show that boundaries between different types of services are necessary for multimedia traffic. Reservation for certain traffic type especially video can significantly improve its quality. Reducing the number of collisions is an important issue for wireless networks since contentions lead not only to potentially high delay but also result in high power consumption. More... »

PAGES

293-306

References to SciGraph publications

Identifiers

URI

http://scigraph.springernature.com/pub.10.1023/a:1019189118727

DOI

http://dx.doi.org/10.1023/a:1019189118727

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1040984962


Indexing Status Check whether this publication has been indexed by Scopus and Web Of Science using the SN Indexing Status Tool
Incoming Citations Browse incoming citations for this publication using opencitations.net

JSON-LD is the canonical representation for SciGraph data.

TIP: You can open this SciGraph record using an external JSON-LD service: JSON-LD Playground Google SDTT

[
  {
    "@context": "https://springernature.github.io/scigraph/jsonld/sgcontext.json", 
    "about": [
      {
        "id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/1005", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "name": "Communications Technologies", 
        "type": "DefinedTerm"
      }, 
      {
        "id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/10", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "name": "Technology", 
        "type": "DefinedTerm"
      }
    ], 
    "author": [
      {
        "affiliation": {
          "alternateName": "University at Buffalo, State University of New York", 
          "id": "https://www.grid.ac/institutes/grid.273335.3", 
          "name": [
            "Department of Electrical & Computer Engineering, State University of New York at Buffalo, 14260, Buffalo, NY, USA"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Chen", 
        "givenName": "Jyh\u2010Cheng", 
        "id": "sg:person.07733655463.45", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.07733655463.45"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Washington State University", 
          "id": "https://www.grid.ac/institutes/grid.30064.31", 
          "name": [
            "School of Electrical Engineering & Computer Science, Washington State University, 99164, Pullman, WA, USA"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Sivalingam", 
        "givenName": "Krishna M.", 
        "id": "sg:person.015362517307.38", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.015362517307.38"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "University at Buffalo, State University of New York", 
          "id": "https://www.grid.ac/institutes/grid.273335.3", 
          "name": [
            "Department of Electrical & Computer Engineering, State University of New York at Buffalo, 14260, Buffalo, NY, USA"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Acharya", 
        "givenName": "Raj", 
        "id": "sg:person.012122452653.93", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.012122452653.93"
        ], 
        "type": "Person"
      }
    ], 
    "citation": [
      {
        "id": "sg:pub.10.1007/bf01200846", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1033485383", 
          "https://doi.org/10.1007/bf01200846"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/bf01200846", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1033485383", 
          "https://doi.org/10.1007/bf01200846"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1023/a:1019117603571", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1033650561", 
          "https://doi.org/10.1023/a:1019117603571"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/bf01202539", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1036975842", 
          "https://doi.org/10.1007/bf01202539"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/bf01202539", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1036975842", 
          "https://doi.org/10.1007/bf01202539"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/0140-3664(83)90084-1", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1051429464"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/0140-3664(83)90084-1", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1051429464"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1109/25.293653", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1061134462"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1109/25.312788", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1061134504"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1109/25.330174", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1061134563"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1109/25.69985", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1061134996"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1109/26.31190", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1061136563"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1109/26.385941", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1061136889"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1109/35.364929", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1061159042"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1109/35.536564", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1061159293"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1109/35.556485", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1061159326"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1109/49.329336", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1061177103"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1109/49.490411", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1061177410"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1109/49.490412", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1061177411"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1109/49.553680", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1061177573"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1109/76.134371", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1061221776"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1109/76.538925", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1061222023"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1109/90.282603", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1061247074"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1109/90.554723", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1061247283"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1109/98.382529", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1061251584"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1109/98.490750", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1061251615"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1109/98.536477", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1061251625"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1109/98.536479", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1061251627"
        ], 
        "type": "CreativeWork"
      }
    ], 
    "datePublished": "1998-09", 
    "datePublishedReg": "1998-09-01", 
    "description": "Extension of multimedia services and applications offered by ATM networks to wireless and mobile users has captured a lot of recent research attention. Research prototyping of wireless ATM networks is currently underway at many leading research and academic institutions. Various architectures have been proposed depending on the intended application domain. Successful implementation of wireless connectivity to ATM services is significantly dependent on the medium access control (MAC) protocol, which has to provide support for multimedia traffic and for quality\u2010of\u2010service (QoS) guarantees. The objective of this paper is to investigate the comparative performance of a set of access protocols, proposed earlier in the literature, with more realistic source traffic models. Data traffic is modeled with self\u2010similar (fractal) behavior. Voice traffic is modeled by a slow speech activity detector (SAD). Video traffic is modeled as a H.261 video teleconference, where the number of ATM cells per video frame is described by a gamma distribution and a first\u2010order discrete autoregressive process model. A comparison of the protocols based on simulation data is presented. The goal of the paper is to identify appropriate techniques for effectively and efficiently supporting multimedia traffic and QoS. Simulation results show that boundaries between different types of services are necessary for multimedia traffic. Reservation for certain traffic type especially video can significantly improve its quality. Reducing the number of collisions is an important issue for wireless networks since contentions lead not only to potentially high delay but also result in high power consumption.", 
    "genre": "research_article", 
    "id": "sg:pub.10.1023/a:1019189118727", 
    "inLanguage": [
      "en"
    ], 
    "isAccessibleForFree": false, 
    "isPartOf": [
      {
        "id": "sg:journal.1136741", 
        "issn": [
          "1383-469X", 
          "1572-8153"
        ], 
        "name": "Mobile Networks and Applications", 
        "type": "Periodical"
      }, 
      {
        "issueNumber": "3", 
        "type": "PublicationIssue"
      }, 
      {
        "type": "PublicationVolume", 
        "volumeNumber": "3"
      }
    ], 
    "name": "Comparative analysis of wireless ATM channel access protocols supporting multimedia traffic", 
    "pagination": "293-306", 
    "productId": [
      {
        "name": "readcube_id", 
        "type": "PropertyValue", 
        "value": [
          "c33d45ed042af2a6d90c8cbb822b063cb60a1bd05d93ff50964862d65c9990ec"
        ]
      }, 
      {
        "name": "doi", 
        "type": "PropertyValue", 
        "value": [
          "10.1023/a:1019189118727"
        ]
      }, 
      {
        "name": "dimensions_id", 
        "type": "PropertyValue", 
        "value": [
          "pub.1040984962"
        ]
      }
    ], 
    "sameAs": [
      "https://doi.org/10.1023/a:1019189118727", 
      "https://app.dimensions.ai/details/publication/pub.1040984962"
    ], 
    "sdDataset": "articles", 
    "sdDatePublished": "2019-04-11T01:59", 
    "sdLicense": "https://scigraph.springernature.com/explorer/license/", 
    "sdPublisher": {
      "name": "Springer Nature - SN SciGraph project", 
      "type": "Organization"
    }, 
    "sdSource": "s3://com-uberresearch-data-dimensions-target-20181106-alternative/cleanup/v134/2549eaecd7973599484d7c17b260dba0a4ecb94b/merge/v9/a6c9fde33151104705d4d7ff012ea9563521a3ce/jats-lookup/v90/0000000001_0000000264/records_8700_00000507.jsonl", 
    "type": "ScholarlyArticle", 
    "url": "http://link.springer.com/10.1023%2FA%3A1019189118727"
  }
]
 

Download the RDF metadata as:  json-ld nt turtle xml License info

HOW TO GET THIS DATA PROGRAMMATICALLY:

JSON-LD is a popular format for linked data which is fully compatible with JSON.

curl -H 'Accept: application/ld+json' 'https://scigraph.springernature.com/pub.10.1023/a:1019189118727'

N-Triples is a line-based linked data format ideal for batch operations.

curl -H 'Accept: application/n-triples' 'https://scigraph.springernature.com/pub.10.1023/a:1019189118727'

Turtle is a human-readable linked data format.

curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1023/a:1019189118727'

RDF/XML is a standard XML format for linked data.

curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1023/a:1019189118727'


 

This table displays all metadata directly associated to this object as RDF triples.

156 TRIPLES      21 PREDICATES      52 URIs      19 LITERALS      7 BLANK NODES

Subject Predicate Object
1 sg:pub.10.1023/a:1019189118727 schema:about anzsrc-for:10
2 anzsrc-for:1005
3 schema:author N865b18854baf490088f276fb14e5c116
4 schema:citation sg:pub.10.1007/bf01200846
5 sg:pub.10.1007/bf01202539
6 sg:pub.10.1023/a:1019117603571
7 https://doi.org/10.1016/0140-3664(83)90084-1
8 https://doi.org/10.1109/25.293653
9 https://doi.org/10.1109/25.312788
10 https://doi.org/10.1109/25.330174
11 https://doi.org/10.1109/25.69985
12 https://doi.org/10.1109/26.31190
13 https://doi.org/10.1109/26.385941
14 https://doi.org/10.1109/35.364929
15 https://doi.org/10.1109/35.536564
16 https://doi.org/10.1109/35.556485
17 https://doi.org/10.1109/49.329336
18 https://doi.org/10.1109/49.490411
19 https://doi.org/10.1109/49.490412
20 https://doi.org/10.1109/49.553680
21 https://doi.org/10.1109/76.134371
22 https://doi.org/10.1109/76.538925
23 https://doi.org/10.1109/90.282603
24 https://doi.org/10.1109/90.554723
25 https://doi.org/10.1109/98.382529
26 https://doi.org/10.1109/98.490750
27 https://doi.org/10.1109/98.536477
28 https://doi.org/10.1109/98.536479
29 schema:datePublished 1998-09
30 schema:datePublishedReg 1998-09-01
31 schema:description Extension of multimedia services and applications offered by ATM networks to wireless and mobile users has captured a lot of recent research attention. Research prototyping of wireless ATM networks is currently underway at many leading research and academic institutions. Various architectures have been proposed depending on the intended application domain. Successful implementation of wireless connectivity to ATM services is significantly dependent on the medium access control (MAC) protocol, which has to provide support for multimedia traffic and for quality‐of‐service (QoS) guarantees. The objective of this paper is to investigate the comparative performance of a set of access protocols, proposed earlier in the literature, with more realistic source traffic models. Data traffic is modeled with self‐similar (fractal) behavior. Voice traffic is modeled by a slow speech activity detector (SAD). Video traffic is modeled as a H.261 video teleconference, where the number of ATM cells per video frame is described by a gamma distribution and a first‐order discrete autoregressive process model. A comparison of the protocols based on simulation data is presented. The goal of the paper is to identify appropriate techniques for effectively and efficiently supporting multimedia traffic and QoS. Simulation results show that boundaries between different types of services are necessary for multimedia traffic. Reservation for certain traffic type especially video can significantly improve its quality. Reducing the number of collisions is an important issue for wireless networks since contentions lead not only to potentially high delay but also result in high power consumption.
32 schema:genre research_article
33 schema:inLanguage en
34 schema:isAccessibleForFree false
35 schema:isPartOf N161c279f85214537ae2b58ac5763a875
36 N8e2b44e7a90e41df905d05fe390cc7fc
37 sg:journal.1136741
38 schema:name Comparative analysis of wireless ATM channel access protocols supporting multimedia traffic
39 schema:pagination 293-306
40 schema:productId N2fd7b346562e4152bc863ceee08ccd12
41 N8e5861b16660424da4d14cfc848786d0
42 N96c552355a7f43768228f594a6744d60
43 schema:sameAs https://app.dimensions.ai/details/publication/pub.1040984962
44 https://doi.org/10.1023/a:1019189118727
45 schema:sdDatePublished 2019-04-11T01:59
46 schema:sdLicense https://scigraph.springernature.com/explorer/license/
47 schema:sdPublisher N4babbd5578e74a03b4ecfacc1be570b0
48 schema:url http://link.springer.com/10.1023%2FA%3A1019189118727
49 sgo:license sg:explorer/license/
50 sgo:sdDataset articles
51 rdf:type schema:ScholarlyArticle
52 N161c279f85214537ae2b58ac5763a875 schema:issueNumber 3
53 rdf:type schema:PublicationIssue
54 N2fd7b346562e4152bc863ceee08ccd12 schema:name doi
55 schema:value 10.1023/a:1019189118727
56 rdf:type schema:PropertyValue
57 N313e53e55cf54aa7a9768ebc9faf6929 rdf:first sg:person.012122452653.93
58 rdf:rest rdf:nil
59 N4babbd5578e74a03b4ecfacc1be570b0 schema:name Springer Nature - SN SciGraph project
60 rdf:type schema:Organization
61 N865b18854baf490088f276fb14e5c116 rdf:first sg:person.07733655463.45
62 rdf:rest N9fe80d3a5b8d48539af550ea1e6f1388
63 N8e2b44e7a90e41df905d05fe390cc7fc schema:volumeNumber 3
64 rdf:type schema:PublicationVolume
65 N8e5861b16660424da4d14cfc848786d0 schema:name readcube_id
66 schema:value c33d45ed042af2a6d90c8cbb822b063cb60a1bd05d93ff50964862d65c9990ec
67 rdf:type schema:PropertyValue
68 N96c552355a7f43768228f594a6744d60 schema:name dimensions_id
69 schema:value pub.1040984962
70 rdf:type schema:PropertyValue
71 N9fe80d3a5b8d48539af550ea1e6f1388 rdf:first sg:person.015362517307.38
72 rdf:rest N313e53e55cf54aa7a9768ebc9faf6929
73 anzsrc-for:10 schema:inDefinedTermSet anzsrc-for:
74 schema:name Technology
75 rdf:type schema:DefinedTerm
76 anzsrc-for:1005 schema:inDefinedTermSet anzsrc-for:
77 schema:name Communications Technologies
78 rdf:type schema:DefinedTerm
79 sg:journal.1136741 schema:issn 1383-469X
80 1572-8153
81 schema:name Mobile Networks and Applications
82 rdf:type schema:Periodical
83 sg:person.012122452653.93 schema:affiliation https://www.grid.ac/institutes/grid.273335.3
84 schema:familyName Acharya
85 schema:givenName Raj
86 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.012122452653.93
87 rdf:type schema:Person
88 sg:person.015362517307.38 schema:affiliation https://www.grid.ac/institutes/grid.30064.31
89 schema:familyName Sivalingam
90 schema:givenName Krishna M.
91 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.015362517307.38
92 rdf:type schema:Person
93 sg:person.07733655463.45 schema:affiliation https://www.grid.ac/institutes/grid.273335.3
94 schema:familyName Chen
95 schema:givenName Jyh‐Cheng
96 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.07733655463.45
97 rdf:type schema:Person
98 sg:pub.10.1007/bf01200846 schema:sameAs https://app.dimensions.ai/details/publication/pub.1033485383
99 https://doi.org/10.1007/bf01200846
100 rdf:type schema:CreativeWork
101 sg:pub.10.1007/bf01202539 schema:sameAs https://app.dimensions.ai/details/publication/pub.1036975842
102 https://doi.org/10.1007/bf01202539
103 rdf:type schema:CreativeWork
104 sg:pub.10.1023/a:1019117603571 schema:sameAs https://app.dimensions.ai/details/publication/pub.1033650561
105 https://doi.org/10.1023/a:1019117603571
106 rdf:type schema:CreativeWork
107 https://doi.org/10.1016/0140-3664(83)90084-1 schema:sameAs https://app.dimensions.ai/details/publication/pub.1051429464
108 rdf:type schema:CreativeWork
109 https://doi.org/10.1109/25.293653 schema:sameAs https://app.dimensions.ai/details/publication/pub.1061134462
110 rdf:type schema:CreativeWork
111 https://doi.org/10.1109/25.312788 schema:sameAs https://app.dimensions.ai/details/publication/pub.1061134504
112 rdf:type schema:CreativeWork
113 https://doi.org/10.1109/25.330174 schema:sameAs https://app.dimensions.ai/details/publication/pub.1061134563
114 rdf:type schema:CreativeWork
115 https://doi.org/10.1109/25.69985 schema:sameAs https://app.dimensions.ai/details/publication/pub.1061134996
116 rdf:type schema:CreativeWork
117 https://doi.org/10.1109/26.31190 schema:sameAs https://app.dimensions.ai/details/publication/pub.1061136563
118 rdf:type schema:CreativeWork
119 https://doi.org/10.1109/26.385941 schema:sameAs https://app.dimensions.ai/details/publication/pub.1061136889
120 rdf:type schema:CreativeWork
121 https://doi.org/10.1109/35.364929 schema:sameAs https://app.dimensions.ai/details/publication/pub.1061159042
122 rdf:type schema:CreativeWork
123 https://doi.org/10.1109/35.536564 schema:sameAs https://app.dimensions.ai/details/publication/pub.1061159293
124 rdf:type schema:CreativeWork
125 https://doi.org/10.1109/35.556485 schema:sameAs https://app.dimensions.ai/details/publication/pub.1061159326
126 rdf:type schema:CreativeWork
127 https://doi.org/10.1109/49.329336 schema:sameAs https://app.dimensions.ai/details/publication/pub.1061177103
128 rdf:type schema:CreativeWork
129 https://doi.org/10.1109/49.490411 schema:sameAs https://app.dimensions.ai/details/publication/pub.1061177410
130 rdf:type schema:CreativeWork
131 https://doi.org/10.1109/49.490412 schema:sameAs https://app.dimensions.ai/details/publication/pub.1061177411
132 rdf:type schema:CreativeWork
133 https://doi.org/10.1109/49.553680 schema:sameAs https://app.dimensions.ai/details/publication/pub.1061177573
134 rdf:type schema:CreativeWork
135 https://doi.org/10.1109/76.134371 schema:sameAs https://app.dimensions.ai/details/publication/pub.1061221776
136 rdf:type schema:CreativeWork
137 https://doi.org/10.1109/76.538925 schema:sameAs https://app.dimensions.ai/details/publication/pub.1061222023
138 rdf:type schema:CreativeWork
139 https://doi.org/10.1109/90.282603 schema:sameAs https://app.dimensions.ai/details/publication/pub.1061247074
140 rdf:type schema:CreativeWork
141 https://doi.org/10.1109/90.554723 schema:sameAs https://app.dimensions.ai/details/publication/pub.1061247283
142 rdf:type schema:CreativeWork
143 https://doi.org/10.1109/98.382529 schema:sameAs https://app.dimensions.ai/details/publication/pub.1061251584
144 rdf:type schema:CreativeWork
145 https://doi.org/10.1109/98.490750 schema:sameAs https://app.dimensions.ai/details/publication/pub.1061251615
146 rdf:type schema:CreativeWork
147 https://doi.org/10.1109/98.536477 schema:sameAs https://app.dimensions.ai/details/publication/pub.1061251625
148 rdf:type schema:CreativeWork
149 https://doi.org/10.1109/98.536479 schema:sameAs https://app.dimensions.ai/details/publication/pub.1061251627
150 rdf:type schema:CreativeWork
151 https://www.grid.ac/institutes/grid.273335.3 schema:alternateName University at Buffalo, State University of New York
152 schema:name Department of Electrical & Computer Engineering, State University of New York at Buffalo, 14260, Buffalo, NY, USA
153 rdf:type schema:Organization
154 https://www.grid.ac/institutes/grid.30064.31 schema:alternateName Washington State University
155 schema:name School of Electrical Engineering & Computer Science, Washington State University, 99164, Pullman, WA, USA
156 rdf:type schema:Organization
 




Preview window. Press ESC to close (or click here)


...