Sufficient rate constraints for QoS flows in ad-hoc networks

Gupta, Rajarshi; Musacchio, John; Walrand, Jean

doi:10.1016/j.adhoc.2006.01.003

Cited by 92 publications

(112 citation statements)

References 21 publications

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“…Given a network graph G = (V, L), define its conflict graph to be G C = (L, L ′ ), where two links ℓ 1 and ℓ 2 are adjacent in the conflict graph if and only if they interfere with each other due to being in the same vicinity and hence cannot be simultaneously active. This interference model has been studied recently by a number of authors; for example, see Jain et al [16], Hamdaoui and Ramanathan [15], and Gupta, Musacchio and Walrand [11]. A special case of this model, where two links are considered to be interfering if and only if they are incident (in the network graph) to a common node, has been studied earlier by Hajek [12], Hajek and Sasaki [13], and Kodialam and Nadagopal [17].…”

Section: Introductionmentioning

confidence: 99%

Performance of sufficient conditions for distributed quality-of-service support in wireless networks

Ganesan

2013

Wireless Netw

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Given a wireless network where some pairs of communication links interfere with each other, we study sufficient conditions for determining whether a given set of minimum bandwidth quality-of-service (QoS) requirements can be satisfied. We are especially interested in algorithms which have low communication overhead and low processing complexity. The interference in the network is modeled using a conflict graph whose vertices correspond to the communication links in the network. Two links are adjacent in this graph if and only if they interfere with each other due to being in the same vicinity and hence cannot be simultaneously active. The problem of scheduling the transmission of the various links is then essentially a fractional, weighted vertex coloring problem, for which upper bounds on the fractional chromatic number are sought using only localized information. We recall some distributed algorithms for this problem, and then assess their worst-case performance. Our results on this fundamental problem imply that for some well known classes of networks and interference models, the performance of these distributed algorithms is within a bounded factor away from that of an optimal, centralized algorithm. The performance bounds are simple expressions in terms of graph invariants. It is seen that the induced star number of a network plays an important role in the design and performance of such networks.Index terms -flow admission control, quality-of-service (QoS), distributed algorithms, interference, wireless networks, conflict graph, link scheduling; fractional chromatic number; induced star number. IntroductionIn recent years there has been an increasing interest in using data networks to support a wide variety of applications, each requiring a different Quality-of-Service (QoS). For example, real-time applications such as voice, video and industrial control are time-sensitive and require that the delay be small, while for other data applications the sender may require that a constant, minimum bit-rate service be provided. In the simplest and lowest level of service, such as the one provided in the Internet Protocol service model, the network makes a best-effort to deliver data from the source to destination, but it makes no guarantees of any kind, so it is possible that packets can get dropped, delayed, or delivered out of order. However, this basic level of service is insufficient for many data applications such as * This work was carried out while the author was with the ECE Department, University of Wisconsin at Madison, WI 53706, USA. This work was presented in part at the International Conference on Networks and Communications (GraphHoc and NetCoM), Chennai, India, December 2009 [5], and at the International Conference on Recent Trends in Graph Theory and Combinatorics (an ICM Satellite Conference), Cochin, India, August 2010 [6]. This paper is a revised version of the Technical Report [8]. The author is with the Department of Mathematics, Amrita School of Engineering, Amrita University, Coimbato...

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Section: Introductionmentioning

confidence: 99%

Performance of sufficient conditions for distributed quality-of-service support in wireless networks

Ganesan

2013

Wireless Netw

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“…The problem of transmission constraints has also been studied in [4], [12] and [16]. (We will denote the particular constraint considered at a time as (T )).…”

Section: Routing and Scheduling Aggregate Trafficmentioning

confidence: 99%

“…In the following we provide the performance of this LP solution. For this example we did not run the nonlinear optimization (11)- (12). However see [6], [20].…”

Section: Simulationsmentioning

confidence: 99%

Providing QoS to Real and Data Applications in WiMAX Mesh Networks

Sharma

Kumar

Sandeep

et al. 2008

2008 IEEE Wireless Communications and Networking Conference

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Abstract-We consider the problem of centralized routing and scheduling for IEEE 802.16 mesh networks so as to provide Quality of Service (QoS) to individual real and interactive data applications. We first obtain an optimal and fair routing and scheduling policy for aggregate demands for different sourcedestination pairs. We then present scheduling algorithms which provide per flow QoS guarantees while utilizing the network resources efficiently. Our algorithms are also scalable: they do not require per flow processing and queueing and the computational requirements are modest. We have verified our algorithms via extensive simulations.

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“…But actually it is easier to compute cliques since they are made of closed links and nodes usually have a better knowledge of their neighborhood. So cliques are often preferred in the literature to compute constraints on flows [7], [11].…”

Section: A Network Modelmentioning

confidence: 99%

“…• power control where n can emit with a higher power to contact nodes within its carrier sensing range directly [3]; • a N-hop interference model where node n interferes with its N-hop neighbors; • localization informations [7]. The whole network interferences can be represented by a conflict graph where interfering links are linked.…”

Section: A Network Modelmentioning

confidence: 99%

Idle Channel Time Estimation in Multi-Hop Wireless Networks

Odou

Martin

Agha

2009

2009 IEEE International Conference on Communications

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Abstract-This paper presents a theoretical estimation for idle channel time in a multi-hop environment. Idle channel time is the time proportion of a node during which the channel state is idle. Thus, it can be used to evaluate the available bandwidth. Major related work considers a cross-layer model, where the idle channel time measure is available at the MAC layer, but it is rarely implemented. Furthermore, this measure is not very flexible: it cannot differentiate the traffic's priorities and it works under the hypothesis that flows are strictly policed. Estimating instead of measuring the idle channel time prevents these drawbacks. This estimation is computed in three steps by (1) calculating the idle channel time bounds, (2) evaluating the probability of a given idle channel time value, (3) computing the expected value of this distribution and deducing the average idle channel time. We show by simulation that our estimation is accurate.

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Sufficient rate constraints for QoS flows in ad-hoc networks

Cited by 92 publications

References 21 publications

Performance of sufficient conditions for distributed quality-of-service support in wireless networks

Performance of sufficient conditions for distributed quality-of-service support in wireless networks

Providing QoS to Real and Data Applications in WiMAX Mesh Networks

Idle Channel Time Estimation in Multi-Hop Wireless Networks

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