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563
Wireless mesh networks: a survey
- COMPUTER NETWORKS
, 2005
"... Wireless meshnet8Ex8 (WMNs)consist of meshrout6L and meshclient8 where meshroutfix have minimal mobilit and formtr backbone of WMNs. They provide netide access for bot mesh andconvent1)fi8 clientt TheintL gratLfl of WMNs wit ot8 net8866 such as t1Int6fiPx1 cellular, IEEE 802.11, IEEE 802.15, IEEE 8 ..."
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Cited by 658 (12 self)
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Wireless meshnet8Ex8 (WMNs)consist of meshrout6L and meshclient8 where meshroutfix have minimal mobilit and formtr backbone of WMNs. They provide netide access for bot mesh andconvent1)fi8 clientt TheintL gratLfl of WMNs wit ot8 net8866 such as t1Int6fiPx1 cellular, IEEE 802.11, IEEE 802.15, IEEE 802.16, sensor netsor1L ets can be accomplishedtccomp tc gatomp and bridging functng1 in t1 meshroutfijx Meshclient can be eit8fi st8fij1)6x or mobile, and can form aclient meshnet16S amongtng1fifiELj and wit meshroutLfifi WMNs are antLfifl1)6fl t resolvets limit18fiflfl andt significantfl improvetp performance of ad hocnetLEP8L wireless local area net1Pxx (WLANs), wireless personal areanet16fij (WPANs), and wirelessmetess1fifljfl areanet1LPS (WMANs). They are undergoing rapid progress and inspiring numerousdeploymentS WMNs will deliver wireless services for a largevariet ofapplicat6fifl in personal, local, campus, andmet8Lfix1)6fi areas. Despit recent advances in wireless mesh netjLfiP1)6 many research challenges remain in allprotjfiS layers. This paperpresent adetEfl81 stEonrecent advances and open research issues in WMNs. Syst1 architL881)6 andapplicat)68 of WMNs are described, followed by discussingts critssi factss influencingprotenc design.Theoret8fiL netore capacit and tdst1LLSjx tt1LL protLLSj for WMNs are exploredwit anobjectE1 t point out a number of open research issues. Finally,tnal beds,indust681 pract68 andcurrent strent actntx1) relatt t WMNs arehighlight8x # 2004 Elsevier B.V. Allrl rl KedI7-8 Wireless meshnet186flfl Ad hocnet8jEES Wireless sensornetor16fl Medium accessconts1fi Routs1 prots1fiS Transport protspor ScalabilitS Securiti Powermanagement andcontfi8fl Timingsynchronizat ion 1389-1286/$ - seefront matt # 2004 Elsevier B.V. Allright reserved. doi:10....
XORs in the air: practical wireless network coding
- In Proc. ACM SIGCOMM
, 2006
"... This paper proposes COPE, a new architecture for wireless mesh networks. In addition to forwarding packets, routers mix (i.e., code) packets from different sources to increase the information content of each transmission. We show that intelligently mixing packets increases network throughput. Our de ..."
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Cited by 534 (17 self)
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This paper proposes COPE, a new architecture for wireless mesh networks. In addition to forwarding packets, routers mix (i.e., code) packets from different sources to increase the information content of each transmission. We show that intelligently mixing packets increases network throughput. Our design is rooted in the theory of network coding. Prior work on network coding is mainly theoretical and focuses on multicast traffic. This paper aims to bridge theory with practice; it addresses the common case of unicast traffic, dynamic and potentially bursty flows, and practical issues facing the integration of network coding in the current network stack. We evaluate our design on a 20-node wireless network, and discuss the results of the first testbed deployment of wireless network coding. The results show that COPE largely increases network throughput. The gains vary from a few percent to several folds depending on the traffic pattern, congestion level, and transport protocol.
ExOR: Opportunistic Multi-Hop Routing for Wireless Networks
- in SIGCOMM
, 2005
"... This paper describes ExOR, an integrated routing and MAC protocol that increases the throughput of large unicast transfers in multi-hop wireless networks. ExOR chooses each hop of a packet’s route after the transmission for that hop, so that the choice can reflect which intermediate nodes actually r ..."
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Cited by 455 (0 self)
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This paper describes ExOR, an integrated routing and MAC protocol that increases the throughput of large unicast transfers in multi-hop wireless networks. ExOR chooses each hop of a packet’s route after the transmission for that hop, so that the choice can reflect which intermediate nodes actually received the transmission. This deferred choice gives each transmission multiple opportunities to make progress. As a result ExOR can use long radio links with high loss rates, which would be avoided by traditional routing. ExOR increases a connection’s throughput while using no more network capacity than traditional routing. ExOR’s design faces the following challenges. The nodes that receive each packet must agree on their identities and choose one forwarder. The agreement protocol must have low overhead, but must also be robust enough that it rarely forwards a packet zero times or more than once. Finally, ExOR must choose the forwarder with the lowest remaining cost to the ultimate destination. Measurements of an implementation on a 38-node 802.11b test-bed show that ExOR increases throughput for most node pairs when compared with traditional routing. For pairs between which traditional routing uses one or two hops, ExOR’s robust acknowledgments prevent unnecessary retransmissions, increasing throughput by nearly 35%. For more distant pairs, ExOR takes advantage of the choice of forwarders to provide throughput gains of a factor of two to four.
Embracing wireless interference: Analog network coding
- in ACM SIGCOMM
, 2007
"... Traditionally, interference is considered harmful. Wireless networks strive to avoid scheduling multiple transmissions at the same time in order to prevent interference. This paper adopts the opposite approach; it encourages strategically picked senders to interfere. Instead of forwarding packets, r ..."
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Cited by 353 (10 self)
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Traditionally, interference is considered harmful. Wireless networks strive to avoid scheduling multiple transmissions at the same time in order to prevent interference. This paper adopts the opposite approach; it encourages strategically picked senders to interfere. Instead of forwarding packets, routers forward the interfering signals. The destination leverages network-level information to cancel the interference and recover the signal destined to it. The result is analog network coding because it mixes signals not bits. So, what if wireless routers forward signals instead of packets? Theoretically, such an approach doubles the capacity of the canonical relay network. Surprisingly, it is also practical. We implement our design using software radios and show that it achieves significantly higher throughput than both traditional wireless routing and prior work on wireless network coding. 1.
Trading structure for randomness in wireless opportunistic routing
, 2007
"... Opportunistic routing is a recent technique that achieves high throughput in the face of lossy wireless links. The current opportunistic routing protocol, ExOR, ties the MAC with routing, imposing a strict schedule on routers ’ access to the medium. Although the scheduler delivers opportunistic gain ..."
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Cited by 290 (8 self)
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Opportunistic routing is a recent technique that achieves high throughput in the face of lossy wireless links. The current opportunistic routing protocol, ExOR, ties the MAC with routing, imposing a strict schedule on routers ’ access to the medium. Although the scheduler delivers opportunistic gains, it misses some of the inherent features of the 802.11 MAC. For example, it prevents spatial reuse and thus may underutilize the wireless medium. It also eliminates the layering abstraction, making the protocol less amenable to extensions to alternate traffic types such as multicast. This paper presents MORE, a MAC-independent opportunistic routing protocol. MORE randomly mixes packets before forwarding them. This randomness ensures that routers that hear the same transmission do not forward the same packets. Thus, MORE needs no special scheduler to coordinate routers and can run directly on top of 802.11. Experimental results from a 20-node wireless testbed show that MORE’s median unicast throughput is 22 % higher than ExOR, and the gains rise to 45 % over ExOR when there is a chance of spatial reuse. For multicast, MORE’s gains increase with the number of destinations, and are 35-200 % greater than ExOR.
A Measurement Study of Vehicular Internet Access Using
- In Situ Wi-Fi Networks. In 12th ACM MOBICOM Conf
, 2006
"... The impressive penetration of 802.11-based wireless networks in many metropolitan areas around the world offers, for the first time, the opportunity of a “grassroots ” wireless Internet service provided by users who “open up ” their 802.11 (Wi-Fi) access points in a controlled manner to mobile clien ..."
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Cited by 190 (6 self)
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The impressive penetration of 802.11-based wireless networks in many metropolitan areas around the world offers, for the first time, the opportunity of a “grassroots ” wireless Internet service provided by users who “open up ” their 802.11 (Wi-Fi) access points in a controlled manner to mobile clients. While there are many business, legal, and policy issues to be ironed out for this vision to become reality, we are concerned in this paper with an important technical question surrounding such a system: can such an unplanned network service provide reasonable performance to network clients moving in cars at vehicular speeds? To answer this question, we present the results of a measurement study carried out over 290 “drive hours ” over a few cars under typical driving conditions, in and around the Boston metropolitan area (some of our data also comes from a car in Seattle). With a simple caching optimization to speed-up IP address acquisition, we find that for our driving patterns the median duration of linklayer connectivity at vehicular speeds is 13 seconds, the median connection upload bandwidth is 30 KBytes/s, and that the mean duration between successful associations to APs is 75 seconds. We also find that connections are equally probable across a range of urban speeds (up to 60 km/hour in our measurements). Our end-toend TCP upload experiments had a median throughput of about 30 KBytes/s, which is consistent with typical uplink speeds of home broadband links in the US. The median TCP connection is capable of uploading about 216 KBytes of data. Our high-level conclusion is that grassroots Wi-Fi networks are viable for a variety of applications, particularly ones that can tolerate intermittent connectivity. We discuss how our measurement results can improve transport protocols in such networks.
Robust rate adaptation for 802.11 wireless networks
- in ACM Mobicom
, 2006
"... Rate adaptation is a mechanism unspecified by the 802.11 standards, yet critical to the system performance by exploiting the multi-rate capability at the physical layer. In this paper, we conduct a systematic and experimental study on rate adaptation over 802.11 wireless networks. Our main contribut ..."
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Cited by 184 (3 self)
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Rate adaptation is a mechanism unspecified by the 802.11 standards, yet critical to the system performance by exploiting the multi-rate capability at the physical layer. In this paper, we conduct a systematic and experimental study on rate adaptation over 802.11 wireless networks. Our main contributions are two-fold. First, we critique five design guidelines adopted by most existing algorithms. Our study reveals that these seemingly correct guidelines can be misleading in practice, thus incur significant performance penalty in certain scenarios. The fundamental challenge is that rate adaptation must accurately estimate the channel condition despite the presence of various dynamics caused by fading, mobility and hidden terminals. Second, we design and implement a new Robust Rate Adaptation Algorithm (RRAA) that addresses the above challenge. RRAA uses short-term loss ratio to opportunistically guide its rate change decisions, and an adaptive RTS filter to prevent collision losses from triggering rate decrease. Our extensive experiments have shown that RRAA outperforms three well-known rate adaptation solutions (ARF, AARF, and SampleRate) in all tested scenarios, with throughput improvement up to 143%.
RSSI is Under Appreciated
- In Proceedings of the Third Workshop on Embedded Networked Sensors (EmNets
, 2006
"... There is a general belief in the Wireless Sensor Network (WSN) community that the received signal strength indicator (RSSI) is a bad estimator of the link quality. This belief is due to the existence of many asymmetry links in older radios such as CC1000 and TR1000. Newer radios that are based on IE ..."
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Cited by 178 (5 self)
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There is a general belief in the Wireless Sensor Network (WSN) community that the received signal strength indicator (RSSI) is a bad estimator of the link quality. This belief is due to the existence of many asymmetry links in older radios such as CC1000 and TR1000. Newer radios that are based on IEEE 802.15.4 standard such as CC2420 implement another parameter called link quality indicator (LQI) which is believed to be a better indicator than RSSI. There is so far no extensive evaluation of CC2420 to validate this claim. We have conducted such an evaluation and our preliminary results indicate that RSSI for a given link has very small variation over time for a link. Our results also indicate that when the RSSI is above the sensitivity threshold (about-87 dBm), the packet reception rate (PRR) is atleast 85%. Around this sensitivity threshold, however, the PRR is not correlated possibly due to variations in local phenomena such as noise. LQI, on the other hand, varies over a wider range over time for a given link. However, the mean LQI computed over many packets has a better correlation with PRR. 1.
Jigsaw: Solving the puzzle of enterprise 802.11 analysis
- In SIGCOMM
, 2006
"... The combination of unlicensed spectrum, cheap wireless interfaces and the inherent convenience of untethered computing have made 802.11-based networks ubiquitous in the enterprise. Modern universities, corporate campuses and government offices routinely deploy scores of access points to blanket thei ..."
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Cited by 173 (12 self)
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The combination of unlicensed spectrum, cheap wireless interfaces and the inherent convenience of untethered computing have made 802.11-based networks ubiquitous in the enterprise. Modern universities, corporate campuses and government offices routinely deploy scores of access points to blanket their sites with wireless Internet access. However, while the fine-grained behavior of the 802.11 protocol itself has been well studied, our understanding of how large 802.11 networks behave in their full empirical complexity is surprisingly limited. In this paper, we present a system called Jigsaw that uses multiple monitors to provide a single unified view of all physical, link, network and transport-layer activity on an 802.11 network. To drive this analysis, we have deployed an infrastructure of over 150 radio monitors that simultaneously capture all 802.11b and 802.11g activity in a large university building (1M+ cubic feet). We describe the challenges posed by both the scale and ambiguity inherent in such an architecture, and explain the algorithms and inference techniques we developed to address them. Finally, using a 24-hour distributed trace containing more than 1.5 billion events, we use Jigsaw’s global cross-layer viewpoint to isolate performance artifacts, both explicit, such as management inefficiencies, and implicit, such as co-channel interference. We believe this is the first analysis combining this scale and level of detail for a production 802.11 network.
Measurement-based models of delivery and interference in static wireless networks
- in SIGCOMM Computer and Communications Review
, 2006
"... We present practical models for the physical layer behaviors of packet reception and carrier sense with interference in static wireless networks. These models use measurements of a real network rather than abstract RF propagation models as the basis for accuracy in complex environments. Seeding our ..."
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Cited by 172 (1 self)
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We present practical models for the physical layer behaviors of packet reception and carrier sense with interference in static wireless networks. These models use measurements of a real network rather than abstract RF propagation models as the basis for accuracy in complex environments. Seeding our models requires N trials in an N node network, in which each sender transmits in turn and receivers measure RSSI values and packet counts, both of which are easily obtainable. The models then predict packet delivery and throughput in the same network for different sets of transmitters with the same node placements. We evaluate our models for the base case of two senders that broadcast packets simultaneously. We find that they are effective at predicting when there will be significant interference effects. Across many predictions, we obtain an RMS error for 802.11a and 802.11b of a half and a third, respectively, of a measurement-based model that ignores interference. Categories and Subject Descriptors C.4 [Performance of systems]: Modeling techniques
